The Death of Microservice Madness in 2018
dwmkerr.com
dwmkerr.com
As an Infrastructure guy, the pattern I've seen time and time again is Developers thinking the previous generation had no idea what they were doing and they'll do it way better. They usually nail the first 80%, then hit a new edge case not well handled by their architecture/model (but was by the old system) and/or start adding swathes of new features during the rewrite.
In my opinion, only the extremely good developers seem to comprehend that they are almost always writing what will be considered the "technical debt" of 5 years from now when paradigms shift again.
Developers want to own their thing. Microserivces desire springs up because of a lack of communication culture and desire for siloification in a companies organization to keep various interests from bothering the developers. Those almost always point to a failure of management in my mind rather than a technical failure.
If a few things are true, I could see this as a win:
* I can isolate my developers from outside interests using microservices. * My developers are more effective in each dimension (quality, retention/happiness, velocity) because they are isolated from outside interests. * My software is easier to operate and more reliable because it is a microservice.
If any of these three things aren't true, then I agree. But I'm not sure that a "communication culture" can scale to a large organization and I'd like to see a truly large company (1000+ developers) successfully doing so. I've seen more success come from separation of concerns and well-deployed microservices seem to be fairly effective to this end.
Conway's Law might as well be renamed "The Law of Microservices". Per Wikipedia [0], it states:
> "organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations."
"Microservices" are on a tear because they make a perfect cover for the blatant and bare expression of unbridled Conway's Law.
Such unbridled expression is much easier in the course of greenfield development, because it lets the core team of 2-3 people per service go about their development work without consulting anyone external. It lets them throw away any overriding convention or cultural concerns, and it avoids the difficulties of cross-group coordination. But it leads to a completely unmaintainable wreck when things transition into production.
This is not to say that no one will have a successful microservice deployment or that it's always a bad choice, but it usually goes way off the rails.
The parent post I was replying to seemed to simplify things down to "let your developers communicate and they'll build a more coupled system that works, instead of a morass of microservices that don't." That's another thing that looks good on paper but doesn't scale, at least in my experience.
I think in many cases microservice architectures appeal to engineering organizations with poor communication and cooperation skills where developers desire to be strongly independent because of the lack of management creating a cooperative and coordinated dev and work environment. I think that's actually saying something very similar to the Conway Law idea brought up by the other poster.
When I see a team of 7 deciding to go with microservices for a new project I know they're gonna be in for a world of unnecessary pain.
So if Netflix has a "User logon" service, and a "payment processing" service, used across their clients clients you might be looking at a couple of "microservice"s with hundreds of related employees. Imagine services for Googles search autocomplete, ML, or analytics...
As the article states the "micro" aspect is mostly in terms of deployment responsibility, freeing those 10-1000 employees from thinking about the totality of Googles/Netflixes' operations before rolling out a patch :)
It’s 8 or so but it’s possible for me to handle it all. If we add features they’re going to be new services, so adding big features to the services I manage is unlikely. It is more likely that I get a new service on my plate in 6 months time than getting additional members of the engineering team to work on already completed services.
I’m obviously not entirely alone... I’ll ask for help if I need it, and I help out with other people’s stuff too, but I am primarily in charge of them and I am responsible for keeping everything working well.
If it takes 10 people to manage one service, it is not a microservice by definition. It is more like a 10x-microservice or a macroservice.
The definition isn't small teams, per se, it's a small area of responsibility with singular focus. A lego block instead of duplo. That lends itself very well to small teams, but you could reasonably have 100 people working on a service and call it "micro".
Reason being: if those 100 people weren't working on their scoped 'microservice' they would be part of a much, much, much larger pool working on the shared 'product', 'platform', or 'service' that contains that exact same functionality, only without the clarity/scalability of application boundaries surrounding the individual service components.
That's not to say microservices are ideal, just that the size of "micro" is highly relative to ongoing operations.
These days I kinda wince at "I run 8 services myself."
If it takes 1 person to run 1 microservice, we are all doomed.
I also feel that ceteris paribus, the meetings got longer, project management tools now consume a lot of input from programmers, and I need to communicate with a lot more people to get something done.
Which seems to end up meaning productivity has gone down when measured by "things end users of websites can do", even though modern FE devs end up creating much more code and html and css than "the old days". (Admittedly, if you include privacy invasion, user tracking, and various other requirements of surveillance capitalism, dev productivity has probably skyrocketed...)
Complex? We still call a function with a return value on a stackmachine.
Sorry for the negativity.
And yet, most homepages today can't be viewed without javascript. You are correct, for the end user the complexity has absolutely not resulted in better homepages but worse.
Higher levels of abstraction makes it easier to get something up and running fast, but at some point you need to be able to look under the hood and understand what's going on, and many programmers today can't do that.
That being said I think the drop in average skill is mostly a product of the growth in the number of programmers. I imagine that if the ability to sculpt a basic statue suddenly became really valuable, the skill level of the average working sculptor would plummet.
More layers of indirection in a system and more dependencies on external libraries and tooling does not necessarily get you any abstractions. To take a contemporary example, there is no "abstraction" in being driven to use Docker because your dependencies have gotten unmanageable otherwise.
seq 21 | while read port; do
python2 -m SimpleHTTPServer 80$port &
done seq 21 | while read port; do
python3 -m http.server 80$port &
done
And it's just one of many.
One developer can certainly be responsible for coding many microservices and even maintaining them depending on the scope, number of users, etc.
Sometimes people might even rotate with a core architect coordinating how they all interact and if they are consistent with each other.
Discussing about microservices can be very confusing if people are thinking about different things and, as always, when there's a good idea implemented in a specific context and people who don't use it get exposed to it as a silver bullet we'll end up with a huge backlash like in this article.
Had to implement a micro-service architecture in python about a year ago and was jealous of my Java colleagues who (so I heard) have great ecosystem for enterprise service discovery, messaging etc.
It does have a single point of failure that is also a bottleneck (the router) and it's a lot of work to load balance / failover it.
But other than that, it provides a fantastic way to make microservices:
- anything is a client of the crossbar router. Your server code is a client. The db can be a client. The web page JS code is a client. And they all talk to each others.
- A client can expose any function to be called remotely by giving it a name. Another client can call this function by simply providing the name. Clients don't need to know each others. Routed RPC completly decoupled the clients from each others.
- A client can subscribe to a topic at any time and be notified when anothe client publishes a message on that topic. Quick, easy and powerful PUB/SUB with wildcard.
- A client can be written in JS (node and browser), Python, C#, Java, PHP, etc. Clients from other languages can talk to each others transparently. They all just receive JSON/msgpack/whatever and error are propagated and turn into the native language error handling mechanisme transparently.
- The API is pretty simple. If you tried SOAP or CORBA before, this is way, way, way simpler. It feels more like using redis.
- It uses websockets, which mean it works anywhere HTTP works. Including a web page or behind a NAT or with TLS.
- Everything is async. The router handles 6000 msg / s to 1000 clients on a small Raspberry Pi.
- The router can act as a process manager and even a static / wsgi web server.
- you can load balance any clients, hot swap them, ban them, get meta event about the whole system, etc.
- you can asign clients permissions, authentications, etc. Sessions are attached to each connexion, so clients knows what other clients can do.
Service Lookup - Hashicorp's Consul.
Authorization/Authentication - I've played with Hashicorp's Vault. It seems overly complicated but the advantage is that it doesn't tie you to a single solution and it can use almost anything as a back end. I haven't had to solve that problem yet.
hahaha
Do you know if there are some well chronicled cases of this happening? I find it very believable, but you know, would love to read something "actual".
A kinda-random example off the top of my head of "shipping the org chart" would be the historical gaps between Windows, Development, and Office at Microsoft. Ie Office is getting a new ribbon, but no development can't supply those icons or any components because they're an "office thing", or the internal API/VBA battles along the same lines.
On the opposite side, as reported in the press, Amazon has used this effect to create manageable teams and build up their own SOA: the two-pizza rule for teams means that teams can only really make targeted self-contained services. In this case Amazon worked backwards and re-structured their teams so that 'shipping their org chart' created the desired architecture.
Microsoft has an app store built into every Windows 10 computer worldwide. And of course, you can not download Microsoft Office from it. However, it does helpfully tell you to get Office by heading to 'MicrosoftStore.com'.
It's all sort of head scratching. A normal person might ask a lot of totally reasonable questions about this, like:
- Why does Microsoft's App Store not have Microsoft's own Apps in it? Office isn't the only missing app, Visual Studio is missing too (even the free 'Code' electron editor).
- Why does the phrase 'Microsoft Store' refer to something 100% different (in products and functions) than 'MicrosoftStore.com'?
- Why does the Office team have their own app updating utility, when there's already supposed to be one 'blessed' place for App Updates inside the Store? (Same question for Visual Studio Code).
---
Anyway, I know a lot of the above is org chart related, or enterprise needs / backwards compatibility related. But they are all reasonable questions despite that.
And stuff like this is part of the reason why reasonable people still fall for phishing schemes. The above sounded to me like some weird popup advertisement trick, until I saw it first hand.
(Isn't it the only way to get Apple software for your Apple devices, even?)
Not that this actually happens-or would be a particularly good idea if it did for other reasons (like breaking up teams etc).
YAGNI is almost always the right approach.
There have been plenty of times where I've taken a project out of a monolith and created a separate shippable package to be consumed by another monolith in a separate repo.
There were also occasions where I had to rip out a feature in a monolithic API that either needed to scale independently or be released independently and then just created a facade in the originally API that proxies the "microservice".
I mostly tell my people "We aren't going to do that yet - or possibly ever - but keep in mind that we might have to if we ever win the user growth hockey-stick graph lottery, so when choosing between options of how to architect things, prefer very narrow focus that _could_ be pulled apart into microservices more easily if practical"
I've also been known to stand up duplicated instances on a monolith with path routing on the load balancer as a "pretend microservices" scaling or upgrade trick.
