amazon-eks-ami VS JaCoCo

Careful assuming system reserved will be present. Last I checked, AWS EKS does not have system reserved resources for the kubelet by default and as a result, pods can starve those for resources (e.g., https://github.com/awslabs/amazon-eks-ami/issues/79). This is of course more important for memory, but could impact CPU as well.

For example, this is available for AL2: https://github.com/awslabs/amazon-eks-ami

I found this document that lists the pod limits per node size. I suspect you will want to consider larger worker nodes or you will very quickly be unable to schedule additional workloads.

source

Issue 1 is a known issue due to memory reservation being to low, see e.g. https://github.com/awslabs/amazon-eks-ami/issues/1145

No, the new node is added if there are not enough resiurces to start a new pod. So if you have many pods with small resource usage you can hit the pod per node limit, on eks you have a max number of pods depending on the instance type - https://github.com/awslabs/amazon-eks-ami/blob/master/files/eni-max-pods.txt You can incerase that limit : https://docs.aws.amazon.com/eks/latest/userguide/cni-increase-ip-addresses.html

# of pods are essentially capped by the worker node choice.

below excerpt from: https://github.com/awslabs/amazon-eks-ami/blob/master/files/...

  # Mapping is calculated from AWS EC2 API using the following formula:

See also: EKS nodes lose readiness when containers exhaust memory

So it manifests itself in this way: your pod is scheduled but remains pending forever. You check the logs and you see that it's complaining that the an IP address. Ultimately, if you check here, you see the maximum number of pods that can be scheduled on any underlying ec2 instance, even if you have remaining IPs in your subnet. I found this to be one of the most poorly understood phenomena in EKS. Even those who claimed to "crack" it and wrote fancy blog posts about it fundamentally got it wrong. AFAIK this document reflects the official AWS guide on how to mitigate this.

I will use here JaCoCo, where also the JaCoCo-Maven-lugin exists for the usage in your Maven builds. This article will show how to configure the code coverage to finally get the results for unit- and integration-tests.

In protection rules, I added build workflow in Require status checks to pass before merging. This is to ensure that before merging code in master branch, build should run successfully. I also added Jacoco Code Coverage to make sure that enough unit tests are available in project and Detekt to make sure that code in project is readable. I added them in build configuration. Even if one of them gives error, build will fail. Whenever, someone push code in pull request, build action will run and check if build is running successfully or not.

Code coverage analysis tools quantify the amount of tested code, serving as a valuable tool to inform on code structure and testing related decisions. We will make use of JaCoCo, JaCoCo produces reports on multiple kinds of code coverage metrics including instructions, line and branch coverage.

One specific example where I regularly use a profile in this way is for configuring code coverage. In all of my Java projects, I use JaCoCo for generating code coverage reports. I use JaCoCo during the Maven test phase. However, while developing I find it useful at times to exclude coverage reporting to reduce the build time. But in my CI/CD workflows in GitHub Actions, I activate the code coverage profile during pull-requests and pushes to the default branch. For pull-requests, my GitHub Actions workflow comments the code coverage on the PR and uploads the coverage report as a workflow artifact, where I can inspect it as necessary. And during a push to the default branch, my workflow updates coverage badges to keep them up to date with the current state of the default branch. I can also activate the code coverage profile locally while developing, such as prior to submitting a pull-request, to ensure that I didn't miss testing something.

In Unit tests, individual software code components are checked if it is working as expected or not. Unit tests isolate a function or module of code and verify its correctness. We can use tools like JaCoCo for Java and Mocha, and Jasmine for NodeJS to generate unit test reports. We can also send these reports to SonarQube which shows us code coverage and the percentage of your code covered by your test cases.

And there is the original jacoco/jacoco: (0.8.7: released this on May 5, 2021), but it's for Java. I'm not sure if we can use it with multiple flavors on Android.

Make sure to also update to Jacoco 0.8.7 to avoid test issues: https://github.com/jacoco/jacoco/releases/tag/v0.8.7