Go best practices, six years in
peter.bourgon.org
peter.bourgon.org
1. Holy crap, this is like coding in early Java days, what the heck were the language designers smoking?! They just ignored everything! Where's my testing framework! DI?! Build system, dependency management?! WTF.
2. Holy crap, this is like coding in the early Java days! This is awesome! I can understand all golang code I read! Everything is so simple and easy. I finally get "less is more", and "worse is better"!
3. (Many months later) Oh god, I'm getting so sick of writing this test assertion in 4 lines over and over, and writing 100s of lines of mock structs. My tests are 5% substance and 95% setup. Okay let's write a junit/mockito assertion library. Oh crap, I'm having to manually wire everything everywhere and it's such a pain. Let's write a DI library. Ugh my project is getting too big and `go get` just doesn't cut it - time to use a dependency management library. Ugh, makefiles only go so far, time to write a build tool. Ugh code generation and metacoding is nonexistent, let's write our own code generation tool so we don't have to hand build 100s of types. ETC.
4. (Distant future) As golang's stubborn designers finally accept some flaws in their original thinking, they add features to make the language look a lot like another widely used language at the Googplex. Mission accomplished?
P.S. This is somewhat tongue in cheek - I do enjoy using golang day to day. It is a refreshing change :).
Go still keeps it lean, and is great.
The fact it does not have hipster dev approved status is also an added bonus. The minute we see a bloated testing suite with yet another DSL, for Go, we are in trouble.
What are you talking about ? the hype is strong with Go. So strong devs are persuaded they need to use Go at all cost then complain Go has a garbage collector ( just go go-nuts mailing list).
So strong there are countless articles on the net about "How we moved from X to Go..." just like in 2007/8 with Rails.
> The minute we see a bloated testing suite with yet another DSL, for Go, we are in trouble.
GoConvey and co ...
Uncanny, isn't it?
Plus GoConvey wisely separated the UI visualizer from the BDD, we use the former and not the latter.
Writing about Go is a great way to hit the front page of HN. I once saw 5 articles about Go on the HN front page at the same time!
If you're looking for C-like though, you are probably not in any modern-featured language designer's aim.
It was implied by the context of "ML" languages. That was my intention at least; I thought ML languages were characteristically safe.
Regarding "C-like", I mostly mean syntax. I'm not too familiar with the ML family, but many FP languages have bizarre syntax which amplifies the difficulty of learning new concepts IMO.
Because you are. You likely wrote widly unsafe things which are perfectly legal in C++. Rust is really just enforcing RAII which C++14 already has, and you've likely avoided.
Once IDEs start coming around it should be quite competitive. I'll admit to thinking the same thing: I'll use Rust for the absolute critical parts, then F# for the rest. But more and more parts I'm writing are easy enough to do in Rust, and I get the perf as a bonus.
Yes go also claims to be C replacement, but probably the only similarity is its simplicity, but unlike C it is not as expressive.
Rust was aiming at innovating and advancing the PL space with meaning. I can't say looking back the time I invested with Go was well-spent.
Rust is probably worth the effort if you have the need for what it offers. It just requires more out of you than Go does.
Huh? In my experience Go is the most hipster dev language around at the moment.
So far, looking like a solid decision.
https://www.techempower.com/benchmarks/#section=data-r12&hw=...
https://www.techempower.com/benchmarks/#section=data-r12&hw=...
In both Phoenix has very high error rates, and in the first it seems really slow. Here is their Phoenix test app:
https://github.com/TechEmpower/FrameworkBenchmarks/tree/mast...
So what is going on there? Is it less of a perf win than I've heard? Is there something bad with their code?
Edit: Here.
1. Wow, this program runs on any platform!
2. Wow, no need to free memory!
3. Wow, threads and locks are so easy to do!
Then many years later
4. Who really cares about cross-platform code if all I do is on Linux?
5. Why does this program require 4GB of ram?
6. Must I really download and install the JVM all the time, and what is it good for anyway?
Go:
1. Wow, I can write stuff that previously could only be done in C/C++, and I can do it almost as easily as writing Python or Ruby.
2. Wow, I don't need anything installed for my program to run, it just runs!
The last example is nsq[1]: Download, unzip and run the binaries .. aahh :)
Obviously this can be true for non-golang programs as well, but I can't think of any right now.