Decomposing and fragmenting an established service into smaller clones of itself should be reasonably straightforward. In most languages with a component story (ie java), library reuse across microservices should make your service architecture orthogonal to your application logic. This kind of approach also eases a lot of pain of cross-service issues.
Faced this a couple of years ago, and I was the lone dissenting voice suggesting this was not going to go well. Then I learned that "microservice" in reality just meant everything was going to be one nodejs process running endpoints, with ios and android clients hitting it, which... didn't really fit my understanding of "microservice"; that's just "service".
Also, the same team spent several hours in meetings deciding whether or not to allow email signup, or facebook signup, or both, or neither, in the mobile app. Then had the same discussions/arguments a few weeks later when a couple new people joined the team.
I realize I sound a bit bitter. I got pushback because I'd used the 'microservice api' in a "we don't like that" language. consuming the api (which I'd understood to be part of the reason of having a central API vs just hitting db tables directly) by anything that wasn't also node was outside the groupthink, and caused problems.
I left the project.
They've got their microservice architecture, but no userbase (yet?) to be concerned about scaling issues.
I understand it's reasonable to be concerned about potential scaling problems, the team/project spent far too much time chasing architectural perfection (and really... 'shiny new stuff') vs executing a marketing plan. It's easier for a group that is tech-folk-heavy to focus on that; I get it. But it didn't solve any problems at hand. But when the mythical "2 million users in an hour" problem happens, it'll probably hold up, unless it doesn't.
Imagine you have a library that implements the serialization and deserialization of something in your system (or anything else where the library implements two "halves" of some functionality). You might (or might not, depending on the change) need to push out that library to other apps to effect the fix you're working on. That new proposed library change may be in a queue behind another pending change that's in development, etc.
And guess what, you have to do the same thing with microservices. You must ensure that all its clients are pointing to the correct version, and you must ensure that the new version didn't add any bugs in the clients.
Adaptations for new service versions will also get into the release queue, and can also get blocked by other stuff.
I chose this approach because the developers who were already there were relatively new to C#, and I knew we were going to have to ramp up contractors relatively fast.
Our dev ops process revolves around creating build and release processes by simply cloning an existing build and release pipeline in Visual Studio Team Services - the hosted version of Team Foundation Services - and changing a variable. Every service is a separate repo. Each dev is responsible for releasing their own service.
The advantages:
1. All green field development for a new dev. They always start with an empty repo when creating a new service.
2. Maintenance is easier. You know going in all you have to do is use a few documented Postman calls to run your program if you need to make changes. Also, it's easy to see what the program does and if you make a mistake, it doesn't affect too many other people if you keep the interface the same.
3. The release process is fast. Once we get the necessary approvals, we can log on to VSTS from anywhere and press a button.
4. Bad code doesn't infest the entire system. The permanent junior employees are getting better by the month and we are all learning what works and doesn't work as we build out the system. Each service is taking our lessons learned into account. We aren't forced to keep living with bad decisions we made earlier and building on top of it.
A microservice strategy only works if you have the support system around it.
In our case, an easy to use continuous integration, continuous deployment system (VSTS), easy configuration (Consul), service discovery and recovery (Consul with watches), automated unit and integration tests, a method to standardize cross cutting concerns
And finally, Hashicorp's Nomad has been a god send for orchestration. Our "services" are really just a bunch of apps. Nomad works with shell scripts, batch files, Docker containers, and raw executables. It was much easier to set up and configure than kubernetes.
This is why a team needs access to good architect who's seen the paradigms shift, or even cycle. You're almost never starting from scratch, so you really need someone who's able to incorporate better or more suitable tech without throwing out the baby.
If you're microservices-based, that last part is easier, even if it falls into one of the described pitfalls, e.g., system-of-systems.
Microservices will not help you if your developers have the same level of skill and foresight as whoever wrote the monolith, which is probably true if those devs were selected by the same hiring process that your company has today, subject to the same organizational effectiveness, etc.
Indeed! Good developers/architects spot repetition or weaknesses in current techniques and can often devise solutions that can be added to the stack or shop practices with minimal impact. You don't necessarily need paradigm or language overhauls to improve problem-areas spotted. Poor developers/architects will screw up the latest and greatest also.
I've also seen really bad developers with that attitude: it's all crap, so just ship whatever already.
The good developers write code that can be replaced, rewritten, or rescaled later. Though, charitably, both monolithic service and microservice people are trying to do exactly that. It's just what sort of scale they're thinking about and what part of the software development lifecycle they think will be especially difficult going forward.
Good developers create code that's prepared for the possibility of being modified repeatedly and becoming foundational; on the other hand, preparing for code/components to be thrown away is a no-op.
You might be agreeing, but I find that the bad code that sticks around is bad code that is hard to get rid of. So in that sense, code that is removable isn't a no-op. It takes some effort, for instance, to keep a clear dividing line between two components so that either may be replaced someday.
You make a very good point.
Over the years, I learnt that almost nobody except the developer and maybe one or two peer-developers cares about good quality code. The management just wants to ship services/products. They don't care how good the code is. All they care is that they can meet their deadlines. Of course, good quality code can increase the chance of meeting deadlines, but working long hours can also increase the chance of meeting deadlines. Management does not understand code, but they understand working long hours.
If I ignore this and still care enough to write good quality code, in nearly all projects, I am not going to be the only one to work on the code. There is going to be a time, when someone else has to work on the code (because responsibilities change, or because I am busy with some other project). As per my anecdata, the number of people who do not care about code quality far exceeds those who do. So this new person would most likely start developing his features on the existing clean code in a chaotic manner without sufficient thought or design. So any carefully written code also tends to become ugly in the long term.
In many cases, you know that you yourself would move out the project/organization to another project/organization in a year or so, and the code would become ugly in the long term no matter what you do, so why bother writing good code in the first place!
It is very disappointing to me that the field of programming and software development that I once used to love so much out of passion has turned out to be such a commercial, artless, and dispassionate field. How do you retain your motivation to be a good developer in such a situation?
No, that's not true, except in a very superficial sense. Yes long hours _can_ increase the chance of meeting deadlines... but often, it doesn't - or more precisely, it only works if the code quality is decent.
"Code quality" is not about following whatever patterns are en vogue today, or using the latest dev language. It is mostly about simplicity - dealing with few things at a time, and making those things explicit. If you need to understand the entire solution, and the entire domain model, and all the edge cases before making the tiniest of modifications - long hours are not going to help you.
To go back to microservices: many companies claim to build microservices, but actually build a distributed monolith. This doesn't help productivity, it actively harms it.
<rant target="not you">
And why should management be able to evaluate technical decisions and code quality in the first place? That's our job! The problem is that we have given management the false choice of lower quality + faster shipping vs. higher quality + slower shipping, when in fact we should not have given them any say in the matter. And before we hit me with the but we have to be first to the market and fix it later line, I need to point out that companies don't die because they were not first to the market, they die because their operations and development became so slow and costly that they could not compete anymore.
What we should do as developers is to stop talking about code quality to our managers! When we are asked for an estimate, we give them as accurate estimate as possible with the code quality that we feel is sufficient for long-term maintainability of the system. And we don't negotiate on quality anymore, and especially we don't negotiate on estimates! Only functionality (MVP and all that). Then we don't need to ask for refactoring time, rewrite time, code polish time, stabilization time on our systems (that we hardly ever get anyway), because it is all in there in the original estimate.
Management expects stable productivity, they base their estimates of operational costs and investment costs on the number of people working on the system, not on the age of the codebase (why should an old codebase cost more to work with? they ask). If we give them false hope on the productivity of the team by producing crap fast in the beginning, the whole business case may collapse when we produce the same crap slower and slower and slower later. Management is in no position to evaluate the effects of bad code on the business case, because they don't understand that. We do. The only thing we can do as developers, is to remove the option of low quality code altogether.
And we say that it is so slow to create quality code? And estimation is hard?
We learn it. We can write high quality code as fast as the usual junk we see in most systems. We keep track on our estimates and evaluate how well we did, and improve. But it takes effort. All I can say is that it is our responsibility.
</rant>
On a positive note, the solution to this on a personal level is to find a place to work where technical excellence is built in the development culture (and there are such places), and cultivate that culture especially with the new hires (mentoring, pairing, etc.).
No, but they do care that this seemingly (to them) trivial change a year later takes two weeks instead of half a day.
> How do you retain your motivation to be a good developer in such a situation?
I honestly don’t know. I’m currently taking a little time out from work, but I’m dreading going back in a month because right now, I am completely disinterested in computers and especially software, things I used to love and be incredibly passionate about. Now with stuff like meltdown and spectre, technology just seems like this dumb house of cards and I have no energy for this BS. I’m pretty sure its burnout and it will pass eventually, but I just hope it does so soon as I don’t know how else to pay the bills.
On the plus side, I’ve spent a lot less time at the computer these last few weeks and spent time on other interests, including learning sleight of hand and card magic. :-P
To me the big benefit of microservices is scaling out components into flexible independent release cadences but the trouble comes with employing them too early.
Rewrites also serve as thorough code review and security audit.
I am more in the camp of "let's do something useful" than "let's rewrite this because previous guy didn't do it good, or it no longer meets our demands". Because whatever you do it will get rewritten again, and it's imho useful to resist the urge.
Ps: also a googler.
There's legitimate arguments for looking at these patterns, the big one being "isolation of concerns". The biggest counterargument is that the ops cost is much higher than assumed, of course.
The idea that the existing code base could have problems shouldn't be a surprise to anyone. Amazon almost fell over because of their code base. Twitter too. And its not even not doing it right, but simply that scales change. Or patterns change.
And in new companies, it _could_ be that people don't get it.
"Microservices as mass delusion" discounts a lot of people who are really thinking hard about how to handle the pros and the cons of things.
