neovintage

I feel like your con about not making the right design choices isn't a con. Solo development doesn't mean throwing out the principles that help you learn. Prototyping and beta releases exist to validate design choices without needing a team to debate them. If your software has users they become the sounding board. You mentioned only asking your friends about your ideas. The best part about prototypes and betas is that you get to build something, use it, and see if you like it before committing. If the idea doesn't get traction, throw it away!

“Data Downtime” is very real and can have terrible impacts on understanding what’s happening to customers or your business. I like that this series is taking the simple approach of using SQL to help identify the problems. (Its also a good lesson on window functions) Run these queries on some kind of schedule and you’ve got a decent solution to monitor the situation. Granted there’s different levels of sophistication to monitor these problems with better tools as your data volumes grow. The bigger problem beyond downtime is how to recover from these situations. I’ve seen many databases architected in ways where you can’t recover said downtime. That’s where change data capture could really help but I think that’s beyond the scope of this series.

I'm sorry code search isn't working. I'm more than happy to help. If you reach out to me via my email I can see whats up. neovintage [at] github [dot] com.

The premise around arrow is that when you want share data with another system, or even on the same machine between processes, most of the compute time spent is in serializing and deserializing data. Arrow removes that step by defining a common columnar format that can be used in many different programming languages. Theres more to arrow than just the file format that makes working with data even easier like better over the wire transfers (arrow flight). How this would manifest for your customers using your applications? They'd like see speeds increase. Arrow makes a lot of sense when working with lots of data in analytical or data science use cases.

Hey everyone. I had a lot of folks reach out to me about this change. We've heard y'all loud and clear that you want a better code search. The goal of this change was to balance performance and search relevance while we work on a new code search backend. The vast majority of folks shouldn't notice a change in their search results. The folks that will are those that are using code search to count things across all the repositories in GitHub. That's a use case that we don't expressly support as part of code search but we know folks are doing it anyway. My goal for publishing this was to be open about the change and for those folks that are using code search for analytics not have to guess at what happened.

I apologize the changelog wasn't more clear. For repos like that, they continue to show up in search results. Every time they do, that resets the clock on when the repo ages out of the index. We tried to strike a balance between performance and having _all_ the code in the index.

Agree with the improvement on code search results. Our team is working on it!

I believe Redis has a great developer experience. It’s easy to get set up and use. When I see the work on Redis streams, I think its going bring a much better getting started experience for developers that want to start using evented architectures. This might be a turning point where we see more developers and applications utilizing those types of architectures. In the end, this might give Apache Kafka a run for its money, or not, who knows. I've tried using Apache Kafka and it can be a bear to set up given its dependencies and to administer.

Put another way, I think Kafka solved a problem for enterprises and was a tops down approach to the problem. Redis streams is a bottoms up approach to implementing evented architectures. Maybe there's room for both products in the market?

The really important part of this post is the section articulating why not Dynamo. It uncovers a big question I ask of all of my customers when they're trying to choose data stores at any point during the life of their application.

Do you know your query patterns for your application?

If you know how your application / product need to pull data from the data store, you way more information that will allow you to pick the right data store to fit the problem at hand.

When you don't have any prior query patterns to go off of, picking a relational database to start your application is a good choice. You need the flexibility to allow your schema to change over time. The schema and query patterns will eventually reach a point where changes don't happen all that often and then you can look to other datastores if you need to scale. Plus, are you really going to have THAT much data when you start?

Disclosure: I work on Heroku Postgres. Could be a little biased....

Interesting offering. I wonder who they're targeting with this and the problem they're trying to solve.

* Is the expectation that everyone can write SQL?

* If the customer can write SQL and they're sufficiently large, won't they export the data into their own in-house data architectures to use the tools and processes they already have?

* Is data exporting that hard from stripe that they decided to offer a query tool instead?

I'm thinking they're going after the lower end of the customer base, the customers that may have medium to small transaction volumes. Plus those customers might not yet have any data warehousing to speak of.

If I was BareMetrics, I would be especially concerned because it will be a matter of time before Stripe has their own compelling offer that does almost everything it does and more. There have been other examples of building businesses around other companies APIs (granted theres always exceptions to the rule but I want to point out its a huge risk):

https://news.ycombinator.com/item?id=9512441

https://techcrunch.com/2012/10/14/why-you-shouldnt-build-a-b...

Thanks for the feedback! I'll see if we can get that in the guide.

I would recommend that you check out the Heroku CLI Style Guide: https://devcenter.heroku.com/articles/cli-style-guide

There are many different teams within Heroku that need to provide interactions for developers via CLI whether its for dynos or data services. The guide was a way to codify building a consistent interaction that all product managers and engineers could follow. Disclaimer: I work for heroku.

Anything proclaiming its going to "kill" some other business, likely isn't.

Google Docs is a great example of solving a problem that carved out a subsegment of Microsoft Office user base. I don't think any one solution is going to be the all encompassing one like Office has been.

Outside of speed benefits as compared to ruby, one of the main things going for crystal is it's ability to use all of the robust tooling that already exists. This post mentions it in passing but Crystal gets the benefit of all the existing tooling without having to build it as part of delivering the language to developers. I think that's a huge win. I also think this is one reason why Crystal has grown fairly quickly. This could largely but due to the fact that it's built upon LLVM. Regardless, the community and documentation is pretty awesome. I can't wait to see what happens for the 1.0 release.

I've spent a number of years using ruby and I got super excited about the potential of Crystal about a year ago. The notion that I can use a Ruby-like syntax and ship a binary to deploy my web apps was killer. But, a year ago the language was a bit rough, and to some extent, it still is. The team behind it is open about their goals and it blows me away with how much changes on a daily basis for a team of their size. Hopefully, the crystal team can set out to complete what they set their sights on for 2017[1]. That would really round out the feature set for a 1.0 release.

