DevOps Observability from Code to Cloud

Modern software delivery practices have evolved over time. We have things like GitOps, AIOps, DataOps, etc., that enterprises employ and experiment to see which one fits well to their needs. It is not just about being agile or speedy these days; companies focus more on the stability of the infrastructure.

While the advancements in DevOps and cloud native practices are in full bloom, it is highly essential to strictly monitor and observe metrics, logs, analytics, and datasets associated with the infrastructure performance to optimize system dependability.

Things were pretty siloed in the age of waterfall software development; nobody knew what others were doing in the software development life cycle. While developers worked on building new features, the testing team and operations tested the features separately, and hence there was a communication and collaboration gap. The monitoring aspects were far beyond the development team’s control. The features were built keeping only success in mind while ignoring the chaos engineering and infrastructure dependencies since the developers less understood these.

More than just another buzzword bingo, observability helps organizations by providing them with solid indicators that let them pinpoint their infrastructure and system problems so they can begin resolving them during the most efficient phase possible. Monitoring was given less importance, and nobody knew what was happening between and within these systems. This made companies have less visibility over their own infrastructure. Hence, monitoring and observability have taken the prime spots in the cloud native space today.

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