As you say there are a lot of pros and cons to any architecture or paradigm, which is why we're still talking about it and saying things like "right tool for the job" and not just using the One True Method(TM).
I legit think that a lot of people using the new hotness as a form of cargo cult programming with no understanding of the methods they're considering or how they apply to the problems they're trying to solve.
It's not just microservices that are improperly applied. I've been in the industry long enough to see dozens of languages, technologies, paradigms, processes, and everything else hailed as the second coming of christ and applied inappropriately all over the place until the shinyness wore off.
And I mean... When we start talking about developing for Amazon scale, we're already talking about situations that don't apply to 99% of developers. Not a great argument that their cases aren't inappropriate applications of the pattern.
There will come a point where you can't scale a monolith, sure, but that point is thousands rather than hundreds of engineers.
If some companies go completely nuts and deploy 5 microservices per developer, then yes, that is madness. If all of those microservices are REST/JSON microservices, that's madness squared because you're wasting half your time in serialization/deserialization. If you're managing all of this stuff with Kubernetes because it's trendy rather than because it's actually necessary for your use case, then you're probably making a bad call.
But ultimately, services give development teams ownership over features in a complete, end-to-end way that is fundamentally impossible with monoliths once you're past a certain size.
The impression I get - and this could be totally wrong - is that the difference is how the services relate to each other.
In this post's example, 5 of the 6 microservices look like something that would be exposed to the user in some way. I would call this a microservice architecture; they're networked together in a way where no one thing orchestrates the others. They likely all touch the same data storage, but the overall structure is mostly flat.
In a service-oriented architecture, there'd be a tree-like or graph-like hierarchy. To an end user, it would look monolithic, but the monolith would, behind the scenes, delegate to the "user-facing" services such as Upload and Download. Upload and Download would then use the Transcode service as appropriate. But the important part is that this would all be one way: Transcode isn't allowed to contact Upload or Download, just return the result to whatever called it.
Yes. That's been my experience.
> The idea that the existing code base could have problems shouldn't be a surprise to anyone. Amazon almost fell over because of their code base. Twitter too.
Most organisations aren't Amazon. Most organisations aren't Twitter. And even these web-scale organisations aren't as all-in as the microservice advocates. (I worked at last.fm for a time and while we did many things that could be classed as "microservices" from a certain perspective, we didn't blindly "microservice all the things")
> "Microservices as mass delusion" discounts a lot of people who are really thinking hard about how to handle the pros and the cons of things.
Most fads start from a core of sensible design. The web really did revolutionise commerce, but many "x, but on the web" companies of the late '90s really were dumb.
I think (at least, I hope) what OP was trying to get at was the relative irrationality of something 1/8000th the cost of the very expensive item taking a very long time to debate through (especially when $100,000 is most probably far less than many of those board members earn as a salary every year)
As Programmers we deal with numbers a lot more often, so this effect is minimized. But still there.
I find I can do most such works better than (average) professionals, but it takes a lot of time to learn, prepare, execute (+ sometimes re-execute) and clean. It all depends on when you are satisfied with the result.
For UK natives it's actually three steps:
"sheetrock" == drywall == Plasterboard
I'm not certain whether the water-resistant, mold-resistant variety typically hung behind tiles in bathrooms is ever referred to as "wetwall" or if they still call it "drywall".
Nor am I aware of whether anyone calls the foil-backed, glass-reinforced, fire-resistant variety "firewall" instead of "drywall".
I wouldn't be surprised if obsolete and inapplicable names still attach to items with the same function. If we ever move to polyethylene film panels sandwiched with phase-change material for our walls, it might still be called "plasterboard" somewhere.
I remember showing up on a site, and the drywall guys had just started carting in a ton of drywall. By the time we left in the afternoon, they had cut, hung, taped and mudded over 3,000 sq feet of home, it was insane.
I managed to paint my walls, but it took me much more time than expected and my flat was chaos for some weeks thereafter.
My parents (not in any way experts on that field) painted their entire house themselves, except for two rooms that were painted by a professional painter, and the professional painter left much worse corners than my parents. This was the paid-for result (ignore the dark corner at the bottom, that’s caused by the flash): https://i.imgur.com/s1VHV2W.jpg
Actually good software engineering is a much larger skill difference.
Based on my years across various companies, the difference between "hobbyist" and "mediocre professional" developer/programmer is close to nil
Also, note that this thread started with a comment about how many developers don't appreciate what the actual hard problems in their own line of work are, and how that produces poor results because of that. I expect that to be true of any profession that doesn't have some kind of rigorously enforced standard.
Painting isn't a profession with a particularly high return on experience. You hire a painter for comparative-advantage reasons. It may take him just as long as it takes you, and several thousand dollars more, but chances are you can make more than several thousand dollars in the time you would've spent painting your house. (If you can't, you may want to re-think hiring a professional, and instead go into business as a painter yourself...)
There is no problem painting for me and many others who know how to use their hand.
Is amazing when you talk to people and they are like: Did you do that? How do you know how to do that?
Learn, try and you can do anything. As people did at every step.
You can just follow all the same steps as you usually do:
1. Define the problem.
2. Determine the desired outcome.
3. Measure the existing state.
4. Note the foreseeable failure modes.
5. Plot the path from existing state to desired outcome as a series of reasonable steps, avoiding the failure modes.
6. Recursively analyze the steps, breaking them down into smaller steps if necessary.
7. Rework your plan as additional failure modes become evident.
In my experience, yes, you can do anything, as long as you ignore costs. You can't, for instance, justify buying a specialized tool to finish just one job. The hardest part is really step 2.
You must be new to DIY :)
If you want a good result don’t skimp on the tools. Buy good quality brushes, rollers, filler, throws and paint. Also buy an edger to cut in the walls and ceilings. One final tip buy some of the disposable plastic liners for the roller tray so you don’t have to spend time washing out the tray at the end of the day.
On the sand paper front make sure to spend money there. Cheap sandpaper last 2 nanoseconds and does a terrible job.
On the other hand, coming from a country that takes its trades extremely serious, I was shocked about what I observed every time I visited the UK. It seems the expectations vary drastically between different countries (though I'm sure there are quality professionals in the UK too).
House price / rent value is basically dependent on location. Money spent on fitting is generally wasted.
There are a lot of great craftsmen in the UK, but they tend to work on a subset of jobs - restoration, passion projects, really high-end stuff.
PS: This is also a direct result of ever-rising house prices. If land/house prices are consistently rising, it often makes more sense to let lots stay empty, rather than building (which is always a massive risk). It also makes sense to do any repair or upkeep work as cheaply as possible - since in a rising market, the only way you can lose money is by expensive development costs.
1 - there are very good professionals, but they aren't cheap and have all the work they need
2 - an amateur can always decide to take economically irrational amounts of time on a project; a professional can't.
So the result is that as a careful amateur you can end up with a job you probably wouldn't be able to convince yourself to pay for.
We can probably all agree that the worst case is the careless amateur....
I am not sure that description is apt. Underdelivering is only rational for the painter because the client won't be on the market long enough to gather sufficient information. The client is getting cheated, and it creates a lemons market, the fact that it is a Nash equilibrium does not make avoiding the entire thing irrational.
And the entire thing has parallels on software development...
An amateur painter will often spend far more time than any reasonable estimation of the market value of that job would justify. Part of this is lack of efficiency and experience, but another part is doing things with sharply diminishing returns. For example, you might apply expensive techniques to inexpensive materials, in a way that would not make for a viable business.
Put it another way - amateurs can easily arrive at a finished job (of painting, in this case) that they would never be able to convince themselves to pay market rate for. This is irrational in certain restricted senses.
For what it's worth I don't believe that "lemons market" is accurate for painters in general, but I'm guessing there is a segment of it that meets your description.
If you're looking at it from a economic standpoint, to be considered irrational, the tradeoff between the value of time vs the cost of hiring a professional would have to assume that the value of the time is greater than the value of the professional.
I always hear this compared to "what is your hourly rate in your job" or "my time is worth more than that", but I think for most people this just isn't a fair comparison. Just because I can spend 10 hours painting my room and I make $x/hour and it would cost <$x to pay a professional, does not mean I would be able to actually generate an _incremental_ $x per hour by not painting and hiring the professional.
For most people on a salary (where your pay is fixed no matter how much time you put in), their time outside of the job is, in a very real sense from an economic standpoint, valueless, and it would be perfectly rational to spend that time yourself, no matter how cheaply a professional could do it.
If you're looking at it from a economic standpoint, to be considered irrational, the tradeoff between the value of time vs the cost of hiring a professional would have to assume that the value of the time is greater than the value of the professional.
For what it’s worth, I don’t think we are really disagreeing much.
Even on the financial level tradesmen here in Australia are so overpaid (compared to everyone else) that it makes sense even for me to do it myself. My house was painted by "professionals" just before we moved in (purple??) and it cost the previous owner $20,000. My wife and I repainted it white (this required 5 coats of paint) and it took us two weeks including the time I had to spend getting the purple paint off the windows and floors and patching all the holes that had been painted over.
Tip. If you are selling your home don't paint it some unusual color. I managed to buy my home $200K under its actual market value and quite a bit of this was due to the crazy way the place has been painted.
I have used gray before to go from red to yellow as it seems to work in fewer steps.
1. There is a believe, that component isolation (taken to extreme by microservices) enables better productivity of the development department.
That is more features, more prototypes, more people can be moved in and out a given role. So that those 5 crusty programmers are not a bottleneck for the 'next great idea' that a Product manager or CIO reads up on.
2. There is a constant battle for the crown of "I am modern" (eg data science, micro services, big data ) That is going on in every development or technology organization. Where the closer you are in your 'vision' to google or Netflix, the more 'modern' you are.
The rest of the folks is 'legacy'. So you get budgets, you get to hire, you get to 'lead'. Micro-services is the enabler to help to win this battle (although, probably, for a short term).
