Monitoring and observability are essential for understanding the performance and health of an organization's systems and applications. Monitoring provides real-time data on the performance and availability of systems, while observability allows for deeper understanding of the underlying systems and the ability to diagnose and troubleshoot issues.
Metrics are measurements of a specific aspect of a system, such as CPU usage, memory usage, or response time. These metrics can be collected and analyzed in real-time to understand the current state of a system and identify any potential issues.
Logs are records of events that occur within a system, such as error messages, system messages, and application logs. These logs can be analyzed to troubleshoot issues and understand the behavior of a system over time.
Tracing is a way to track the flow of a request through a distributed system, providing insight into how different components are interacting and performing. This can be useful for identifying bottlenecks and errors.
Alerting is the process of setting up notifications or automated actions when certain conditions are met, such as a system going down or a threshold being exceeded. This allows for proactive monitoring and faster resolution of issues.
Dashboards provide a visual representation of metrics, logs, and other data, making it easier to understand and analyze the information. Dashboards can be customized to show the most important information for a specific system or use case.
This is the process of identifying unusual or abnormal behavior in the system, it could be based on machine learning algorithms or statistical analysis, it helps to detect and alert on potential issues before they become critical.
This is a set of procedures and actions that are triggered automatically when an issue or incident is detected, this can include sending notifications, triggering automated fixes, and escalating to a human operator.