Netfilx has been getting more and more attention, and I think part of that reason is they talk about things that go wrong, things that they have learned from. Netflix has learned the lesson that people listen much more when you talk about your mistakes then when you self promote your error free ways.

Netflix's latest move is to release Chaos Monkey to the open source community. Here is their blog post.

Chaos Monkey released into the wild

By Cory Bennett and Ariel Tseitlin

We have found that the best defense against major unexpected failures is to fail often. By frequently causing failures, we force our services to be built in a way that is more resilient. We are excited to make a long-awaited announcement today that will help others who embrace this approach.

We have written about our Simian Army in the past and we are now proud to announce that the source code for the founding member of the Simian Army, Chaos Monkey,is available to the community.

Do you think your applications can handle a troop of mischievous monkeys loose in your infrastructure? Now you can find out.

What is Chaos Monkey?

Chaos Monkey is a service which runs in the Amazon Web Services (AWS) that seeks out Auto Scaling Groups (ASGs) and terminates instances (virtual machines) per group. The software design is flexible enough to work with other cloud providers or instance groupings and can be enhanced to add that support. The service has a configurable schedule that, by default, runs on non-holiday weekdays between 9am and 3pm. In most cases, we have designed our applications to continue working when an instance goes offline, but in those special cases that they don't, we want to make sure there are people around to resolve and learn from any problems. With this in mind, Chaos Monkey only runs within a limited set of hours with the intent that engineers will be alert and able to respond.

There are more Monkeys coming from the Simian Army.

Inspired by the success of the Chaos Monkey, we’ve started creating new simians that induce various kinds of failures, or detect abnormal conditions, and test our ability to survive them; a virtual Simian Army to keep our cloud safe, secure, and highly available.

Latency Monkey induces artificial delays in our RESTful client-server communication layer to simulate service degradation and measures if upstream services respond appropriately. In addition, by making very large delays, we can simulate a node or even an entire service downtime (and test our ability to survive it) without physically bringing these instances down. This can be particularly useful when testing the fault-tolerance of a new service by simulating the failure of its dependencies, without making these dependencies unavailable to the rest of the system.

Conformity Monkey finds instances that don’t adhere to best-practices and shuts them down. For example, we know that if we find instances that don’t belong to an auto-scaling group, that’s trouble waiting to happen. We shut them down to give the service owner the opportunity to re-launch them properly.

Doctor Monkey taps into health checks that run on each instance as well as monitors other external signs of health (e.g. CPU load) to detect unhealthy instances. Once unhealthy instances are detected, they are removed from service and after giving the service owners time to root-cause the problem, are eventually terminated.

Janitor Monkey ensures that our cloud environment is running free of clutter and waste. It searches for unused resources and disposes of them.

Security Monkey is an extension of Conformity Monkey. It finds security violations or vulnerabilities, such as improperly configured AWS security groups, and terminates the offending instances. It also ensures that all our SSL and DRM certificates are valid and are not coming up for renewal.

10-18 Monkey (short for Localization-Internationalization, or l10n-i18n) detects configuration and run time problems in instances serving customers in multiple geographic regions, using different languages and character sets.

Chaos Gorilla is similar to Chaos Monkey, but simulates an outage of an entire Amazon availability zone. We want to verify that our services automatically re-balance to the functional availability zones without user-visible impact or manual intervention.