DevOps teams use observability tools to help them debug applications, uncover root causes of system issues, or follow resource activity to determine malicious security behaviors. In a distributed, cloud-native, or hybrid environment, modern observability meets the need to manage multiple states through telemetry sources known as the three pillars of observability—logs, metrics, and traces.
What is Observability in DevOps?
The three pillars of observability reveal a system’s state, demonstrating how well any or all environments are functioning. Observability tools indicate where issues and errors should be resolved using system data. And, while monitoring is based on a predefined set of data, observability is based on what’s happening now, what happened in the past, and predicting what might happen in the future. In cloud-native environments that emit massive amounts of data, observability tools aim to gain the greatest insight into prioritized issues in the shortest amount of time and cost.
What are the Three Pillars of Observability?
Observability describes the property or state of a single service or across all environments. The three pillars of the observability triad play different roles. DevOps teams that prescribe to continuous delivery-continuous integration achieve observability as a foundational capability with tools that engineers use daily.
Three Pillars of Observability: Logs
Logs are as old as server use. These machine-created text records with metadata are generated from all the applications, endpoints, cloud services, and network infrastructure across the IT environment ecosystem. Logs can be simple to aggregate, but storing large amounts of logs for very long is expensive and unwieldy. And analyzing them with traditional tools is challenging. However, logs provide the most valuable historical records used to determine the root cause of an issue. The beauty of logs is that they capture a wealth of discrete information that’s immutable and timestamped.
As a complement to data logs and a way to make logs more useful in today’s distributed and complex environments, metrics and traces provide an abstraction built on top of logs.
Three Pillars of Observability: Metrics
Metrics provide a numerical representation of data, enabling a longitudinal record over time. When combined with predictive or mathematical modeling, metrics provide useful context around issues and events. Time-series data describe measurements of resource use, runtime, and behavior.
Metrics use simplified log data and don’t increase in correlation with increased traffic or resource provisioning. They can be optimized for longer-term storage and easily queried, making them less costly and more accessible for analysis.
Observability tools or custom-built dashboards visualize metrics to demonstrate events over time. And, because metrics encompass environment KPIs, a tool can trigger real-time alerts when issues or errors are found. The beauty of metrics is that they indicate system health and performance, offering insights or suggested actions from abstracted log data.
Three Pillars of Observability: Traces
The last pillar, traces, rounds out observability capabilities by presenting a picture of how applications interact with the resources they request. Distributed, cloud-native, and containerized systems use microservices-based architectures that rely heavily on distributed tracing. Traces help the team understand when and where errors or issues occur. Teams zero in on individual requests as they move from service-to-service.
Traces are similar to logs but for events. They reveal the path used by a request and the structure of that request. Traces can also be used to troubleshoot specific behaviors within code, giving engineers needed information to hunt down issues or chokepoints across an environment. Like logs, the cost to maintain traces can become concerning.
Leveraging All Three Pillars for a Cloud-Native Environment
The most comprehensive visibility into the state of a complex, distributed environment is possible by combining all three observability tools provides. The observability triad can support real-time alerts, centralized log management, and advanced persistent views. When the relationship among all three data types is visible, DevOps teams can find and resolve issues faster. This helps them maintain a complex environment more efficiently creating stronger and more resilient enterprise architecture.
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