The three pillars of observability
The three pillars of observability are metrics, logs, and traces — three complementary data types that together let you understand a system's internal state from its outputs.
The three pillars, defined
The "three pillars" is a popular framing for the foundational telemetry types of observability. Metrics are aggregated numeric measurements over time, logs are timestamped records of discrete events, and traces follow a single request as it travels across services. Each answers a different kind of question, and you usually need all three to go from a symptom to a root cause.
It's worth being honest about the model: "three pillars" is a useful starting point, but many practitioners now consider it incomplete. Events and continuous profiles are increasingly treated as first-class signals, and the deeper idea — that observability is about asking new questions of your data without shipping new code — matters more than the count of pillars.
Each pillar's strengths and limits
The pillars complement each other precisely because each is good at what the others are bad at. Knowing where each shines tells you which to reach for.
Metrics — cheap, aggregate, what
Metrics are compact numbers — request rate, error rate, CPU — ideal for dashboards, alerting, and trends. They tell you something is wrong cheaply, but not which request or why.
Logs — detailed, discrete, why
Logs capture rich, event-level detail — the exact error, the parameters, the message. They're invaluable for root cause but high-volume and costly to store and search at scale.
Traces — causal, cross-service, where
Traces follow one request across every service it touches, exposing which hop is slow or failing. They're essential in distributed systems but require consistent instrumentation to be complete.
How they combine
A typical flow: a metric alert says error rate spiked, a trace shows which service is failing, and logs from that service reveal the exact exception. Each pillar hands off to the next.
Beyond three pillars
The model is increasingly seen as incomplete. Events and continuous profiling are now common additional signals, and wide structured events are argued by some as a better foundation than three separate stores.
Why the pillars matter
No single telemetry type is enough on its own. Metrics alert you cheaply but can't explain a failure; logs explain it but are expensive to keep at the breadth metrics cover; traces connect the dots across services but need the other two to fill in the detail. The pillars matter because each covers the others' blind spots.
But treat the framing as a model, not a law. The real test of observability isn't whether you collect exactly three data types — it's whether your data lets you answer questions you didn't anticipate when an unfamiliar problem appears. That's why correlation across signals usually matters more than which pillars you happen to call them.
The pillars in AllStak
AllStak brings the three pillars into one platform: infrastructure and application metrics, log management, and distributed tracing, alongside error tracking. Because they share a home, you can move from a metric alert to the trace to the logs without stitching together separate tools or bills.
Keeping the signals together is what makes correlation practical — the part that, in the end, matters more than how many pillars you count.
Three pillars FAQ
What are the three pillars of observability?
Metrics, logs, and traces. Metrics are aggregated numbers over time, logs are detailed records of discrete events, and traces follow a single request across services.
How do the three pillars work together?
A metric alert tells you something's wrong, a trace shows which service is responsible, and logs from that service reveal the exact cause. Each pillar narrows the search the next one completes.
Is the three-pillars model complete?
It's a useful model but increasingly seen as incomplete. Many teams now add events and continuous profiling as first-class signals, and some argue wide structured events are a stronger foundation than three separate stores.
Do I need all three pillars?
For non-trivial systems, yes — each covers blind spots the others have. The real goal is correlating them so you can answer unexpected questions, which is easier when they live in one platform.
Explore more
Metrics, logs, and traces in one place
AllStak brings the three pillars together with error tracking so you can correlate signals instead of juggling tools. Start free.