Monitoring keeps an eye on known metrics, logs, and alarms depending on set scenarios and gives you a clear idea of what's going on in your systems.

• Observability takes a step further by letting you figure out why problems happen by comparing data from logs, metrics, and traces. Monitoring asks a simple question: Is my system working? Observability asks, Why isn't my system working? and also focuses on How can I prevent this from happening again? For full visibility, modern systems need both methods.

• DORA measures (Deployment Frequency, Lead Time, Change Failure Rate, and MTTR) are conventional ways to measure how well software is delivered.
• Companies that use DORA measurements reach their organizational performance targets twice as quickly and get their products to market 50% faster.
• These indicators serve as an effective way that lets you find problems in your delivery pipeline, compare your performance to industry norms, and plan ways to make things better. Elite performers deploy many times a day with a failure rate of less than 15% and a recovery time of less than an hour.

The monitoring and observability stack is built on open source tools such as Prometheus, Grafana, OpenTelemetry, and Loki. You keep the data and configuration in open formats, so the stack can be extended or migrated without renegotiating a vendor license.

It means anomaly detection and root cause correlation are built into the pipeline from the start, using models trained on your metrics, logs, and traces, rather than AI added on top of static dashboards after the fact.