Rail Aliiev: Taskcluster: First Impression

Вторник, 31 Марта 2015 г. 15:47 + в цитатник

Good news. We decided to redesign Funsize a little and now it uses Taskcluster!

The nature of Funsize is that we may start hundreds of jobs at the same time, then stop sending new jobs and wait for hours. In other words, the service is very bursty. Elastic Beanstalk is not ideal for this use case. Scaling up and down very fast is hard to configure using EB-only tools. Also, running zero instances is not easy.

I tried using Terraform, Cloud Formation and Auto Scaling, but they were also not well suited. There were too many constrains (e.g. Terraform doesn't support all needed AWS features) and they required considerable bespoke setup/maintenance to auto-scale properly.

The next option was Taskcluster, and I was pleased that its design fitted our requirements very well! I was impressed by the simplicity and flexibility offered.

I have implemented a service which consumes Pulse messages for particular buildbot jobs. For nightly builds, it schedules a task graph with three tasks:

generate a partial MAR
sign it (at the moment a dummy task)
publish to Balrog

All tasks are run inside Docker containers which are published on the docker.com registry (other registries can also be used). The task definition essentially comprises of the docker image name and a list of commands it should run (usually this is a single script inside a docker image). In the same task definition you can specify what artifacts should be published by Taskcluster. The artifacts can be public or private.

Things that I really liked

Predefined task IDs. This is a great idea! There is no need to talk to the Taskcluster APIs to get the ID (or multiple IDs for task graphs) nor need to parse the response. Fire and forget! The task IDs can be used in different places, like artifact URLs, dependant tasks, etc.
Task graphs. This is basically a collection of tasks that can be run in parallel and can depend on each other. This is a nice way to declare your jobs and know them in advance. If needed, the task graphs can be extended by its tasks (decision tasks) dynamically.
Simplicity. All you need is to generate a valid JSON document and submit it using HTTP API to Taskcluster.
User defined docker images. One of the downsides of Buildbot is that you have a predefined list of slaves with predefined environment (OS, installed software, etc). Taskcluster leverages Docker by default to let you use your own images.

Things that could be improved

Encrypted variables. I spent 2-3 days fighting with the encrypted variables. My scheduler was written in Python, so I tried to use a half dozen different Python PGP libraries, but for some reason all of them were generating an incompatible OpenPGP format that Taskcluster could not understand. This forced me to rewrite the scheduling part in Node.js using openpgpjs. There is a bug to address this problem globally. Also, using ISO time stamps would have saved me hours of time. :)
It would be great to have a generic scheduler that doesn't require third party Taskcluster consumers writing their own daemons watching for changes (AMQP, VCS, etc) to generate tasks. This would lower the entry barrier for beginners.

Conclusion

There are many other things that can be improved (and I believe they will!) - Taskcluster is still a new project. Regardless of this, it is very flexible, easy to use and develop. I would recommend using it!

Many thanks to garndt, jonasfj and lightsofapollo for their support!

http://rail.merail.ca/posts/taskcluster-first-impression.html