From SLO alert to the code path, in one query
Trace metrics back to the lines that produce them. Wire CodeAlive into Grafana, Prometheus, or your chaos platform over MCP.
Owning reliability for systems you didn't build
- SREs own reliability for systems they didn't build and don't fully understand.
- Runbooks describe symptoms, not actual code behavior.
- Capacity planning requires understanding that lives only in developer heads.
- Chaos engineering findings are hard to trace back to code.
- SLO violations require developer involvement to diagnose.
Read the code, not just the dashboard
Find the failure mode before chaos engineering finds it for you. MCP plugs CodeAlive into the rest of your observability stack.
What you can ask the system
Reliability Analysis
Surface failure modes in the checkout flow, locate where timeouts are not properly handled, and predict what happens if the cache becomes unavailable.
Capacity Planning
Enumerate database queries run during checkout, understand memory allocation strategy per service, and check batch sizes used in data processing.
Dependency Understanding
Map external service dependencies for the platform, find which circuit breakers are implemented, and review how services handle downstream failures.
SLO Investigation
Trace what code paths affect a given SLI, where retries are implemented that could affect a latency SLO, and what logging exists for tracking response times.
MCP Observability Integration
Connect CodeAlive to Grafana, Prometheus, Nobl9, or chaos platforms via MCP. Enrich SLO alerts and chaos findings with code context automatically.
How SREs use CodeAlive
- 1
Proactive Reliability Review
Audit error handling in the critical path. Identify missing circuit breakers, retries, and fallbacks, and find hardcoded timeouts that could cause cascading failures.
- 2
SLO Violation Investigation
When an SLO alert fires, immediately understand what code affects it. Trace from metrics to code paths automatically.
- 3
Chaos Engineering Context
Before running chaos experiments, ask what happens if service X is unavailable. Validate expected failure modes against actual implementation and find untested scenarios.
- 4
Runbook Generation
Auto-generate runbooks from actual code behavior. Keep runbooks in sync with code changes and provide code context within runbook steps.
What changes for reliability engineering
- From SLO alert to the code path that affects it, automatically.
- Proactively identify reliability risks before incidents.
- More accurate capacity planning with code-grounded analysis.
Find the failure mode before chaos does
Connect your observability stack to the code that produces the metrics.