Most developers write their code on Windows and MacOS and then deploy on Linux. I'd say this "Write once run anywhere" thing was and still is a pretty big deal.
> 5. Why does this program require 4GB of ram?
Oh no! I need to buy a $5 piece of hardware to run this Java code? What kind of nonsense is that?
> 6. Must I really download and install the JVM all the time, and what is it good for anyway?
Once or twice a year, if you really want to. You update your browser much more often.
.. and then someone gets the idea that your application should now run natively on Android phones, since they all run Java anyway, right?
What's your point?
There are hundreds of millions of phones running Java today, what does that tell you?
It's not if you meet one of these typical "don't do any premature optimisations (even in the design phase of my data structures), because some important CS person said so"-designs. There's all too many programmers who think they should never have to care about hardware anymore.
Funny. That's Microsoft line of thought with Vista.
4 GB per program absolutely destroys VM consolidation. I love the look on managers' faces when they ask for a 1 GB VM and I ask them, "Is this for a Java program?" :)
On other hand, on truly constrained embedded systems where real time is essential, no GC-based language has any business, no matter how GC is good. Even C++ is sometimes avoided.
http://www.pr.com/press-release/136232
Or do you prefer Aegis battleship Weapons System ?
http://dl.acm.org/citation.cfm?id=2402699
These are my favorite examples for Java being used in life critical situations.
> The applications use a combination of Thales proprietary middleware written in C combined with Java code enabled by the Java™ Native Interface (JNI).
> AONIX has additionally delivered professional services to help PERC Ultra users at Thales optimize their applications and improve execution performance including, a customer-specific training course handled the needs of coding in Java™ with hard real time constraints.
Seems like with helping of C and Consulting on 'How to do Java right' they made it work.
> End-to-end distributed thread timing constraints measured from stimulus to response are typically under 100 ms.
Since it is slightly faster than typical (per char) typing speed on keyboard. It appears nice but terribly impressive real time Java use case.
Not Java, not even close. JavaCard is an extremely stripped-down version of Java. I've used it and it feels like C.
From https://en.wikipedia.org/wiki/Java_Card#Java_Card_vs._Java:
> However, many Java language features are not supported by Java Card (in particular types char, double, float and long; the transient qualifier; enums; arrays of more than one dimension; finalization; object cloning; threads). Further, some common features of Java are not provided at runtime by many actual smart cards (in particular type int, which is the default type of a Java expression; and garbage collection of objects).
[EDIT] But I am not arguing with the overarching argument that Java proper can run efficiently on very constrained devices. It all depends on the implementation.
I really hope you actually mean 7+ times a year. https://en.wikipedia.org/wiki/Java_version_history#Java_8_up... - most versions contained security updates.
What I'm saying is - you should care 7+ times a year. Doesn't matter if you only update twice.
I don't think concurrent programming was ever particularly easy in Java. If you're talking about `synchronized` methods, well, they are of limited usefulness (to put it mildly) when you need to lock objects in an interleaved fashion: "lock A, lock B, unlock A, lock C, unlock B, lock D, unlock C, etc.", which isn't too uncommon a user case.
> stuff that previously could only be done in C/C++ (...) almost as easily as writing Python or Ruby
Metaprogramming, any? C++ has templates. Python and Ruby have metaclasses. What does Go have?
Go generate AKA C Macros but even worse since there is no macro syntax , you have to code you own code generator yourself .
Deployment happens mostly on Linux, but development happens mostly on OS X and Windows. Having guaranteed behavior, compiling it only once, being able to deploy as a simple JAR file, the same JAR file that you tested locally, is awesome.
> 5. Why does this program require 4GB of ram?
Java is actually very memory efficient, all things considering. There are Ruby developers choosing JRuby for deployment because of that efficiency. By the time Go's GC will reach the same maturity, it will behave similarly.
> 6. Must I really download and install the JVM all the time, and what is it good for anyway?
The JVM ensures consistent behavior across all platforms and is able to do optimizations based on runtime profiling, with JVM bytecode acting as a very efficient ABI, making the JVM an efficient target for multiple languages, including Scala, Clojure, Groovy, Ruby, Kotlin, Ceylon and others, languages that have been able to bootstrap easily and have a huge ecosystem at disposal because of the JVM.
> 1. Wow, I can write stuff that previously could only be done in C/C++, and I can do it almost as easily as writing Python or Ruby.