I think what I like the most is the community is willing to help you out. Although, nowadays a strong community is what makes or breaks a language.

[1] https://crystal-lang.org/2016/12/29/crystal-new-year-resolut...

I would start with the Mode Analytics SQL tutorial. It's fairly robust and gets into advanced topics: https://community.modeanalytics.com/sql/tutorial/introductio...

That will get you pretty far but the advanced SQL topics will require the study of what the underlying database provides and how it works. Every database is different in terms of how it implements advanced features, if at all. For example, MySQL doesn't have window functions. For postgres related topics, the documentation is excellent, postgresguide.com gives a high level overview, or you can follow craig's blog (http://www.craigkerstiens.com/) that provides a gentle introduction to many of these topics as well.

Interesting. I can think of a number of scenarios where this makes sense if you're using Redis for caching and you don't have a proxy in your architecture.

Does redis cluster only support one database? If that's still the case, then this is probably not available for the larger redis deployments.

Redis has a great developer experience. It's super easy to spin up and to add to applications. There have been a few warts though when it comes to operational experience in production. I really miss things like administrative connections and tls for client connections that I get in the relational db world. Also, using redis in highly regulated environments is challenging because you have to meet all sorts of compliance requirements. As a result, I find myself jumping through a ton of hoops to get redis to work there. It'd be great if it "just worked" in that arena.

Not yet. We're working it during our early access program. Well be looking for lots of feedback from customers.

I'm not sure what you mean by interactive data visualizations. But there are a bunch of companies and open source projects that have charts and you can interact with them:

* chartio (https://chartio.com) - commerical * looker (https://looker.com) - commerical * metabase (http://www.metabase.com/) - open source * http://fnordmetric.io/ - open source

There's a ton more that I haven't listed.

Thanks! The .env file is a nice touch. Can't wait to try it out.

Cool. Would love to hear about the drivers for building a db migration tool instead of using something like goose.

Have you tried using Postgres Foreign Data Wrappers? There's a redis fdw that will allow you to use SQL from Postgres and query the keys in Redis.

http://www.postgresql.org/docs/9.4/static/sql-createforeignd...

That's a great idea. Allowing for discovery at the command line is one of the biggest challenges I've faced. Your solution is definitely a good way to accomplish that and one I hadn't thought of. Do you think that the mode variable is a common enough pattern that advanced users would know to do that right off the bat?

That's what happens when I proof read too fast.

I think you're looking in the wrong place. Who cares about what the consumers think who've decided not to sign up? Personally, I don't think users know exactly what they want or how to convey how they feel about something. Dont get me wrong you need their input, but take it with a grain of salt.

Before thinking about why people aren't signing up for your service, think about who SHOULD be signing up for your service. What I mean here is, who exactly is your target customer for the service? Does this person use particular websites, do they only spend a couple of hours on the web every day, do they like to use twitter? (Since I really don't know what your service is I can't make better suggestions) Basically, what are the characteristics of your target customer? If your market is defined too broadly then your service doesn't really stand for anything. If your market is defined too narrowly then you'll be running into the problem where you don't have enough people signing up.

In terms of actionable steps, this is what I've done in the past for a business that's already running: 1. Do some research on your current customer base, mine your current database. Some questions to ask include: - What websites do they visit before hitting your site? - What websites do they go to once they've finished using your service? - How long do they spend on your site? - In a survey, how many people work at their company or how much revenue their company makes? - In a survey, ask how people heard of your site (subsequently visit those sites to see what context your site was mentioned)

2. What patterns are emerging from the research you've been doing? - The goal here is to find a type of user that have grown a strong affinity to your service. Once you've found that strong user, it's on to the next step.

3. What needs to change based on the patterns you've identified to attract more of those "strong users"? - This is easier said than done, but you need to think about pricing, value proposition for user (what is the user going to get out of using your site), or are advertising in the right places. - Much like the others have said in this thread, A/B test is a good idea if the value proposition is off. - You may want to consider advertising, if it resonates with the user. This includes all the typical social media outlets.

I hope this helps. Good Luck!

I'm a little skeptical about this one. For one, when doing corporate strategy and deciding what to build, you need to understand the dynamics and deficiencies in the marketplace. So at some level, someone within the organization had to evaluate using either primary (focus groups, surveys) or secondary (already published studies and facts) research to see if the idea or product was viable. Now I'm guessing that secondary research might be more the norm at Apple because primary research might give people that are in the potential target market an idea of what new products are in the pipeline. Apple wouldn't want to give hints at what it's doing by performing primary research.

I'm not staying they have to do tons, they need to have some understanding of who they're going after.

I agree that it might not be like every other corporate venture arm. Although, if I had to speculate, I think Google is doing this because it needs to diversify its business outside of generating cash through advertising. By investing in ventures, Google should be able to supplement its income nicely, keep its stock price high, and not have in increase operating expenses too much should anything that they invest in takes off.

In the interest of full disclosure, I am a current MBA student during the day and developer by night.

Its unfortunate that this article focused solely on the financial industry. I agree that some schools seems to breed more of what the author is referring to in the industry. Yet I think its a blanket generalization to all MBA programs. The MBA typically gets a bad wrap when any economic problems start to occur. Most people will then start to quote statistics that say most of the top companies do not have MBAs at the helm, so why do we need these MBA programs? What about those that have worked on Social Ventures during their MBAs? Are they guilty of wasting their time in an MBA program?

I chose to get an MBA so that I could understand the business side of things more and to build a professional business network, the latter being the most important. You'd be surprised at the background of people you meet in school. Do I think that everything taught to me in the program should be taken as gospel? No.