The collection and storage of observability data is critical for day to day operations and long term health of clusters and applications. The increasing volume of this observability data can be leveraged by AI algorithms and data analytics to automate triaging, response, and remediation for common issues, reducing mean time to detection and resolution. To achieve this observability based AIOps system, one must be capable of implementing AI algorithms, set up a combination of logging, monitoring, and tracing backends to store data, and agents for each type of observability data in downstream clusters to ship data to the backend. This complex setup can be challenging to users and this talk will demonstrate how Opni can be leveraged to simplify the setup and management of a fully open source AIOps & observability system.

Log aggregation is one of the cornerstones of observability but setting up a logging stack can be overly complicated. As the number of clusters an operations team are expected to manage explodes a simpler solution is needed. This talk will demonstrate how we can simplify this process and set up a log aggregation platform in 5 minutes.