Go is not a replacement for C/C++ because it has a GC. In fact it's impossible to use Go for the same use-cases where C/C++ is required. And if you can use Go, then you can use Java as well. And in fact, because Java is more mature and has alternatives like Azul's pauseless GC, it's more amenable for projects with soft real-time constraints.
> 2. Wow, I don't need anything installed for my program to run, it just runs!
That's cool sometimes, but Java is almost as ubiquitous as POSIX and HTML5. On Linux it's basically one "apt-get install" away, just like everything else. So the advantage of not requiring a runtime for me is, you know, meh.
That makes me wonder about your universe of things to consider. Java's terrible memory usage was set in stone the moment they decided not to include structured value types.
https://en.wikipedia.org/wiki/Project_Valhalla_(Java_languag...
The Java language is definitely not set in stone.
If (and that's a big if) they introduce value types in 2018, it will have been almost 25 years since that fateful decision that has done so much damage.
Go owners have millions and millions of lines of existing Java code and they employ many people whose entire careers were made on top of Java.
I'm not saying there are no rational reasons to prefer Java over Go. But Google is hardly the yardstick for that.
An example would be how the IBM J9 JIT converts a final Point class, just with getters and setters into a value type.
Also there are language extensions from JVMs like IBM Packed Objects or Azul Object layouts that are exploring how to involve the language into value types.
It sucks that they didn't follow the route of Mesa, Modula-3, Eiffel and Oberon in regards to value types, but they aren't holding still.
But then you also need data structures that can be parameterized to store such value objects as values. Otherwise you're back to square one.
> Java is actually very memory efficient, all things considering.
Huh? Considering what? Compared to what?
> There are Ruby developers choosing JRuby for deployment because of that efficiency.
Yeah, Java !=JVM, and Ruby is not Go so this is kind of moot.
>By the time Go's GC will reach the same maturity, it will behave similarly.
Says who? You can't just state that as a fact without backing it up somehow.
The biggest issue with Java IMHO , 6 not so much since deployment is automated.
> 1. Wow, I can write stuff that previously could only be done in C/C++
Not true, like at all. Every Go does can be done with Java.
And, of course, it spawned a completely useless thread litigating Java vs. Go. Perhaps that's why it's at the top of the thread --- which means voting had a perverse effect for this topic.
I don't know what to do about this tendency in language threads on HN, but it's a real problem.
It also covers "important-to-me" features the author mentions. I haven't tried VSCode yet, but have tried all the others listed. IntelliJ is fantastic for Go.
Both approaches are totally valid, of course, but I suspect Go developers are biased toward lighter-weight editors.
https://groups.google.com/forum/#!msg/golang-nuts/hJHCAaiL0s...
https://en.wikipedia.org/wiki/1_Corinthians_13
I won't argue that it was in good taste.
https://www.biblegateway.com/passage/?search=1+Corinthians+1...
I know my setup isn't for everyone, but if you're looking for a good Go IDE experience, especially if your projects are of any size, don't pass over trying IntelliJ. I spend 95% of my time in Go now, and IntelliJ has been surprisingly good.
The existing command line Go tooling (while great) just don't do a good job at providing that kind of support to your IDE.
This one applies to every language. I was working with a python package that decided that, since `sys.argv` was available from anywhere, it should parse `sys.argv` to configure its own behavior. For a long time, their suggestion was to first parse `sys.argv` yourself, then to modify it before going into the library.
It was so ridiculous, someone ended up sending in a patch for the kernel to modify the command line once it had been parsed to remove the debug parameter.
Where flags shine is when you've some obscure tunable deep in the dependency tree that you need to tweak (particularly in an emergency). Plumbing through potentially thousands of flags through to main is nonsensical in that scenario.
Maybe you've seen a better flags library than I have, though.
When that came up what you'd do then is refactor that to be a class parameter or config option or whatever (and we'd usually ask that the flag be kept in some form).
Until then though you get the benefits of a quick and easy way to both expose and use tunables, which is much better than not having it at all.
Does anyone want to submit a best-practice Go solution?
> If your repo foo is primarily a binary, put your library code in a lib/ subdir, and call it package foo.
IMHO, that's just ugly, uglier than foo/foo or foo/foolib or foo/libfoo.
I also think that anything which has commands other than a single-command project which will always be a single-command project (there are fewer of these than one might think …) should put all commands, even a single one, in cmd/.
