1. Install minikube (https://github.com/kubernetes/minikube#installation);
2. Authenticate local docker:

   gcloud auth configure-docker  # part of `make gke_login`

3. Launch minikube:

   ./minikube.sh start

4. Make sure the kubectl tool uses the minikube k8s cluster:

   minikube status
   kubectl config use-context minikube

5. Load images into minikube's virtual machine:

   ./minikube.sh load-images

6. Apply minikube configuration and some k8s fixture services:

   ./minikube.sh apply

7. Create a new virtual environment with Python 3.11:

   python -m venv venv
   source venv/bin/activate

8. Install testing dependencies:

   make setup

9. Run the unit test suite:

   make test_unit

10. Run the integration test suite:

    make test_integration

11. Cleanup+shutdown minikube:

    ./minikube.sh clean
    ./minikube.sh stop

Job container logs are tracked by Fluent Bit and sent to S3 compatible storage using Amazon S3 plugin. Files are pushed to S3 every minute for each running job. S3 keys have format kube.var.log.containers.{pod_name}_{namespace_name}_{container_name}-{container_id}/{date}_{index}.gz.

Logs are periodically compacted (every hour by default). Logs compaction consists of two phases: merging and cleaning. After merging phase certain number of log files are merged into one and pushed to S3. Cleaning of the merged files is done before the next merging phase to avoid situations where log files are being deleted while user is reading them.

S3 log reader is capable of reading both merged and raw log files and combining them into a single job log output.

Batches of raw Fluent Bit logs files are merged and pushed to S3 under data folder. S3 keys have format data/{pod_name}/{container_id}/{date}_{index}.gz. Additionally for each job a separate metadata file is maintained, it has a key format metadata/{pod_name}.json. It contains the list of all the merged files and some additional statistics.

Every time merging is done for a certain job its name is pushed to the cleanup queue. This queue is just a folder in S3 bucket and we need it in order to perform one last cleanup once the job finishes or stops producing logs. After cleanup job is removed from the queue.