What Is Observability? Understand Your System with Logs, Metrics and Traces
Observability is the ability to understand why your system is misbehaving — not just that something is wrong.
Observability helps you debug issues, trace errors, and identify bottlenecks across distributed systems using telemetry data: logs, metrics, and traces.
What is Observability in Software?
Observability is the ability to understand what's happening inside a system based on the data it produces — such as logs, metrics, and traces.
It answers not just “is my service up?”, but also:
- Why is it slow?
- What caused that error?
- Which services were affected?
Why Is Observability Important?
Without observability, you're flying blind.
Modern applications are:
- Distributed (microservices, containers, cloud)
- Dynamic (frequent deployments, autoscaling)
- Complex (many dependencies)
Observability helps you:
- Debug production issues faster
- Detect and fix performance bottlenecks
- Understand system behavior over time
- Improve reliability and customer experience
How Is Observability Different From Monitoring?
| Feature | Monitoring | Observability |
|---|---|---|
| Scope | Known problems and thresholds | Unknown issues and root cause analysis |
| Data type | Metrics only | Metrics, logs, traces |
| Approach | Reactive (alerts) | Proactive (understanding and debugging) |
| Ideal for | Uptime checks | Complex, distributed systems |
What Are the Three Pillars of Observability?
Observability is often described using three core types of telemetry:
- Logs – Text records of events, warnings, and errors
- Metrics – Numeric data such as response times or memory usage
- Traces – End-to-end visibility into request paths across services
Each of these helps you answer different types of questions during troubleshooting.
Is Observability the Same as Telemetry?
Not exactly.
- Telemetry is the data (logs, metrics, traces).
- Observability is what you do with that data — to understand the system.
Think of telemetry as the raw materials, and observability as the insight you gain from processing them.
What Tools Are Used for Observability?
Some of the most popular tools include:
- Uptrace – Fast, open source observability platform for traces, logs, and metrics
- Grafana – For dashboards and metrics
- Jaeger – For distributed tracing
- Prometheus – For collecting time-series metrics
- Elastic Stack – For log management
🟢 Want a lightweight APM with full observability support? Try Uptrace.
What Problems Does Observability Solve?
- Tracking down intermittent bugs
- Diagnosing slow performance
- Understanding cascading failures across services
- Measuring the impact of deployments
- Answering questions like: "What changed recently?"
How Do I Start With Observability?
Start with this 3-step approach:
- Instrument your app using OpenTelemetry SDKs
- Collect telemetry data (logs, metrics, traces)
- Analyze it with an observability tool like Uptrace
What Is the Difference Between Observability and APM?
| Observability | APM (Application Performance Monitoring) | |
|---|---|---|
| Scope | Full system understanding | Application-centric performance tracking |
| Data | Logs, metrics, traces | Mostly metrics and predefined transactions |
| Flexibility | High (custom telemetry possible) | Often limited to vendor defaults |
| Example tool | Uptrace | Datadog, New Relic |
Summary
Observability is not just about detecting problems — it’s about understanding them.
It gives you the tools to answer why something is wrong and not just what is wrong.
FAQ
- What is observability in simple terms? Observability is the ability to understand the internal state of a system by analyzing the data it produces, such as logs, metrics, and traces.
- How is observability different from monitoring? Monitoring typically focuses on known issues with predefined alerts, while observability enables you to investigate unknown problems by providing deeper insights through multiple data types.
- What are the three pillars of observability? Logs, metrics, and traces form the three pillars, each offering different perspectives for diagnosing and understanding system behavior.
- Can observability work without traces? Traces provide end-to-end context but observability can start with logs and metrics; however, full observability requires all three.
- What tools help implement observability? Popular tools include Uptrace, Grafana, Jaeger, Prometheus, and Elastic Stack.
You may also be interested in:
Table of Contents