I think that inline config objects should be used with useful zero values to try to emulate Lisp's or Python's keyword arguments: if one always needs to provide a value for each config object member, then just use arguments after all.
I think a testing library can be a great addition, since it can turn a three-line if check into a one-line assertion.
It's this kind of inflexibility in the directory structure of ones repo that really turned me off of Go. It's such a trivial thing, and yet the fact that Go lacks a level of indirection (package.json, Cargo.toml, pom.xml, etc) to map a chosen directory structure to the standard build tooling causes problems that get really annoying. For instance, there's a ton of Go repositories out there that are not go gettable because the author wanted to put source code under a src directory and hacked that together using make. And good luck with organizing any repository that contains multiple languages where go is one of them...go's "code lives at the repository root" doesn't play well with others.
It all makes me sad since Go's decentralized dependency management (i.e. go get being able to pull/build based on a meta tag) is brilliant and I always hate having to rely on a single, centralized repository to deal with dependencies.
Are there? If someone's that ignorant of the language, I don't think I'd want to run something written by him …
> And good luck with organizing any repository that contains multiple languages where go is one of them...go's "code lives at the repository root" doesn't play well with others.
I've actually built libraries which involved both Go & Python without a problem.
Yes, there are. I don't know any off the top of my head, but I see them all the time. So, just for fun, how about a little test:
Step 1: Google 'notable applications written in golang'
>> first result: http://www.infoworld.com/article/2843821/application-develop...
Step 2: Click through to github repos
>> Result 9/10 of them won't work with go get.
So, are Docker, Kubernetes and Etcd the kind of software you wouldn't want to run because their creators are too ignorant of the language?
Totally concur with this. I feel like all these people complaining about "bloated test frameworks" either haven't written a lot of tests, or are just fine with repeating themselves in test code, or they end up writing their own version of a test framework anew in every project. So much simpler and sane to grab an off the shelf solution for test code.
(Disclaimer: I was the track host for Perer's talk)
I'm not sure if this is a nit, a misunderstanding on my part, or a difference in terminology, but I think what is meant here is "value constructors" (or more commonly, just "constructors"). As I understand the term, "type constructors" construct types.
We inject a logging interface into all our methods that take a context.Context object [1]. This allows us to push contextual information onto the stack of context objects, and then when we log we can do it at the point of failure and have access to an immense amount of useful information. Check the attached gist to see an example of how this works in practice [2].
Given that the context library originated out of Google and is now part of the stdlib in 1.7, I would love to see other libraries embrace it instead of relying on much less flexible solutions.
[1] https://godoc.org/golang.org/x/net/context
[2] https://gist.github.com/justonia/f81eead323d2b23eca1c485ed8e...
This seems kind of misleading. Per my understanding of Go, omitted fields in a struct initialization are defaulted not reported as errors. So you're equally likely to be passing invalid state, in the two situations.
One pattern I like in Haskell, for this kind of thing, is to define a defaultConfig value that contains typical defaults and which can then be tweaked as desired.
One big advantage this has is that when some functionality is made newly configurable, you set the default to be the old behavior and existing code continues to work correctly unmodified without any additional effort.
It still breaks down when a zero value is meaningful for a configuration parameter, but means something different than what was done before the parameter was configurable. I think that's probably not super often.
In light of all this, I still don't really see what harm we're avoiding by preferring the inlined struct initialization. I do agree it looks a little prettier, but the article seems to give it a greater import.
This might be a stupid question, but can someone explain to me what this means? Thanks!
Updating code you depend on is a semi-manual process - you choose to copy the latest version of the code you depend on into your project again.
This is contrast to stacks like Java, where I can give you a pre-compiled JAR file that you can link your code to.
git subrepo pull --all
> Top Tip — Libraries should never vendor their dependencies.
Peter goes on to clarify:
> You can carve out an exception for yourself if your library has hermetically sealed its dependencies, so that none of them escape to the exported (public) API layer. No dependent types referenced in any exported functions, method signatures, structures—anything.
I think this is the way to go if you're writing a library which has its own dependencies. You get a repeatable build and free yourself to change which dependencies you rely on without impacting users of your package.
There are exceptions, such as if your dependency has an init which only makes sense to run once. Loggers come to mind, where the setup should be determined by the main package. The f.Logger point in the article is friendlier to users of your package than just using log.Printf, and frees you from having to vendor logrus, for example, if you want to support structured logging.