---
I personally, do not believe that microservices bring anything new compared to previously used methods of run-time modularization :
Plugins
Web services
RPC
N-tier architectures
Perfect, I've seen this happen many times as well. I think you're generous on the 80% part. Usually they nail the first 50%, but they time they get to 80% its getting just as messy and some of the developers are planning another rewrite again.
That only works until you encounter something for which there was no rational reason in the first place.
That is to say - most people are acting rationally, but their context to an outsider may not appear rational. Maybe there's something to be said for a general relativity of rationality?
I found that a lot of the time developers start moving towards microservices when they find that a monolithic app becomes too difficult to work on. For example, multiple teams working on the same codebase will often have accidental code conflicts. Plus, scaling a monolithic app because one part of it is under load isn't always cost effective or logical. So, teams will start to break off components into microservices to make development easier and less painful. Naturally this has to be weighed up as microservices bring a different set of challenges, 'gotchas', etc, etc but in my experience the teams have done a proper job discussing the pros and cons.
It's also reflected in how we manage code at the micro-level: collecting related logic into a module until it becomes unwieldy and then separating out independent sub-functionality into their own modules and dependencies as they grow...
There is no right size for a class. Smaller is better, but the ideal is "right sizing". What's right? Well, that's tricky, but whatever doesn't hurt is pretty ok.
There's no right size for a service. Smaller is better, but...
Mixed tabs and spaces, sometimes one space indentation or no indentation at all, 1000+ line Java methods, meaningless variable names, no comments or documentation. SQL transactions aren’t used, the database is just put into a bad state and hopefully the user finishes what they’re doing so it doesn’t stay that way. That’s just the server. The UI is just as bad and based on Flash (but compiled to HTML5 now)
I've come to view microservices in the context of Conway's Law. If you have a team of developers working on a project who don't like to communicate or work with each other, do not understand version control, and all have different programming styles and technology choices, the only feasible architecture is one service per person.
I have no trouble believing that this is what's really behind Netflix's adoption of microservices. From what I've heard it's a sociopathogenic work culture, and if I worked there I would probably want to just disappear from everybody too.
Abstractly spoken, I don't care whether you call f(x) directly, via IPC, RPC or as a microservice. In my preferred programming languages there is not much of a difference anyway.
> You don't solve problems. You take the problems you have, and exchange them for a different set of problems. If you're doing your job, the new problems won't be as bad as the old problems. That's all you can really do.
"Here’s the thing, most of the time we do something that incurs technical debt, we know it then. It’d be nice if there’s a way for us to log the decisions we made, and the debt we incurred so we can factor it into planning and regular development work, instead of trying to pay it off when there’s no other alternative."
So how would this ledger work? Well, for starters it has to
track what we can’t do because of current technical debt.
It should also be updatable to note any complications to
subsequent work or things you can’t do yet because for old
design decisions. At this point, you’re tracking the
“principle” (the original design decision causing technical
debt) and interest (the future work that was impacted by
the debt).
This was an eye opener for me – thanks for sharing!
It's not a microservice if you have API dependencies. It's (probably) not a microservice if you access a global data store. A microservice should generally not have side effects. Microservices are supposed to be great not just because of the ease of deployment, but it's also supposed to make debugging easier. If you can't debug one (and only one) microservice at a time, then it's not really a microservice.
A lot of engineers think that just having a bunch of API endpoints written by different teams is a "microservice architecture" -- but they could't be more wrong.
I gotta ask, how is this realistic? A salient feature of most of the software I've worked on is that it has useful side effects.
I am not quite sure what you mean. A microservice with REST api that has POST method is not a microservice?
If two black boxes directly contact each other, then that also defeats the purpose. Microservices are not appealing unless talk via message queues. The whole point of microservices was to handle scale independently for independent functions.
Where do you suggest storing that state if it needs to be persistent? The definition of microservices should not assume anything about how long I need to track my data. If two of your microservices are touching the same database fields, then that's the implementor's mistake.
Whether it should consume other microservices is less clear, and gets into the choreography vs. orchestration issue; choreography provides lower coupling, but may be less scalable.
Can we extend that logic to classes or interfaces? Accessing data operations through a well-established API is generally seen as a good thing and is the exact cure for spaghetti...
Service APIs also entail load balancing and decoupled deployments, so they eliminate unclear architecture that arises at the app level when trying to tune the whole for individual components. Particularly when a shared component exist across multiple systems.
For a generalized microservices architecture: layering is a bit of a misnomer as everything is loosely in the same 'service' layer... I'd also point out that in N-tiered applications application services or domain services calling other services at the same layer is seen as the solely approved channel for re-use, not an anti-pattern.
This was one of the main ideas behind the original definition of OOP. The original notion of "object" was very similar to our current notion of "service":
https://www.youtube.com/watch?v=QjJaFG63Hlo
Objects received messages, including messages sent over the network. There was not supposed to be a clear distinction between local and remote services - by design. A lot of inter-computer stuff could be/was handled transparently.
Just like sometimes, in real-world C, “goto” is the right tool, even though arbitrary jumps of that kind are also a “recipe for spaghetti”.
They were having performance problems and "needed" to migrate to microservices. They developed 12 seperate applications, all in the same repo, deployed independently it's own JVM. Of course if you were using microservices, you needed docker as well, so they had also developed a giant docker container containing all 12 microservices which they deployed to a single host (all managed by supervisord). Of course since they had 12 different JVM applications, the services needed a host with at least 9GiB of RAM so they used a larger instance. Everything was provisioned manually by the way because there was no service discovery or container orchestration - just a docker container running on a host (an upgrade from running the production processes in a tmux instance). What they really had was a giant monolithic application with a complicated deployment process and an insane JVM overhead.
Moving to the larger instance likely solved the performance issues. In place they now had multiple over provisioned instances (for "HA"), and combined with other questionable decisions, were paying ~100k/year for a web backend that did no more than ~50 requests/minute at peak. But hey at least they were doing real devops like Netflix.
For me, I've become a bit more aware of cargo cult development. I can't say I'm completely immune to cargo cult driven development either (I once rewrote an entire Angular application in React because "Angular is dead") so it really opened my eyes how I could also implement "solutions" without truly understanding why they are useful.
What's gonna look better on a devs CV: 'spent a year maintaining a CRUD monolith app' vs 'spent a year breaking monolith into microservices, with shiny language X to boot'.
We can be a very fashion and buzzword driven industry sometimes.
EDIT: this perverse incentive goes all they way to the top, through to CTO level. Sometimes I wonder if businesses understand just how much money and effort is wasted on pointless rewrites that make life harder for everyone.
This doesn't stop at engineering; open offices, teaser/trick based interviewing, OKR's, ... Even GOOGLE doesn't do some of those things anymore, but the follower sheep still do.
well experimentally oracle solved that problem, somewhat. you could now use CDS and *.so files for some parts of your application. it probably does not eliminate every problem, but yeah it helps a bit at least. but well it would've been easier to just use apache felix or so to start all the applications on a OSGI container. this would've probably saved like 5-7 GiB of RAM.
Their "microservices" suffered from the same JVM overhead and to remedy this they are joining their functionalities together (initially they had 30-40).
9 times out of 10 it's because developers don't know how to properly design and index the underlying RDBMS. I've noticed there is a severe lack of knowledge of that for the average developer.
I've dealt with an even worse system, with a dozen separate applications, each in its own repo, then with various repos containing shared code. But the whole thing was really one interconnected system, such that a change to one component often required changes to the shared code, which required updates to all the other services.
It was a nightmare. At least your folks had the good sense to use a single repository.
What source control system?
Also, from the article:
> even though theoretically services can be deployed in isolation, you find that due to the inter-dependencies between services, you have to deploy sets of services as a group
This is the situation we are in, like you were.
Git in our case. And our direction was not to use submodules or anything like that to make life manageable. It was pretty unpleasant.
Azure Functions are technically a "serverless" product, but using them as y'all intended to is a textbook definition of a "microservice" :)
That's plainly wrong. I get the gist of what you are saying and I more or less agree with it but you expressed it poorly.
Having API dependencies is not an issue. As long as the microservices don't touch each others data and only communicate with each other through their API boundaries microservices can and should build on top of each other.
In fact that's one of the core promises of the open source microservices architecture we are building (https://github.com/1backend/1backend).
I think your bad experiences are due to microservice apps which are unnecessarily fragmented into a lot of services. Sometimes, even when you respect service boundaries that can be a problem - when you have to release a bunch of services to ship a feature that's a sign that you have a distributed monolith on your hands.
I like to think of services, even my services, as third party ones I can't touch. When I view them this way the urge to tailor them to the current feature I'm hacking on lessens and I identify the correct microservice the given modification belongs to easier.
I'm not sure what you think side effects are, but I'm using the standard computer science definition you can look up on Wikipedia. If you have a microservice that modifies, e.g. some hidden state, it's a disaster waiting to happen. Having multiple microservices that have database side-effects will almost always end up with a race condition somewhere. Have fun debugging that.
If no one then what's the point of that service's existence?
> In computer science, a function or expression is said to have a side effect if it modifies some state outside its scope or has an observable interaction with its calling functions or the outside world besides returning a value. For example, a particular function might modify a global variable or static variable, modify one of its arguments, raise an exception, write data to a display or file, read data, or call other side-effecting functions.
Note "write data to a display or file". I think we agree that writing to a database falls under this definition, hence using terms like "side effecting" when talking about microservices is misleading.
This management of API boundaries is likely handled for you by an app, though, so from a user perspective the story is still "open netflix, enter password, watch movie".
a bunch of API endpoints written by different teams is a "microservice architecture"
Most people have enough trouble getting three methods in the same file to use the same argument semantics. Every service is an adventure unto itself.
