"Support for distributed systems. Check how well the tool handles microservices, serverless, and Kubernetes. Can you follow a request across services, queues, and third-party APIs? Does it understand pods, nodes, clusters, and autoscaling events, or does it treat everything like a static host? Correlation across metrics, logs, and traces. In an incident, you shouldn't be copying IDs between tools. Look for the ability to pivot directly from a slow trace to relevant logs,"
"Alerting and noise reduction. The best alert is the one that fires rarely and points to something actionable. Evaluate support for dynamic baselines, composite alerts (for example, error rate and latency together), and ways to group related issues. Ask how the tool helps you reduce "flapping" alerts during deployments or traffic spikes. Time to value and ease of setup. Instrument a single critical service end to end-code, infra,"
Elastic APM often fits teams that already run Elasticsearch at scale and want to add APM without bringing in a separate vendor. Check support for distributed systems: microservices, serverless, and Kubernetes, and the ability to follow a request across services, queues, and third-party APIs while recognizing pods, nodes, clusters, and autoscaling events. Ensure correlation across metrics, logs, and traces to pivot from a slow trace to relevant logs and infrastructure metrics without copying IDs between tools. Evaluate alerting for dynamic baselines, composite alerts, grouping, and reduction of flapping during deployments. Measure time to value by instrumenting a critical service end-to-end and assessing manual versus automatic configuration and developer instrumentation overhead.
#elastic-apm #distributed-systems #metrics-logs-traces-correlation #alerting-and-noise-reduction #time-to-value
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