Monitoring watches for conditions you decided to check in advance and alerts when they break. Observability is the ability to ask new questions about a running system, including ones you did not predict, using the telemetry it emits. Monitoring tells you that something is wrong. Observability helps you find out why.
How do the sources define them?
Google's SRE book describes monitoring as collecting, processing, aggregating and displaying real-time quantitative data about a system, with uses including alerting and dashboards, and ad hoc retrospective analysis. Its guiding idea: monitoring and alerting let a system tell us when it is broken, or about to break.
OpenTelemetry's primer defines observability as understanding a system from the outside by asking questions without knowing its inner workings, including unknown unknowns, and answering "Why is this happening?" It requires that the application be instrumented to emit traces, metrics and logs. An application is properly instrumented when developers do not need to add more instrumentation to troubleshoot an issue.
These are not rival ideas. Monitoring is a use of telemetry. Observability is a property of a system that makes more kinds of questions answerable.
What does monitoring do well?
The SRE book separates black-box monitoring, which is symptom-oriented and represents active problems ("the system isn't working correctly, right now"), from white-box monitoring, which depends on inspecting internals such as logs or HTTP endpoints. White-box monitoring can detect imminent problems and failures masked by retries. It also names four golden signals for user-facing systems: latency, traffic, errors and saturation. If you can measure only four things, measure those.
Good monitoring is about known failures: alert when error rate exceeds a threshold, when a queue backs up, when a disk fills.
Where does monitoring run out?
Constructed example. Checkout latency doubles, but only for customers in one region using one payment method, and only after 6 p.m. Your dashboards show averages that look fine. An alert on overall latency fires late. Nothing in the existing charts splits by region and payment method together.
With rich, high-context telemetry, an engineer can slice by region, payment method and time, follow one slow trace to a retry storm in a downstream call, and find the cause in minutes. The data was emitted before anyone knew they would need that question.
Who owns what?
Monitoring is usually an operations habit: someone owns the alerts, tunes thresholds and answers pages. Observability is closer to a design choice owned by the people who write the code, because the context in telemetry comes from instrumentation inside the application. If developers never add the customer tier or the build version to their spans, no tool can invent it later.
That split explains a common failure. A team buys a powerful analysis tool, points it at services that emit little context, and concludes the tool does not work. The limit was in the data. Treat instrumentation as part of the definition of done for a feature, the same as tests.
Is there a security angle?
Yes. The SRE book mentions that monitoring can supply raw input for analysis of security breaches. The same telemetry that explains a slow checkout can show an unusual spike of failed logins or a service calling something it never called before. Telemetry also holds sensitive data, so apply access controls and redaction as for any log.
How to check or apply this
- Start with monitoring basics: the four golden signals for each user-facing service, with alerts that need action.
- Add context to telemetry: request IDs, region, version, customer tier, without personal data.
- Instrument one critical journey with traces, so a request can be followed across services.
- Connect signals: from an alert, one click to related traces and logs.
- Run a game day. Break something, then see whether a person unfamiliar with the code can find the cause using only telemetry.
- Prune alerts nobody acts on.
- Review what telemetry stores and who can read it.
Quick check
Do I need observability if I already have monitoring?
Monitoring answers known questions. If incidents regularly end with someone adding new logging, you are missing the observability that answers the next unknown one.
Are traces, metrics and logs the same as observability?
They are the signals. Observability is whether those signals, with enough context, let you explain system behavior without new code.
Sources
Last reviewed: 18 October 2026.