We have a couple services that use something in the vein of GraphQL but some of the fields are calculated from other fields. If you have the derived field but not the source field you get garbage output and they don’t see the problem with this
I just wish someone with "street cred" (or with a famous, recognizable name I could use for appeal to authority) could create a simple post saying "Hey, if you have a shared data store that all services depend on and are accessing directly, you are not doing microservices". "And you also don't have microservices if you have to update everything in one go as part of a "release"".
That way I could circulate it throughout the company and maybe get the point across. I've tried to argue unsuccessfully. After all, "we are doing K8s, so we have micro-services, each is a pod, duh!" No, you have a monolith, which happens to be running as multiple containers...
The best imagery I know for this picture is a two-headed ogre. It might have multiple heads, but one digestive system. Doesn't matter which head is doing the eating, ultimately you have the same shit. I've head semi famous people talk about this in conferences, but few articles.
So yes, you now have an authority that says doing that is bad.
A large purpose of service oriented architecture is encapsulation. If no other microservices can make requests to your microservice, then you really haven’t encapsulated much.
If and when you need to support mobile devices independently of your web UI, you can have a mobile gateway. Same idea. This gateway is optimized to know how to handle mobile traffic realities like smaller download sizes, etc.
No, you definitely don't want microservices making synchronous requests to other microservices and depending on them that way.
But it still may be necessary for your services to depend on each other, and that's where you can allow that communication through asynchronous eventually consistent communication. Actor communications, queue submission/consumption, caching, etc.
Even in such cases you might want to move bulk of processing to asynchronous queue based system but part of the logic might need to be executed synchronously (authorise credit card payment, you can process the payment asynchronously later, perhaps in bulk cron jobs like Apple Itunes does it but initial authorisation which decides whether purchase is successful must be synchronous).
I hate to burst your bubble, but you shouldn’t and can’t have truth working along side systems that access it. Data is messy and tends toward dishonesty. The only way to get clean truth for your organization is by thoughtfully applying rules, cleaning and filtering as you go. The more micro your architecture is, the more this is true. Because there is no way 20different teams are all going to have the same understanding of the business rules around what constitutes good, clean input data. Even if your company is very clear and well-documented about business and data rules, if you hand the same spec sheet to 20 different teams, you are going to get 20 variations on that spec.
The only way to get usable data that can be agreed upon by an entire company (or even business unit) is by separating your truth from your transactional data. That’s kind of the definitional of a data warehouse.
If you let your transactional systems access and update data directly in your warehouse, you are in for a universe of pain.
I strongly agree with this assessment :)
I have posted a bit more on this nearby, but Apache Kafka is well positioned as a compromise to support both of those truths: an orthogonal data warehouse full of sanitized purity and chatty apps writing crappy data to their hearts content.
By introducing a third system in between the data warehouse and transactional demands, Kafka decouples the communicating systems and introduces a clear separation of concerns for cross-system data communication (be they OLAP, or OLTP).
If your transactional data is crappy (mine is!), and you want your data warehouse pure (I do!), then Kafka can be a 'truthy' middle ground where compromises are made explicit and data digestion/transformation is explicitly mapped, and all clients can feast on data to their hearts content.
Your data warehouse can suck facts from Kafka (with ETL on either side of the operation, or even integrated into Kafka if you so desire), and you can keep Kafka channels loaded with micro-"Truth"s (current accounts, current employees, etc). That way apps get basically real-time simplified access to the data warehouse while your data warehouse gets a client streaming story that's wicked scalable. And no coupling in between...
It's a different approach than some mainstream solutions, but IMO hits a nice goldilocks zone between application and service communication and making data warehousing in parallel realistic and digestible. YMMV, naturally :)
It depends on what you want to debug. It is like unit test vs integration test. If you are finding a bug related to integration between multiple services, you definitely need to debug on multiple services.
Just out of curiosity, what alternatives are there to avoid API dependencies? Is it really possible to make non-trivial apps while avoiding internal dependencies?
At some level, is it really possible to have a truly decoupled system?
Very important how the boundaries a drawn. Generally, the more fragmented the micro-services the more API dependencies.
Also, look at the Bounded Context concept.
https://martinfowler.com/bliki/BoundedContext.html
And Conway's Law certainly plays a role.
http://www.melconway.com/Home/Conways_Law.html
> At some level, is it really possible to have a truly decoupled system?
You cannot avoid all the API dependencies, but you can reduced their number.
APIs calling other APIs is...well, I'm having a hard time understanding how that could be construed as fundamentally wrong.
Computers also don't care how code is deployed and different services can be bounded by classes, or namespaces, or assemblies, or packages, or processes, or completely separate APIs reached over the internet on the other side of the planet.
Microservices can perhaps be defined as more of a deployment model but even then it's 99% about the team and organization structure. As companies get larger, there is a trend towards smaller teams in charge of separate functionalities that create, deploy, and operate their own service. This can be effective in managing complexity and creating efficiency, although definitely not absolutely necessary.
All that being said, outside of the major software companies, I have seen exactly 0 uses of microservices where the benefits were worth the effort, if any benefits even appeared at all.
Microservices make it possible to simply deal with unstable environments. Cattle, not pets.
Many of the same reasons to use them apply to both, but with a finer granularity on what is being hosted where and how it is scaling with microservices. Scaling a service with multiple facets going through it gets tricky, hence a desire for a more appropriate modularity.
"Placing services in the cloud" kinda papers over why microservices and cloud-native apps hang together so tightly... Leveraging cloud-provider capabilities (message queues, streaming services, specialized DBs, etc), often introduces new kinds of scaling, new requirements, and new deployment needs at the component level. Particularly if you're working in multiple clouds or a hybrid environment or with teams in different organizations... Tech stacks might diverge at the component level, developer competencies diverge, maintenance routines and monitoring and the rest of it too.
A thin service wrapper in front of DynamoDB is gonna have a different scalability story than a DoItAll service on a VM that can also write to DynamoDB. Especially if the service is used by multiple apps, or customers in addition to apps. For a SaaS outfit that can be make or break.
All of these "cloud-provider capabilities" are just normal software that you can run on your own hardware. In one or two cases, the software was first exposed via a particular provider's platform, but similar, and very likely superior software that accomplishes the same goals, is now available for self-hosting (Dynamo -> Cassandra or Riak, for example). That's about as strong as the connection gets.
It doesn't follow that "microservices and cloud-native apps hang together" because the cloud provider charges you a lot of money to access their Redis server, when you could run your own Redis server.
There's no inherent "infinite scale" that magically shows up; proper architecture and design does that. "Microservices" again just goes back to being a rather badly defined description of a certain way of deployment. Every time I've seen these used (in smaller companies), there's no benefit over just having separate assemblies talking in the same process instead.
The madness is going away but the microservices are staying. There are some rationales for microservices that are conspicuously missing.
1. Fault isolation. Transcoder stuck in a crash loop? Upload service using too much RAM? With microservices, you don't even really have to figure out what's going on, you can often just roll back the affected component.
2. Data isolation. Only certain, privileged components can access certain types of data. Using a separate service for handling authentication is the classic example.
3. Better scheduling. A service made of microservices is easier to schedule using bin packing. Low priority components can be deprioritized by the scheduler very easily. This is important for services with large resource footprints.
The criticisms remind me of the problems with object-oriented programming. In some sense, the transition is similar: objects are self-contained code and data with references to other objects. The 90s saw an explosion of bad OO design and cargo cult architectures. It wasn't a problem with OO design itself. Eventually people figured out how to do it well. You don't have to make everything an object any more than you have to make everything a microservice.
it is not clear to me, why data isolation is your view, is exclusive to microservices.
I have build non trival RBAC+ABAC authorization platforms, using PDP and embedeabble PEP, and did not find that it was useful by micro services only. And I did not feel that it can only be called via 'micro service' pipeline.
In a way the Authorization is a separate service, yes, but it should be offering an embeddable PEP (policy enforcement point) that one can embed (link or call out-of-process if needed), from pretty much anywhere (monolith, or any runtime component).
Authorization decisions require very very low latency, as you are authorizing pretty much every data or function interaction.
In fact, for data interaction, authorization engines offer SQL-rewriting/filtering -- so that the actual 'enforcement' happens at the layer of database you are using, not even at the layer of the component that's accessing the data.
Authentication can be very easily centralized in a separate service, authorization is a completely different beast. Authentication often involves access to high-value data such as hashed passwords, authorization does not.
That's harder scheduling, not easier. With a monolith you just give it all the resources and threads will use resources as is necessary. After that it's a matter of load balancing appropriately.
The key was "with bin packing". If you "just give it all the resources" then you're not bin packing and you're barely scheduling. At that point, your scheduler is only capable of scheduling based on CPU and IO usage, and not (for example) based on RAM. That last one is tricky, because most runtime environments won't return memory to the operating system (e.g. free() won't munmap()), and we're currently in the middle of a RAM shortage. Your machines will almost always have a different shape from your processes, it's just something you have to live with.
A bin packing scheduler is not useful for all companies and all services. It depends on the size of your resource footprint, with very large services benefiting the most.
So, microservices give you better scheduling in the sense that you can use fewer machines to run the same set of services. However, this is not important to everyone.
This stuff is built into e.g. Kubernetes so it is actually quite easy. You just can't do it with monoliths.
I tend to have two layers of design, now. One - big picture, which treats services anonymously. Just black boxes that respond to input. The goal here is to build solution like kids are building stuff from building blocks.
Other layer depicts services, as separate beings. They treat all their clients anonymously. They have a contract to fulfill and whomever plays by the rules can be served all right. They should be treated as completely separate projects, have their own backlog, release strategies, etc.
Now, if you would have a product that utilize certain data, would you allow some anonymous guy from the internet tap to it directly? No need to answer, I guess.
Edit: typo
Input --> Stuff happens --> Output
Again, it's a simplification, although to be fair, I sometimes don't see how -- other than that I'm feeling that I'm ignoring context too much (e.g. underlying hardware or networks or REST API endpoints).
