Measure and implement any necessary improvements to ensure OLM v1.0.0 meets or exceeds OCP guidelines around performance and scalability.
Why is this important?
OLM v1.0.0 will be a payload component that always runs in OCP clusters. In order to reduce SD and customer costs, we need to minimize this overhead.
OLM v1.0.0 is intended to be used on a wide variety of clusters, ranging from single node clusters with just a few namespaces to clusters 2-3 orders of magnitude larger. We need make sure that it runs just as well on a small cluster as it does a large cluster.
In order to reduce user frustration, we need to provide a responsive user experience. Reconciliation needs to be fast and non-blocking to ensure users receive the experience they have come to expect from OCP. To the extent possible, long-running tasks (e.g. catalog fetching/caching and image pulling) should be performed asynchronously.
Scenarios
Collect pprof profiles for CPU and memory when running standard user flows around installing, upgrading, and removing operators from public catalogs (e.g. operatorhub)
Find the most resource intensive code paths. Provide documentation and recommendations related to making improvements in those areas.
Coordinate with OLM maintainers to make improvements in areas deemed to provide the most significant performance and scale gain.
Implement automated performance and scale regression tests in the existing upstream CI test suite.
Examples of known areas for improvement include:
When reconciling a ClusterExtension to resolve a bundle from the criteria provided by a user, the reconciler should return a desired bundle within 100ms and allocate no more memory than the size of the catalog metadata for the named spec.packageName.
When the ClusterExtension reconciler does not have the contents of a resolved image bundle available, it does not block waiting for the image to be pulled and processed. Rather, it starts an asychronous job, reports the pending image pull via the ClusterExtension status, and returns from reconcile.
Epic Goal
Why is this important?
Scenarios
Examples of known areas for improvement include: