Observability instruments systems and applications, collects metrics and logs, and enables an understanding of system behavior. Observability goes beyond traditional monitoring approaches to explain system behavior over time and provide accurate operational insights. And, in alignment with the new direction of DevOps, observability examines the sequence of a problem through monitoring, correlating the system data, and automating with ML. Observability provides DevOps with end-to-end system visibility to quickly respond, fix, and prevent problems. Observability helps organizations:
Observability and monitoring are complementary solutions, meaning one does not replace the other. Effective monitoring almost always includes observability.
Monitoring collects metrics and logs that provide information on whether the system is working, and it tells you when something went wrong. Put another way, monitoring is building your systems to collect data, with the goal of knowing when something goes wrong and starting your response quickly.
Observability instruments your systems with tools to gather actionable data that provides not only the when of an error or issue, but—more importantly—the why. Observability typically shortens the duration and reduces the impact of incidents.
While today’s world of accelerated cloud and microservices adoption has greatly advanced innovation and helped organizations reduce time to market, it has also increased operational complexity resulting in increasingly ephemeral environments with unpredictable behavior.