I don't love it, like I love Python, but it does its job and it is fast.
What I really like is the defer(), the channels(having the option for asynchronous channels would be awesome), the go routines(async callback hell is getting old).
What I find completely awkward however is the enforced first letter capitalization(don't tell me how to live my life, go!), the interface{}, and the GC.
How does Go (including Go frameworks specifically geared towards web development) compare in terms of performance, ease of development with RoR, Laravel?
Is building websites using Go a good use case or is Go better suited for building high performance microservices?
(And yes, you can go the IPC route to introduce dynamism that you get out of the box from a VM based language. But here is the classic case of the Go [tail] wagging the architecture [dog]..)
[edit: correct tail endian]
- testing is way harder (ruby has some amazing mocking/stubbing/testing tooling).
- debugging is way harder. Hope you like printf.
- Json; the strict typing & struct searialization rules make dealing with Json a pain in the arse, and heavy on boilerplate
- interfacing with Sql (if you have to do a lot of it) is a pain in the arse, for similar reasons to json.
- having no stack for errors is insanely frustrating.
- templating in go is primitive
Go is amazing for services. The parallelisation primitives are fantastic, and allow you to do things that would be hard/impossible in ruby/Python. Go is undeniably much faster, execution wise. (Although our super high volume ruby product api is at 50ms median so, it matters less than you think)
Decide what you care about most; if your prime goal is to get a product in front of customers as soon as possible, I'd pick a higher level language. If you want to make a rock solid service that sips on resources & scales to the moon, use go.
Quantile your latency. I suspect you'll find 99th tells an interesting story between Ruby vs. Go. The best latency graph has five or six lines at different percentiles (yes, including 50) stacked in a latency sandwich. I'm willing to bet your app has a rough 99th. Maybe even a rough 95th. Nothing against Rails (honest, this applies to most interpreters), but most scripted stuff has a pretty rough latency tail, and you ignore that with median. (Go is not off the hook either; GC pauses can blow out high percentiles if you're memory-heavy.)
I'm pretty passionate about this, sorry. I'm on a mission from God to purge our mortal plane of average/median latency, because it's one of those misapplications of statistics that everybody does without a second thought. Don't even collect it. Average latency is unimportant and misleads people, and misleads people more as you get more popular. It's that 1% of clients sitting there for 2sec that impacts perception of your UX.
p99 blowout is generally an operational smell, even on low-RPS endpoints.
The median has absolutely not "comforted" us, nor do we disregard the percentile data. In fact, we have a whole perf team basically dedicated to looking at 95/9th & other slow transaction trace data, and fixing these.
In big projects, serving 10's of millions of users, with a handful of devs, you've gotta pick your battles, you cant fix everything always. We do our best, just like anyone else. So obviously we agree with the importance of percentiles. Dont make assumptions :)
And all of this is rather irrelevant to the main point now, which is overall _language_ speed.
I have not wandered off topic into irrelevancy nor talked past you. This is still addressing the point you attempted to make by citing median latency in defense of the performance characteristics of your chosen language, in order to assuage general hesitance to adopt Ruby over performance concerns. I think you'll find that your metrics do not support your data if you dig into that p99.
(I share that experience from handling tens of millions of users myself, which is all I can admit to publicly, so that request re: assumptions goes both ways.)
To recap: claim submitted with flawed supporting data, thread addressing why the supporting data is flawed. No talking past taking place.
And of course we've investigated further... (this is anecdotal i know), but of all the degenerate 99th cases we've investigated/solved, I can only think of 2 or 3 that were lang related, rather than logic, db, n+1s, etc. If you're curious, those were: - degenerate GC behaviour in a specific circumstance - JSON serialization (specifically crossing the C/ruby boundary shiteloads of times to serialize an object) Sure these issues sucked, but we mitigate/sidestepped those issues for the most part.
It's all a trade off when you're trying to decide what to use for your project; right tool for the job etc. Im not evalganizing for or against anything.
Curious what would you propose instead to roughly compare speeds of a product API? (Keeping in mind my anec-data about nearly all of 99ths being a logic/db issue). Comparing 99ths (from my experience) would be more like comparing which codebase has more bugs, because thats how we treat degenerate cases.
Fine, you claimed the performance difference "matters less than [one thinks]," which is pretty much the same thing if you really step back and think about it. It's also wrong for a whole cornucopia of reasons in general, but I'm choosing to focus on the supporting data you used to make that claim.