Microservices are just another way for us to do premature subsystem decomposition -- because we always think that we can build components with stable APIs that will be small, clean and reusable. It's even more fun to put that subsystem into a different process because, who doesn't like a little bit of extra latency in their processing? I jest, but it's not such a silly idea. By making sure everything is in another processes and using the most inefficient IPC system available (TCP/IP), you ensure that nobody is going to do stupid things similar to what people tend to do with threads. The multi-processing aspect appeals to people because it helps them break down the problem into isolated chunks and reason about them.
The key here, though, is to realise that you almost never need multi-processing. The design challenge is actually the same whether you isolate your processing in different processes or not. However, it's much easier to refactor your code when you haven't put road blocks in your path first. If you are doing that, then it is easy to extract the functionality into a separate process if you need to (or even a thread if you happen to work in an OS that thinks that thread processing should be more efficient than process processing).
In short, don't practice "I must protect myself from the stupid programmers" programming and instead concentrate on writing good code with your coworkers.
Now you can use this microservice anywhere and just change a few params in how you call it and you have avatars, thumbnails, etc.
I joined a company that had a large, old, and mature selection of services written in PHP. If I'd tried to rewrite that mature code in a different language I probably would have wasted a lot of time for little benefit. If I'd had to write new code in PHP just to access old code as libraries that would have been a problem too. But functionality was exposed over HTTP APIs that could be used from any language, any runtime.
Although I'm not sure whether or not a task queue architecture with separate server workers executing code passed over from a central monolithic app server is still considered a "microservice" architecture.
The operational part of microservices can end up being pretty important in these cases
For the posters who said "like a library," yeah that's exactly the idea, but consider if you have an operation that can be done by a library but that has very different scaling characteristics compared to the rest of your system. Eg. you have one highly compute intensive operation while the rest of your system is IO bound. If you can split these apart it's easier to deal with scaling.
There are definitely special cases, but overall, after 33 years building software, domain driven design, PaaS, micro-services, and continuous delivery is the most productive paradigm I have ever seen.
Edit: another one, is that if you keep the microservices actually small and well described by an API, you can easily, quickly and safely heavily refactor/rewrite old services.
Boundaries are by domain, and yes that's not a simple thing to define. Sometimes, domains have varying interfaces, which makes building micro-services more complex, especially when trying to adhere to REST/Swagger standards (something I'm not overly find of).
But keeping things as simple as possible is really the best approach.
All micro-services should be small. When I see someone say "big", then I'm guessing there are a lot of ad-hoc actions...those need to be broken down into their proper domain or relegated to a query service.
Using authentication, users of an API can have "claims" that will help a micro-service delineate access and provide a way to design for varying interfaces.
This still leaves the Swagger standards in direct opposition to building a set of variant end points since it _requires_ that end points be singular (you can't have a GET api/foo/{id} and a GET api/bar/{id} on the same API without a lot of fudging. This is a distraction from building enterprise-level API's and leans far too much toward single-purpose API's.
There's just so many topics that all come together here: stateless programming, pure FP, NetOps, DevOps, and so on. It feels like one of those cross-discipline discussions where it's either really simple -- or really complex. In fact the core skill here is managing complexity across multiple domains up and down the entire stack. It all depends on the fine details and which choices you make.
I just finished a really good book which may seem unrelated to the current topic but actually is spot on. It's "Domain Modeling Made Functional" It uses F#, but the principles involved apply no matter which language you're using.
https://pragprog.com/book/swdddf/domain-modeling-made-functi...
It's weird you mention that, I was just chatting to a colleague the other day on this topic, and I rooted out this old article which I loved:
www.slideshare.net/ScottWlaschin/ddd-with-fsharptypesystemlondonndc2013
I was lucky enough to work on a big F# project a while ago and really enjoyed the experience, it was the first time I'd done any functional programming in a professional context and I miss it now that I'm doing more JavaScript and Node.js!
Thanks for the kind words on the article, much appreciated!
No problem. There was a ton of good stuff in there! I saved it to refer back to it later. :)
As a tech coach, I teach good programming skills, which mostly ends up being TDD and other good coding skills for OOP folks. But I've become a huge pure FP fan over the past decade, learning it all on my own just by struggling through it.
So as a coach, I'm seeing more and more of these microservice train wrecks. I'm also seeing a ton of people who don't understand microservices come online and bitch about how they don't work.
Wlaschin's book goes into building a pure FP system from the top-down -- something I never considered doing (I've never coached or worked in a large pure FP shop). Of course, if you build it out that way, it really doesn't matter how you splice up the code or where it goes. You can do monolith, serverless, microservices, whatever.
I liked the process described in the book a lot. It describes to me how you can have 50 people and 100 microservices and make it all work. (Although everything you point out is still an issue, many of the pure FP techniques mitigate them.) Feels a lot like BDUF, though, which kinda bugs me.
I sat down with Uncle Bob last month and spend a week showing him F#. TDD didn't seem to work that well, but maybe I missed it. There's just nothing to test in simple transforms, and you want to keep using simple transforms as much as you can. I think we need to evolve a TDD-like process for growing systems in pure FP from the ground-up. I'll probably cogitate on this for a few years and end up writing something. If you know of any good resources, please send them my way!
I kind of also feel that TDD has a kind of cult like following, especially with the Rails crowd
Broadly speaking, microservices make small, limited changes/update less complex, and large, sweeping changes/updates more complex.
This is why generalizations like "larger, established organizations [which make mostly relative small changes] should lean more to microservices than smaller, younger organizations [which make mostly relatively large changes]" hold true.
1. Setting up a "Microservices" architecture itself is a convoluted process. If you're not a Netflix or Amazon that will run hundreds of microservices, the up-front cost and time is NOT at all worth it. I would rather just run an app on Digitalocean.
2. IF I decided to bypass step 1 and just use existing vendors like AWS, Google, Microsoft, etc., first I don't feel good about it because I know it's in each vendor's best interest to implement lockin, which conflicts with my own interest.
3. Lastly, none of the existing cloud function vendors have good user experience. AWS Lambda, Google cloud functions, etc. all require you to go through all the authentication related stuff before running a simple function, not to mention all the constraints that come with "function based paradigm". Again, definitely not worth it unless you're trying to run hundreds of these functions.
I think part 3 is critical, because I was willing to ignore part 1 and 2, as long as I could get my function up and running really easily. But none of the vendors make it easy. Sure, there are frameworks that let you do that like Apex and Serverless, but those also require setup. I would rather just run a DigitalOcean server for $5 which by the way can run multiple of those services as a regular server, without me having to spend time dealing with the complexities of function servers.
I thought about how this could be improved. Sure there can be some "Heroku for functions" SaaS, but nobody is excited about building SaaS startups nowadays because they know they can't compete with large vendors in the very long run. (Unless you're comfortable with just building a lifestyle business, which is totally fine, but I personally won't rely on a lifestyle business SaaS)
The only way this can be improved is if each root vendors like Amazon, MS, and Google actually implemented better UI, but none of them are really focused on this since the reason they're doing this business in the first place is not for consumers but to make sure they have leverage in this space. (If AWS dominated 90%+ of this market, the rest of the companies will be in a great risk in the long run)
Independent development - just stick to your own part of the app.
Reusability - write a library
Isolated deployments and deployment velocity - I suppose not isolated but there’s no reason you can't achieve great velocity with a monolith.
A less often cited advantage that I do think has a lot of merrit is the ability to choose different languages and tools for different problem domains.
I love (without quotes) microservices for their isolation principle, people can kill off/rewrite parts of the system without affecting other parts, written possibly in a whole different language etc., but lets not abuse it. If you put every tiny function behind an API, what you'll get is a slow and unmaintainable mess.
In this go around I think the value of discreet, well factored services clearly have merit but it's really a question of just how often you truly have something that's a good candidate for this pattern. From what I've seen in some places it's used as a reason to rewrite systems and not worry about doing a good job creating well abstracted software because the integrity of the overall system is some other team's problem.
This article is really well written and does a great job shedding light on the truth. Thank you for sharing.
- scaling based on very disparate resource requirements across our api
- security isolation of critical backend infrastructure
- language requirements and dependency management
- accommodating different skills and groups of skills across our organization
When I first started with Java one of the coolest things was that I could embed anything. I could embed Elasticsearch in my web service. Wow! Forget services calling each other! I’ll prototype real quick with everything in one JVM!
But that proved impossible! :( It turned out that until Java 9, the JVM has a single namespace for all loaded classes. For me this was the greatest driving force for building out smaller services. You had to be very careful about dependencies and couldn’t just include Elasticsearch—or even much of anything—in your web service even if you wanted to. You’d be in immediate unresolvable dependency hell. I can imagine the insane artifacts people produce when they try to build monoliths on the JVM. Even with JavaScript now you have one huge flat dependency namespace. Good luck building a monolith.
I can only conclude that the all the people on this thread who are painting “monoliths” as some easy alternative developers are ignoring due to some inexplicable desire to make things complicated have no idea what they’re talking about.
https://martinfowler.com/bliki/MonolithFirst.html
You start with a Monolith and break it out as needed. (i.e. When you find out that is not a good idea to embed Elasticsearch )
You avoid premature boundaries that can become a significant constraint.
Forget embedding Elasticsearch for the purpose of running it inside your monlith; just the transport layer drivers (supposing you're not using drivers that work over HTTP) basically add all of Elasticsearch onto your classpath. Good luck building your monolith after that. And that's true for so many things you'd want to use. If you want to build a monolith you basically can't have any dependencies. Or be very experienced in dependency management.
This is why I have a microservice that fronts all my Elasticsearch queries. Its artifact has the Elasticsearch drivers, all other microservices that need access data from Elasticsearch talk to this service over gRPC. Any time I want to upgrade Elasticsearch or change something about a query, I only need to do it in one spot. It's great.
