Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update best-practises-jenkins-stability.md #2206

Merged
merged 3 commits into from
Sep 28, 2023
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ Unlike in cloud, in a local environment, these commands are executed by a CLI co

## Memory management

One of the most common issues encountered with Jenkins is excessive memory usage. In a local development environment, Docker containers are usually set up to use as much RAM as they need as long as they stay within the RAM limit configured in Docker. This limit often corresponds to the total RAM available on the machine. However, when deployed to cloud, the Jenkins container is deployed to its own dedicated server, which limits the available RAM based on the server's configuration. Non-production environments have different RAM configuration tiers, which can be found in our Service Description. Standard environments typically assign 2 GB of RAM to Jenkins. This means that the server running Jenkins has a total of 2%nbspGB of RAM. Considering some overhead for the operating system, Docker, and Jenkins itself, around 1-1.5 GB of memory is usually available for PHP code execution. This shared memory needs to accommodate all console commands run on Jenkins. Therefore, if you set `php memory_limit` to 1 GB and have a job that requires 1 GB at any given time, no other job can run in parallel without risking a memory constraint and potential job failures. The `php memory_limit` does not control the total memory consumption by any PHP process but limits the amount each individual process can take.
One of the most common issues encountered with Jenkins is excessive memory usage. In a local development environment, Docker containers are usually set up to use as much RAM as they need as long as they stay within the RAM limit configured in Docker. This limit often corresponds to the total RAM available on the machine. However, when deployed to cloud, the Jenkins container is deployed to its own dedicated server, which limits the available RAM based on the server's configuration. Non-production environments have different RAM configuration tiers, which can be found in our Service Description. Standard environments typically assign 2 GB of RAM to Jenkins. This means that the server running Jenkins has a total of 2 GB of RAM. Considering some overhead for the operating system, Docker, and Jenkins itself, around 1-1.5 GB of memory is usually available for PHP code execution. This shared memory needs to accommodate all console commands run on Jenkins. Therefore, if you set `php memory_limit` to 1 GB and have a job that requires 1 GB at any given time, no other job can run in parallel without risking a memory constraint and potential job failures. The `php memory_limit` does not control the total memory consumption by any PHP process but limits the amount each individual process can take.

We recommend profiling your application to understand how much RAM your Jenkins jobs require. A good way to do this is by utilizing XDebug Profiling in your local development environment. Jobs that may have unexpected memory demands are the `queue:worker:start` commands. These commands are responsible for spawning the `queue:task:start` commands, which consume messages from RabbitMQ. Depending on the complexity and configured chunk size of these messages, these jobs can easily consume multiple GBs of RAM.

Expand All @@ -24,3 +24,7 @@ We recommend profiling your application to understand how much RAM your Jenkins
Jenkins executors let you orchestrate Jenkins jobs and introduce parallel processing. By default, Jenkins instances have two executors configured, similar to local environment setups. You can adjust the executor count freely and run many console commands in parallel. While this may speed up processing in your application, it increases the importance of understanding the memory utilization profile of your application. For stable job execution, you need to ensure that no parallelized jobs collectively consume more memory than what is available to the Jenkins container. Also, it is common practice to set the number of executors to the count of CPUs available to Jenkins. Standard environments are equipped with two vCPUs, which means that configuring more than the standard two executors risks jobs "fighting" for CPU cycles. This severely limits the performance of all jobs run in parallel and potentially introduces instability to the container itself.

We recommend sticking to the default executor count or the concurrent job limit recommended in the Spryker Service Description for your package. This will help ensure the stability of Jenkins, as configuring more Jenkins Executors is the most common cause of Jenkins instability and crashes.

## Queue worker configuration

If you have configured multiple queue workers per queue, keep in mind that the comments made above regarding memory management also apply in this scenario. Each configured queue worker can consume up to PHP's max_memory, causing a significant increase in total memory demand as they are spawned. Another crucial factor to take into consideration is CPU utilization. If you have configured more workers than the number of available cores, it becomes increasingly likely that processes will need to wait for CPU resources. This can ultimately lead to suboptimal performance and potentially even stability issues. We recommend avoiding resource contention of this nature by adjusting the number of workers in a manner that aligns with your environment package. Our service description specifies the number of CPU cores available to you in each package.