> Our go services run at about 5-15ms(excluding 95/99 etc),
See, nobody can resist middle-ground aggregations to describe things, even in a thread about middle-ground aggregations! They are such a cognitive trap. You should say "our Go services run at about 5-15ms half the time," because that'd be more correct if my assumption about where that aggregation is coming from is correct (and I'm guessing it's a gutstimate of median). And, again, 95th and 99th are super interesting, particularly when describing the performance characteristics of a latency-sensitive service, and it's a disservice to omit them.
I will absolutely say "about ___ms" and refer to my 99th and let people think I'm telling them average. To me, 99th is my average. (Normally I'd ignore this as pedantry, by the way, but it's the subject of the thread...)
> - JSON serialization (specifically crossing the C/ruby boundary shiteloads of times to serialize an object)
All of the terrible code in the world that handles JSON is one of my favorite "make this app go faster" targets. Its ease and ambiguity is its downfall, because people write genuinely awful code to interact with it. Most of that code is in language standard libraries. I will stand by that remark no matter how much you challenge me on it.
I'm of the fun school of thought now where I treat JSON as an external hot potato and throw it in a sane bag at the edge like protobuf or Thrift internally. If your internal services are communicating in JSON you are wasting a lot of cycles and bandwidth for pretty much no reason. You can switch to MsgPack and get an immediate win if IDLs aren't your thing, or CapnProto and get an even bigger win if they are. If you like being on the fun train, protobuf3+grpc is a pretty fun environment. This complaint even applies to Go even though Go shipped JSON in the standard library with clever reflection, so now everybody wants to lazily expect JSON configuration files which map cleanly to their internal config struct (please, stop doing this and write configuration formats that don't completely suck; looking at you, CoreOS).
Does serialization really matter, you ask? Profile your application and watch how much time it spends dealing with JSON. I've seen switching away from JSON remove the need for entire machines at scale. Whole machines. Because that many cores were freed up by not making every single instance spend 5-6% of its time marshaling and unmarshaling data.
> Comparing 99ths (from my experience) would be more like comparing which codebase has more bugs, because thats how we treat degenerate cases.
In other words, I was correct about organizational comfort with how you interpret 99th percentile latencies.
99th are not your degenerate cases. The poor souls in the 1% are your degenerate cases, and they are users too. A bad 99th percentile latency is bad, no matter how you justify it. Most folks write off 99.9th latency; 99th is a bit strong, especially if we're talking about your 10MM+ (M?)AU app. 1% of requests is a shitload of requests if your volume is as high as your audience description implies. I'm weird in that I consider a strange 99th+ as interesting data worthy of investigation, but I think that should be the norm, too.
As for comparing the performance characteristics of two separate apps, the metrics I'd start with are going to be RPS, TTFB, and TTLB. For the times I mentioned, σ (my personal favorite) as well as 50th, 75th, 90th, 95th, 99th, and 99.9th percentiles. Those are the externally-interesting ones. I also want to know how many cores are running it, how much RAM it consumes, and a whole bunch of other stuff on the inside. But it's a poor comparison at all, really; no two codebases are directly comparable, which I think you already know.
Umm, you do not get the median latency by averaging anything. Median latency is just the 50th percentile. It is definitely not one of the interesting ones to reason about or care about improving, but not valueless to measure. It is interesting to have if you are graphing your latency curves, to make an example.
Notice later in the comment I say average/median, implying that they are separate but related concepts. I think it's safe to assume that someone who can conversationally use the word "quantile" is not confusing median with mean. You're assuming that my (intentional) selection of a lower-fidelity term to describe a concept, which I carefully illustrated with ancillary points to give specificity to said concept, demonstrates a misunderstanding of the very field I'm explaining. That is pretty obviously wrong and a bit condescending.
We agree, which is what's frustrating. You're just latching on to a pedantic correction of my point, and rather than belabor that correction I encouraged you to reread to see that we do actually agree. Now, I do see average latency far more often than I'd care to admit, which is why I got lazy and just said "average" at the end there once I started referring to generality instead of specificity, but I think it's pretty clear that I understand the distinction regardless.
That feels like an overly-bold claim. Improving your 99th percentile latency from 2 seconds to 1 second may not be worth it if you bring your average latency up from 0.05 seconds to 0.99 seconds.
