Definition: Observability is the ability to understand what is happening inside a software system from the data it emits, mainly logs, metrics and traces, so teams can detect, investigate and fix problems quickly.
Metrics show trends such as error rates and latency. Logs record individual events. Distributed traces follow a request across services. OpenTelemetry has become a common open standard for collecting these signals, which tools such as Datadog, Grafana, New Relic and Honeycomb analyze.
Monitoring checks known conditions and alerts when thresholds break. Observability aims to answer new questions about unexpected failures without shipping new code, which matters most in distributed systems such as microservices.
AI applications need extra signals, such as prompts, outputs, token usage and quality scores, covered by AI observability. Observability data also feeds SRE practices such as service level objectives. Teams usually start by instrumenting the most critical user journeys, then expand coverage and tune alerts to cut noise.
Ryz site reliability engineers and DevOps engineers instrument systems in your stack, working on your team.
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