The importance of observability has been well established, with organizations relying on metrics, logs, and traces to help detect, diagnose, and isolate problems in their environments. But, like most things in IT, observability is continuing to evolve rapidly – both in terms of how people define it and how they are working to improve observability in practice.
I’ve argued in the past that observability is, at its core, a data analytics problem. The formal definition of observability tends to center on the external outputs of IT systems. I use a slightly broader definition of observability: “The capability to allow a human to ask and answer questions about the system.” I like this definition because it suggests that observability should be incorporated as part of the system design (rather than being bolted on as an afterthought) and because it underscores the need for engineers and system administrators to bring an analytics mindset to the challenge of enabling observability.
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