> It's that 1% of clients sitting there for 2sec that impacts perception of your UX.
Well, surely that depends on what endpoints those are and what people are expecting from them. A 2s wait for a whole rendered dashboard page of your entire organisation may not really be a concern. A 2s wait for 'find out more about our fast CDN' might really harm sales.
Now, if your point was "you shouldn't only look at average latencies" then you're entirely right, but I cannot see how they're irrelevant. The overall distribution is important and I'd actually recommend that people look at this shape. Just picking one percentile is always going to be misleading because you're throwing away a vast amount of data.
| ==== p99
|=================
ms |+++++++++++++++++++++ p95
|..................... p75
|````````````````````` p50
|---------------------
t ->
You gain a lot from this. Visually, you can see how tight your distribution is as the rainbow squeezes together. Narrower the better. Every time. In fact, very often the Y axis is irrelevant, and here's why:
Reining in your p99 that far at the expense of a higher average is, oddly, a win. That might surprise you but it is borne out in practice, because at scale only the long tail of latency matters. A wide latency distribution is problematic, both for scaling and for perception. A very narrow latency distribution is actually better. If you can trade off a bit higher latency for less variance/deviation, it will be a win every time. Weird, I know. User perception is weird and, as you point out, the rules change per-endpoint. Perception tends to evolve, too. As a rule of thumb, though, tighter distribution of latency is always better and how far you can push median to get there is your business decision and user study environment.
To borrow one of Coda Hale's terms[0], the scenario you presented demonstrates the cognitive hazard of average and is actually my root point. The average came up, yes. That is not necessarily bad (at all!), but "average" intuitively tells you that it maybe should be. In this case, it is misleading you, because the exact scenario you presented might be a strong win depending on other factors. A 99th of 1000ms with a 990ms average is a really tight latency distribution so it is fairly close to ideal for capacity planning purposes. It blew my mind when I discovered that Google actually teaches this to SREs because, like you, how unintuitive it is threw me off.
It's hard to swallow that a 990ms average might be better than 50ms. Might be. Average doesn't tell you. That's why it sucks. Not just for computing, either; average is pretty much the worst of the aggregations for cognitive reasons and is really only useful for describing the estimated average number of times you fart in a day to friends, because it is quite overloaded mentally for many people without experience in statistics.
Can't you use gdb with Go? https://golang.org/doc/gdb
You have other options: https://github.com/derekparker/delve
Check out https://github.com/pkg/errors
If you want more rich control of the output of the stack trace there's https://github.com/go-stack/stack
The available web frameworks for Go are more comparable to microframeworks like flask. If comparing directly to RoR or Laraval, you may find some gaps. Not that they can't be solved, but there's less available out of the box. Things like:
- multiple file upload
- session handling without cookies
- built in support for a variety of authentication types and backends
The communities are also significantly smaller, so there's less experience to draw on.
Not to say you can't build websites just fine with golang, but it's doesn't seem to be a strong suit at the moment.
Compared to something like Ruby on Rails, the development story with Go is much less batteries-included. You'll find yourself gluing together lots of components, and they're not really that friendly. Plus, for any front-end code, you'll end up using Node or whatever anyway to build assets. It's big and messy and not a good match.
Go does excel at two kind of web applications however:
- Simple single-page applications that use Websockets or simple AJAX to perform a basic task. In this case, the limitations around templating and such are less obvious, and Go is a brilliant match for Websocket clients. Think of things like status dashboards.
- JSON APIs with no front-end. Build your front-end using whatever other technology, and just fire requests at a Go app. It's pretty good at handling this, though JSON marshalling/unmarshalling is a bit stupid in Go.
Whether one can effectively write a classic website with complicated HTML templates and web forms like Rails,JSF and co allow is however questionable since Go type system lacks of expressiveness. Go fans answer is "use client side javascript" which is ironic since javascript is the antithesis of Go in terms of design.
I've also found it unexpectedly useful for some embedded applications. Deployin code to the raspberry pi is super simple and that makes it quite attractive - there are projects that provide for thing like i2c, GPIO and SPI, and combined with the built-in HTTP support its a pretty compelling platform.
Those reasons aren't really convincing to add another platform into the stack for me. I'd just continue using the many good-enough technologies to build those things on.