1. 'Death' is a bit too extreme. I think everybody is excited at first and tries to find an excuse to use microservices. We're assisting to a decline in that initial push, that's all.
2. I think the point about transactions is fair, as well as the expertise and team concerns, but the rest are mostly "it's too hard and complex". It'll get better with time. I think that being a bit uncomfortable as a dev is not too bad, that's what we're here for (assuming there's a real need of course).
1. I think here I was going for 'death' more in terms of the end of the hype, rather than the approach! 2. Agreed. As people get more familiar with the patterns, tools and code and so on it does get easier. The point is more that it can be a hell of a journey :)
I see smaller teams heaping in tons of complexity for no real gain; and actual measurable cost.
> Being both a developer and an operator is already tough (but critical to build good software)
> Yes, with effective automation, monitoring, orchestration and so on, this is all possible
This argues for having a separate ops team to handle the complexity centrally (e.g. operating a kubernetes cluster, providing standard building blocks), so developers can concentrate on their services.
Then you have the platform teams that support them by managing the platforms they use, the monitoring solutions etc. and work as much as possible so the devops teams can be self service.
I have no experience with it though but I feel that having all knowledge in all devops teams does not scale to any sufficiently complicated environment and the idea of the dev team not being responsible for deploying to production sucks.
However, I don't actually think a central team is always necessarily the best way to handle the cluster, it depends on the setup in the org and how many people are using it. In some cases it might be best to have the team who use it most heavily handle it, and share their best developers with other teams on rotation. But there's lots of options here. I agree the points are a bit unclear!
https://www.youtube.com/watch?v=x7cQ3mrcKaY
It addresses this and is pretty great in my opinion. Of course one does not have to agree with it but it is not the same as the mess back then and usually the separation of concerns is more about separations of technology than concerns.
As an an example:
Let us say we have a shopping basket up in the top right corner of our web page. For me there is a big difference between the logic of calculating to the total sum of the parts we have in it or collapsing/expanding it. One is "business logic" and one is "presentation logic" and they are not the same.
And I also bet that if for example HTML or CSS had native collapse/expand then people would consider that presentation as well and not to mention all the logic you usually have (loops, conditions) in a normal template language.
It resonates on many of the pain points of microservices. I also nearly broke out laughing at his definition of "microservice madness":
> Netflix are great at devops. Netfix do microservices. Therefore: If I do microservices, I am great at devops.
Because it is so hilariously accurate it's almost painful.
I do want to point out something the author implies, which is that there are benefits to microservices as a pattern...and as a pattern it is likely here to stay. It's an advanced pattern that comes with tradeoffs and complexity increases on the ops side. In the best case you're trading developer complexity for operational complexity and perhaps also getting better reliability (but this is not a guarantee).
Additionally, projects like Kubernetes, Istio, and Envoy are all tools aimed at making certain operational complexities of microservices easier...so the operational trade offs are likely to change dramatically this year.
But in the end we can all still hope that madness dies in 2018 though.
For example, you have a centralized security service. It handles the things related to accounts, profiles and group membership. You have a recipe service. It handles things like finding recipes, adding them to "books", etc. The recipes need to be guarded. They are shown only to members of certain groups.
You could have the recipe service call the security service each time to get the caller's groups. Then compare those groups to the allowed groups. If that user service goes down, you're borked.
If you use events instead, you'd keep a copy of the profile and its groups in the recipes. Every time that changes, it gets an event with the details. Now they've decoupled by sharing data async. It is not a perfect system. It can be possible that the recipes service doesn't update. Now a user that should get the data can't.
The trade off with events is that you can upgrade and redeploy services more easily. If you find a bug in the user profile service, bring it down, update and restart. No other service goes down with it.
All of this makes sense but also seems unavoidable to some degree. Seems like a set of tradeoffs you make by going microservies that you should be weary of.
Having services fully state-decoupled via unified log is interesting. I’ve considered this but it seemed a bit complicated in terms of then being able to scale the services that need, say, local copies of user profiles.
Here's two examples. Provided you don't get much churn in key profile data, you might be able to use JWT to store group membership for example. All services can read the the token. The token provides the groups necessary for the access operation.
Another example is only copying parts of the data. My current project has profiles and memberships. Interestingly the app side code doesn't actually use that information directly. A copy of group membership is held in the DB. When the user executes any operation, the queries themselves check for rights. When a use wants to read a list of recipes, part of the query is "and has read permission". The same is true of updates. The system queries for the resource to update. Only those that the user has an explicit right to modify are found.
That might mean that you still take that cost willingly but engineer in the extra tooling to make things easier to manage – i.e. simplifying tracing load or errors across service boundaries back to the source – but it might also be a cue for you raise to reconsider whether the service divisions are in the right place or whether all of the services are appropriately sized. If you find yourself needed distributed transactions, retries, etc. that’s often a good time to pause and reconsider.
Thank you that makes sense.
If I have one api that is low throughput and one that is high, say requires 2 and 20 nodes respectively, then you need 22 nodes whether they are two independent microservices or a monolith. I'd think the monolith would actually be easier to manage as you don't have to worry about how to divvy up the resources. All 22 nodes run the same code. Sure you could do the same with a k8s cluster autoscaling (I assume), but still, I don't see how this makes anything strictly easier than a monolith scaling. If anything it seems like one more thing to worry about.
But I've heard the argument multiple times, so wonder if I'm missing something.
The 20+2 distinction isn't clear because each part of the code is causing action-at-distance on the others. Failures become a lot harder to isolate. That's what people mean by scaling is hard with a monolith.
That said it allows you to tailor your code to its specific need. One of the services needs a certain database, or queuing or other connectivity considerations while the other doesn't or has different needs. Having them bundled prevents you from splitting things out. You don't have a limited and specific design.
Chess API is a daily cycle between 10-1,000 TPS and is CPU intensive. Haiku is uaually 1-10 TPS apart from Fridays (when everyone's device gets a new one) and holidays when it spikes to 100,000 TPS and is IO intensive.
Scaling a single service with both these API endpoints being called for different pattens like the above is a pain. Splitting them allows for choosing different host types (e.g. More CPU or Memory / SSD etc.) and makes scaling (especially planned / dynamic scaling) easier.
For example if you had your chess AI engine running in the same monolith as your web server, it could slow down your response time to the point of timeout. But if they were separate services, your web server could stay snappy and give a meaningful response to the problem. "our ai service is overloaded right now, but here is a nice haiku while you wait."
Though still, I'd think of that as a fairly advanced use case. Not something small projects should have to think about.
You may find cases where decoupling a service is a good idea. That doesn't justify decoupling everything by default. The more you decouple the more rigid becomes the whole system.
- you use in-memory cache, so with monolith each instance will need X+Y amount of ram, where X is needed for api A and Y is needed for api B.
- say api A serves client http requests, and api B does some asynchronous resource intensive computations. When a large workload lands on api B, api A will suffer until auto-scaling kicks in. Even after auto-scaling kicks in, individual nodes could be overloaded which is fine for api B but unacceptable for api A.
- in a scenario where api A and B both serve client traffic, maybe you want to switch api A load balancing from round-robin to sticky, now you have to worry about the impact on api B as well.
The possible scenarios are endless, and you always have to think about both api.
What? Isn't a serverless model necessarily a microservices solution?
Microservices get to be necessary for large dev teams, but probably a lot later than most teams think.
You've gotta tip your hat to Sun, despite the OO crap and XML-itis the underlying ideas were - and are - sane.
Now, just as ejb was rightfully considered massive overkill for all but the most large-scale applications, just as simple servlet based (later on controller, service, persistence designs) we often more than enough to get the job done, same applies to uServices.
When every department wants the easiest job with max outcome and the boss decides to split the cake equally, then an easy job X can be cut into N services which are usually named "micro", resulting in a huge project of complexity (X/N)^N for each team.
> A new version of the subscriptions service may store data in the subscriptions database in a different shape. If you are running both services in parallel, you are running the system with two schemas at once.
Microservices should manage their own separate data stores and communicate with others through a well-defined API. Only then services can evolve independently, and each team is free to change the internals (including schema migrations) without coordinating with everybody else.
Multiple services sharing the same database is the perfect example of the "monolith in disguise" anti-pattern mentioned in the article, with all of the costs of microservices but few benefits.
Thanks for the point! In this case I meant more the situation that the same service (single service, single DB) might be running with more than one version concurrently (during a rolling deployment, or a canary deployment etc) which can lead to issues. The other case is that if services depend on an old contract there could be times where teams might run multiple versions of a service to allow different APIs to be used, rather than a single version of the service which exposes all current compatible APIs. Although to be honest, this is an issue with any service.
A lot of technologies get a lot of hype over the years. But often the backlash is no less ignorant or fashion driven.
Is there a silent majority of us that look at these hype trends, consider them, and make a level-headed decision to see if they fit our problem? I never got into micro-services, because I worked on small teams and it seemed like over-engineering. But it's an idea that I tucked away in the back of my head, that I'd still use if the situation calls for it, HN backlash be damned. The same goes for nosql databases or dynamic scripting languages or anything else that's now irrationally hated.
Choosing the right tool for the job is difficult, there are many variables at play. There's a lot of value to people sharing their perspectives/experience about these issues. At the same time, I think the overall discussion shouldn't be so dichotomous.
From the perspective of a high-level architect it makes delegating certain types of responsibility a bit easier and potentially reduces the need for communication between teams while maintaining centralized control of the overall system.
However, it always seems to come with such a high overhead that IMHO it's almost never worth doing unless there really isn't another option.
So for example one developer can create the backend and one developer can create the frontend. The codebases can be completely independent. One could use PHP+Laravel and the other one PHP+Symfony for example.
Frontend and backend would live on their own servers. And simply having the IP, login and PW of the shared DB set in their project.
What do you guys think about such an approach?
