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Author: Adam

You don’t have enough static analysis


Pretty much every programming language out there has tools that statically analyze your source code and detect different problems. These problems can range from simple things like ensuring that you have consistent casing for variable names in Java to ruthlessly enforcing method limits in Ruby. If you’ve ever used one of these tools, they may seem overbearing and not worth the hassle, but they will soon prove their value once your application becomes larger, has multiple developers, or is business critical and can’t afford outages caused by trivial mistakes. Static analysis tools are a super-low cost solution for improving the quality of a code-base.

Structured and audit-able changes to infrastructure

Note: I’m going to use AWS services as most of my examples for this post, but that’s just because I’m most familiar with them, the patterns found below are not limited to just AWS and can be applied to any cloud provider or self-hosted where similar patterns exist.


Every service has some amount of supporting infrastructure required to support it. This includes any virtual servers (EC2 or other), storage (ex. S3, DynamoDB), load balancing, etc. basically any resources that your service uses that is not your direct business logic could be considered infrastructure. If you use continuous integration and change control on your business logic, then why would you not apply the same rules to your infrastructure?

Allowing and requiring developers to make changes using the UI introduces risk that one might make a mistake and bring down your production service. Continuing from my last post about infrastructure names, you could also make a mistake in any of regional clones.

Dynamic AWS resource discovery for one-click region spin-ups

Disclaimer: At the time of this article’s writing, I work at Amazon, but not in AWS. This article is based on my own research and ideas and is not the official position of Amazon. This article is not intended as marketing material for AWS, only as some architectural patterns for you to use if you do leverage AWS.

AWS provides a number of different resources that you can use to build services using, including S3 buckets, SQS queues, etc. When you create a new instance of that resource, you must pick a name that usually must be unique in a given namespace. Depending on your naming scheme, you may also have to start embedding resource names in code or configuration files. This makes spinning up new regions difficult as now you have to update configuration with names for every stage/region that you might use. This may not seem like that big of a deal, but consider that you may have tens of different SQS queues, S3 buckets, etc. for each region/stage. This can begin to combinatorically explode as you now have # regions * # stages * # resources of different configuration definitions. This results in a lot of boilerplate.

But what if there was a better way?

Fast development environments

Setting up new hosts entries for every different web site that you develop is hard. This workflow allows you to completely automate it. First thing you’ll want to do is setup a wildcard DNS record that points to your host. This allows you to dynamically setup new development websites without having create new DNS records for each one of them. I created a fake internal-only TLD on my local network’s DNS server that automatically returns the IP address of my development VM for any query to *.devvm. If you don’t have access to that, you could re-use an actual domain and automatically forward something like * to the VM.