As our production application systems continuously increase in complexity, the challenges of understanding, debugging, and improving them keep growing by orders of magnitude. The practice of Observability addresses both the social and the technological challenges of wrangling complexity and working toward achieving production excellence. New research shows how observable systems and practices are changing the application performance management (APM) landscape.
Observability Requires Both Technical and Social Approaches
Tooling alone can't solve anything, it's just a necessary part of any solution. Tackling the challenges of managing complex production systems isn't just a technical problem and it isn't just a social problem. We manage sociotechnical systems and any reasonable solution must take that into account in order to be effective.
Observability isn't logs, metrics, and tracing. Yes, those aspects are important. Those tools can help shed light on what's happening in the systems that are critical to your business. However, there's a big difference between having tools that provide instrumentation and using them to achieve better outcomes. Many of today's tools require you to predict the future by knowing in advance what conditions to monitor, which trends to look for, or the correlations you need to make to find application performance hotspots.
The coveted observability sweet spot is finding the unknown unknowns. Observability is a sociotechnical practice that allows you to answer any arbitrary questions about your environment, without needing to know ahead of time what you wanted to ask. However, it's doing the work that proves a bit more challenging for many teams, especially those weaning off legacy tools.
Practicing observability is a journey. It takes time for entire teams to adopt new practices and shift mindsets to a model of shared ownership. Our new study shows how different teams are practicing, or intending to practice, observability within the next two years. The report also examines the challenges teams face and the practices they are implementing as they progress on their observability journey.
Observability Maturity Research Findings
Teams must decide how to start their observability journey. Those early decisions have a high degree of impact because they influence both tool choices and habits during the software development and delivery lifecycle. Teams that adopt recommended observability practise to an advanced degree see greater benefits than less advanced teams. Advanced teams stabilize their systems, spend less time reactively fixing issues in production/refactoring code/resolving technical debt, and spend more time proactively innovating.
The report affirms that adopting observability tools, site reliability engineering (SRE) practices, and a culture of shared ownership translates to efficiencies across the software engineering cycle, better end-user experiences, and ultimately helps teams achieve production excellence.
Outcomes are much more pronounced when teams apply observability mindsets and processes in conjunction with tooling. That combination can lead to a virtuous cycle of reinforcement, presuming those teams are using tools purposely designed to address observability use-cases. Research findings show that most teams adopt a handful of tools across disparate teams to accomplish daily tasks. Yet it's that same juggling of different tools that creates confusion, frustration, an oft-heard complaint of tool bloat, and ultimately leads to slower performance.
Go to Advanced Observability Teams See Big Efficiency Gains - Part 2
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