Issue ends up being how to keep applications from ruining assumptions made in other services. There’s no single code base which you can walk through and see possible changes.
At that point this isn’t making things easier to understand or maintain so it’s not the best approach.
If you're talking about the separate microservices using the same tables in the database, that's probably an even worse idea. Either your services are way too tightly coupled, or shouldn't have been split into separate services in the first place.
This is already a smell. Usually, microservices don't need to access global state.
"We think we can drop this column, someone figure out which of our eight apps using this DB might be using it still"
I much prefer putting a single service layer in front of the DB that speaks thrift or protobuf and letting all clients interface with that instead. Evolving thrift services is fairly straightforward and allows you to make changes without needing every app the keep up.
The answer will depend on the data in question, of course; maybe it is fine to serve stale data for a while, maybe you need to write to one DB, read from another, and combine in-process, etc., until the change fully propagates. But the impact needs to be localized to whatever extent is possible.
If you have several applications accessing the database directly, it makes the database everyone's problem, instead of just the one thing's problem. Then everyone has to know about the downtime and come up with their own strategy to mitigate. They can't say "Well we'll just trust what we get from Service A", because they don't actually get info from service A; they get info from service A's underlying datastore.
Worse, in most cases like this, there will just be one global database for everything, so schema changes, database restarts, etc., necessary for one thing can have negative effects, both direct and indirect, across the entire ecosystem. If Bob's Service decides it needs to do a massive reindexing and Alice's Service is on the same DB, even if they're using completely independent tables, etc., the performance hit is going to affect both. If Bob changes his schema and Alice reads or writes directly to those tables (e.g., Alice's service updates a column in records originally inserted by Bob's service), now Alice has to know about the change, plan for it, and coordinate her deployment in sync with Bob, etc.
That kind of thing is what people mean when they say "distributed monolith". There is no real "private" and "public" space where one service provider could reasonably offer a stable API but change things as necessary on the back-end. Nothing is really independent. All you've done is make a monolith that is much harder to coordinate, manage, debug, and understand.
Over time they all learned to reach into eachother’s databases. The truth is we had ONE database arbitrarily divided into three schemas, each with different traditions.
As load increased it became a nightmare and a literal single point of failure. If one app misbehaved or took a load spike all the rest would slow/fall down. Even though huge chunks of the applications had nothing to do with each other they couldn’t be scaled independently.
We were working very hard, slowly, to detangle it without blowing everything up.
No application should ever have direct access to another application’s database. It’s going to go wrong. The temptation is too great. And by the time you realize it the technical debt it has caused may be MASSIVE.
In the end, it's mostly about enforcing contracts and making devops simpler.
Let's take an address for an example. Your contact database might have "id", "name", "addr_line_1", "addr_line_2, "addr_line_3", "city", "state", "zip". Your API v1 lets you query any combination of these fields and return a set of fields.
/api/v1/contacts?zip=10018&fields=name
[{"name": "Jessica Jones"}, {"name": "Matt Murdock"} ]
/api/v1/contacts?name=Matt%20Murdock&fields=zip returns something like:
[{"zip": 10018}]
Later, you change your database to split name into fname and lname. You update your code and API to reflect this. In calls to /v1/ of the API, the field "name" is concatenated by your code to combine the database columns of fname and lname. In /v1.1/ of your code, you may or may not keep the "name" field as a convenience , but you do provide the ability to search on fname and/or lname fields.
Basically, for any change to the underlying database, your API maintains the same interface to the data, however you might also publish a newer version of the API. In fact, your code that handles the API might be entirely different. For instance, /api/v1 might be handled by a python flask framework, while /api/v2 is handled by node. You can run multiple versions of the API at one time, supporting multiple iterations of clients. Obviously to reduce the amount of maintenance efforts, you will deprecate some versions and provide deadlines for them to be disabled. You can run all sorts of reports on the usage of each API endpoint and see what calls and response formats are still in use. This can open up the ability to do an outreach to those developing a client and make them aware of necessary changes.
I heard a few years ago that some government jobs apparently actually still require stored procs for security reasons. The ACL is controlled there.
Yeah, agree. This is exactly how big companies end up doing, very interesting approach!
It's inevitable that someone has to invent another abstraction, but it does pay the bill. One thing you can do with this single layer is to control the flood gate.
I remember hearing this from a talk given by someone working at Instagram: as the team grew larger, cooperating on DB changes became problematic. So Instagram picked up Facebook's Tao.
If the backend dev needs to change a field in the database, or add a new one, then can might affect the front end dev.
Also - simple things like validation rules - i.e. what can the front end dev allow users to store into the DB vs what can the back end dev use/need.
This might be fine, and maybe it could even be a good choice in your situation, but I would probably avoid the added complexity.
If you're sharing the database because sometimes you want to access a table from the frontend and sometimes you want to access that same table from your backend layer, you're probably setting yourself up for pain later.
It's hard enough to coordinate this kind of maintenance when there is only one OLTP-style user of the database. If you get a lot of interdependent units, where app A needs to read table B and app C needs to write to table D, it's nigh impossible to do it without global downtime.
"Microservices" require a large amount of control and discipline to implement properly. In almost all cases, a straight-up monolith ends up being much saner. "Microservices" are often seen as a license to run hog wild and disregard everything outside of one's immediate area of concern / team. This is convenient at the time because of Conway's Law, but it is terrible for long-term maintenance, overall consistency, and employee sanity.
> While monolithic applications prefer a single logical database for persistant data, enterprises often prefer a single database across a range of applications... Microservices prefer letting each service manage its own database, either different instances of the same database technology, or entirely different database systems https://martinfowler.com/articles/microservices.html
Not to say that pattern can't be successfully implemented, just that it wouldn't be considered microservices. It sounds like you're describing a three-tier architecture: https://en.wikipedia.org/wiki/Multitier_architecture#Three-t...
It's not a bad system - it worked for a technology generation, from around 1997-2012 - but it's somewhat limited in the problem domains it can solve effectively. Anything real-time or with high change volume becomes problematic, because each service needs to poll the DB for work to do. The DB can quickly become a scaling bottleneck. It's not as well-suited to thick clients, because you need an app server in front of the DB anyway to check & validate requests so the entire world doesn't get access to all your data.
On the plus side, state coherency becomes much easier, because all state is in the DB and you can use transactions to update it atomically. I also disagree with the posters who say that updates & versioning are a nightmare: they are, but updates are a nightmare in any distributed system, and sticking an app server in front of the DB just makes it easier to know when you've made a breaking change, it doesn't make the change itself easier. I've worked on large (= Google) protobuf-based SOAs before, and changing anything that touches backend protocols or storage is difficult regardless of which architecture you use.
I'm a big fan of the "solve the problem first, scale the architecture later" approach. For your first version, just store everything in hashtables/lists in RAM, in a single process, and serve out RPCs to client code (or run a webserver) as necessary. At this point, you don't have a useful product anyway, so it doesn't matter if it goes down and loses all data. Once you have something that's useful, work on moving state out to external systems: at this point, you have a pretty good idea what the schema should be, so you can save on a lot of migrations. Split into separate services when the computational resources exceed the ability of a single process to service them; before then, just split it up into libraries.
The microservice approach is to have each service have its own database (MySQL) or schema (PostgreSQL).
Another solution is the use of a modular architecture, where separate modules are each responsible for their database tables' schema. Tables are not shared across modules; accessing data from a table requires calling its module's API.
Each module can be developed independently, and combined into one large service or several smaller services. It's helpful to be able to separate modules into their own service for load balancing and optimization, while having all modules in the same service eases administration of the system.
From previous experience, you start by lumping all modules together, then use monitoring software (i.e. ELK stack, collectd/Grafana) you decide where to split into services. Because the reality is you'll not really know where to split until you are running in production.
This is the approach of Django for example and works quite well for large projects.
Latency Numbers Every Programmer Should Know https://gist.github.com/jboner/2841832
However I would argue Microservices has been done before the idea is not new. Microservices is a realization of the same principle as that of UNIX/Linux. This is called the UNIX philosophy, Write one program that do one thing well. Make the output of one program the input of the other one.
Microservices are not a new idea, its the reimplementation of the UNIX philosophy for the web.
The UNIX philosophy https://en.wikipedia.org/wiki/Unix_philosophy
"Make each program do one thing well. To do a new job, build afresh rather than complicate old programs by adding new "features"." compare with Microservice definition by wikipedia "The services are small - fine-grained to perform a single function."
Improving reliaility with recursive reboots, Microservices on Kubernetes are at least implementing micro reboots in case of component failure. https://radlab.cs.berkeley.edu/people/fox/static/pubs/pdf/j0...
Like most tech Micro services probably follow the Hype cycle https://en.wikipedia.org/wiki/Hype_cycle
eheh, on an article about micro service madness
This is the part I keep getting hung up on. Even with perfect boundaries, there always seems to be a cross-cutting feature that would require touching all of the services.
When trying to implement as multiple microservices something that should actually be a single service—i.e., the ms's are not useful as independent units—answering a single API request is an amazing mess of distributed calls all over the place and unnecessary serialization/deserialization of queries.
- easier to manage (smaller team) - easier to hire (we can hire good people with different skillset) - easier to scale - and so on...
Same issues right? Complexity === pain and we can't seem to grasp this as developers. Are we the most self-flagellating people on the planet?
Can any of the old timers here name any predecessors to CORBA?
What might work is hashing the text and outbound link content submitted pages of, and building something like a similarity index of text, metadata and a graph of links, but that would probably still be fragile, and definitely be too much effort for a site with as little traffic as this.
https://news.ycombinator.com/item?id=16149039
It is strange how no one was interested when previously submitted and sudden it attracts a lot of interest.
Social is fickle that way, and since most social algorithms strongly consider post recency and other time-sensitive factors in their ranking, duplicates should be allowed within a reasonable time frame, because you never know when the critical path will get hit.