I was getting into Go some years ago and came to the same conclusion as you stated. It's good of course if its someone's favorite language to use, then it doesn't matter what it is and isn't great at. But in the end for me it didn't do enough, or do enough better than existing broad PLs that I already knew.
I think Go is still in need of a "killer usecase" to justify its usage for people like me. Rails was that for Ruby. Linux entrenchment and Django was that for Python (now numerics and scientific computing). Node for JS. That said, I'm a Go fan in theory as a "simple is better" type.
[0] view-source:https://dmitri.shuralyov.com/resume
Go is a different story. You need to join the pieces together to make something functional. You will probably need:
- A router like [Gin](https://github.com/gin-gonic/gin)
- A [XSRF token generator and validator](https://github.com/golang/net/blob/master/xsrftoken/xsrf.go)
- An ORM like [Gorm](https://github.com/jinzhu/gorm) or [XORM](https://github.com/go-xorm/xorm)
- A template lib like the one that comes with the stdlib
- Node for front-end (ugh, this is the harder part)
- The testing library in stdlib plus maybe [testify](https://github.com/stretchr/testify)
- etc...
Many nice things are missing. Some were [shamelessy copied by other people](https://github.com/go-testfixtures/testfixtures). Some you may need to implement yourself.
The big advantages is that Go has much better performance, and run on Windows, etc.
You are comparing apples to oranges. With go you can then select what functionality, libraries, toolkits or frameworks you want to use with your system.
ps. why would you mention node? would you use node with a php site?
I don't know nothing monolithic like Rails for Go, do you? What I was trying to say is that you have to use libs, instead of a big monolithic framework like Rails, that do not exists for Go (AFAIK).
I don't like Node and NPM, but it would be the alternative to Asset Pipeline (e.g. for concatenating and minifying JS and CSS, etc).
Revel is pretty monolithic: https://revel.github.io/
I've used it to build a web application, and here are some of the problems it addresses (this is just the table of contents from their manual):
- Controllers
- URL Routing
- Request Parameters
- Validation
- Session & Flash
- Results & Response
- Templates
- Interceptors
- Filters
- Websockets
- Internationalization
- Cache
- Database
- DebuggingAs a backend for a web application, Go's performance is pretty great. The Go standard library comes with a fast parallel-enabled HTTP server that already makes use of all your cores in recent Go versions. No need for things like gunicorn to take advantage of cores. There's no interpreter overhead, and there's plenty of benchmark comparisons with other languages out there on Google. I've never heard of someone not using Go as a server-side language because it wasn't fast enough :-)
Go has very robust support for creating web applications. Of course, for the frontend you will still need HTML+CSS+JS (maybe + a JS framework like Angular depending on your needs). There is a crazy experiment called GopherJS to run Go in the browser/frontend, but currently, a crazy experiment is all it is IMO...
For serving dynamic content, the Go standard library comes with its own templating language and library: https://golang.org/pkg/html/template/
The standard library also comes with most of the tools you'll need for defining HTTP routes (see the server examples): https://golang.org/pkg/net/http/
Personally, I've found the following third-party packages to be quite helpful with putting together HTTP server-side apps in Go:
- Gorilla mux for defining templated routes: https://github.com/gorilla/mux
- Negroni for HTTP route Middlewares: https://github.com/codegangsta/negroni
As you can see, most of what you need just comes with the standard library, which is quite professionally designed and coded (reading through their source is a pleasure). The two external dependencies I mentioned are helpful, but not a strict requirement to build a server-side app.
The main obstacle people have with using Go IMO has little to do with its ability to be used as a server-side language, and more to do with the nature of the language, and the consequences of its design choices. I think people who strongly prefer terse dynamic languages have trouble adopting/enjoying Go and its way of doing things. For instance, someone in this thread said that Go's structs and static typing makes it harder to work with JSON. You could also make the argument that this is a strength- all I have to do is declare a struct to specify what exactly I want to read from / write to JSON. Some people have complained about Go's verbosity. Sometimes they are right- certain things in Go take a little more text to express. I'm convinced that Go is a language that is more optimized for readability than for writability. You typically can't write "expressive" koans in a line of code... but your teammates probably have a higher chance (in my subjective opinion) of understanding the Go code you wrote a year after you've forgotten what you were thinking about.
I could go on and on, but now I'm just fighting the eternal language holy wars :-)
I hope I've given you a starting point for more research if you were considering Go for a server-side web application.
not my quote