Observability is a superset of tools and techniques to understand how a system works, exploring “knowns” and “unknowns” in the systems. Monitoring involves tracking and measuring structured data.

## **Log Aggregation**

- _log forwarder_ - software to collect logs from different data sources, transform logs if required and send those to a _log aggregator_

- _log aggregator_ - software to aggregate, store and present logs

**Process of log aggregation**

- collect logs from multiple sources in different formats. Recommended to have a standardised log format.

- standardise - if logs have different formats, at this step you need to align logs to one format

- verify - check, that logs are valid, parsable, and contain all data.

- consolidate - gather logs to one place, where you can analyse logs.

## **Distributed Tracing**

Tracking multiple services calls for the same business operation in the distributed system. Usually implemented by adding a correlation id into the message envelope.

## **Metrics Aggregation**

Similar to logs aggregation. The difference is, that metrics are usually numbers giving the insights about system characteristics/resources/performance.

## **Types of context in logs**

- Temporal context - context of how an object changes in time.

- Relative context - context of how an object changed in relation to other objects.

- Relation context - context about dependencies and defendants in the system of a logged action.

- Proportion context - gives insights about the scope of action in the logs.

## **OpenTelemetry**

Open source observability framework. It provides libraries, conventions, APIs and SDKs to have observability on your system. It is neither an observability backend nor an observability database.

[_opentelemetry.io_](https://opentelemetry.io/docs/)