Dashboards are no longer enough.
In 2026, SREs aren’t just looking at graphs - they’re encoding reliability logic directly into queries, alerts, and pipelines.
This shift is called Observability as Code (OaC).
Why Dashboards Fall Short at Scale
Traditional dashboards:
- Are manually curated
- Drift over time
- Don’t enforce correctness
- Visualize symptoms, not intent
- Fail during incidents when you need precision
When infrastructure is ephemeral and distributed, static dashboards become screenshots of the past.
What “Observability as Code” Really Means
Observability as Code means:
- Treating queries, alerts, and SLOs as versioned code
- Storing PromQL, LogQL, TraceQL in Git
- Reviewing observability changes via pull requests
- Automatically validating observability logic in CI/CD
If it’s not version-controlled, it’s not reliable.
Why PromQL Becomes the Source of Truth
PromQL expresses intent, not presentation.
Examples:
- Burn rate detection
- Error budget consumption
- Latency SLO breaches
- Saturation and backpressure patterns
- Cardinality-safe aggregation
One PromQL rule can power:
- Alerts
- SLO dashboards
- Automation triggers
- Root-cause correlation
Dashboards just render the result.
SRE Use Cases That Demand Code, Not Clicks
Modern SRE teams use PromQL to:
- Detect slow burns before alerts fire
- Encode service reliability objectives
- Correlate infra + app + traffic signals
- Reduce alert noise with math, not heuristics
- Automate incident classification
These cannot be click-built consistently.
How CI/CD Changes Observability
With OaC:
- Observability breaks builds when queries are wrong
- Alert logic is tested before deploy
- Changes to metrics schemas fail fast
- New services ship with SLOs by default
Observability becomes part of the delivery pipeline, not an afterthought.
Beyond Metrics: Logs & Traces as Code
The same model applies to:
- LogQL for error patterns
- TraceQL for latency breakdowns
- Event correlation logic
- Deployment-aware observability
SREs now write cross-signal queries instead of clicking across tools.
Where KubeHA Fits
KubeHA turns Observability as Code into actionable intelligence by:
- Correlating PromQL, LogQL, TraceQL outputs
- Connecting telemetry with Kubernetes events & config changes
- Explaining results using LLM reasoning
- Surfacing why signals changed - not just that they changed
Queries find the signal. KubeHA provides the story.
🔚 Bottom Line
Dashboards don’t scale. Code does.
In 2026, SREs:
- Write PromQL to encode reliability
- Version observability logic
- Automate detection and response
- Use dashboards only as a visualization layer
Observability as Code isn’t advanced - it’s the minimum bar for modern reliability engineering.
👉 Follow KubeHA for:
- Production PromQL patterns
- Observability automation
- Cross-signal correlation
- LLM-assisted RCA
- Kubernetes reliability intelligence
Experience KubeHA today: www.KubeHA.com
KubeHA's introduction, 👉 https://www.youtube.com/watch?v=PyzTQPLGaD0
Top comments (0)