By IT Brew Staff
less than 3 min read
Definition:
Observability, or a clear view into a system or network, is one of the most crucial functions of any IT team, especially as tech stacks become more complicated. Once a team has a holistic view of how something is operating, they can quickly diagnose and solve issues as they arise.
The observability tools that allow this process to happen are often designed to provide IT teams with three crucial elements: metrics, logs, and traces.
Metrics: These quantify system and network performance using a variety of key performance indicators (KPIs), including uptime, app response times, CPU usage, and more. For maximum transparency, IT professionals often rely on dashboards that track these metrics in an easy-to-grasp way. However, they also provide only part of the picture; when discussing IT with other organizational stakeholders, IT professionals often have to put metrics in context to provide an accurate view of system and network health.
Logs: Logs are historical records of discrete events, presented in binary, structured, or plain-text formats. Like metrics, logs can incorporate any number of data types, including event details, error messages, timestamps, IP addresses, and user logins. Observability tools may incorporate logs from systems and devices throughout a network to give IT professionals, data analysts, and others a clear picture. Logs are especially useful in the event of a malfunction or cyberattack, as they can provide some insight into when and how an incident began. Logs are likewise critical for regulatory compliance.
Traces: Traces monitor actions performed by users within a service or network. By mapping how these requests touch on various components, IT professionals can better diagnose any system events or issues; for example, an IT team might use traces to monitor and streamline applications utilizing multiple resources distributed across hybrid architecture. Traces also help teams maintain service-level agreements (SLAs), which can be put at risk if a particular component is failing to operate within specified parameters.
The more complex a system, the harder it is to accurately observe all aspects of it. While the right tools can provide a stream of actionable data to IT professionals, the proliferation of microservices and data silos—combined with alert fatigue from monitoring and observability tools—can also make observability a real challenge.
