What Periscope tracks
Periscope calculates CFR from your deployment events. The dashboard shows:- Overall failure rate as a percentage
- Total deployments and failed deployments count
- Failure rate by service to identify which services are most failure-prone
- Recent failed deployments with details (service, time, pipeline URL)
DORA benchmarks
| Level | Benchmark |
|---|---|
| Elite | 0-5% |
| High | 5-10% |
| Medium | 10-15% |
| Low | 15%+ |
How it is calculated
status: "failure" against the total number of production deployments (any terminal status) in the selected time range.
The per-service breakdown applies the same formula scoped to each service name in your deployment data.
Interpreting the data
- Low CFR with high deployment frequency is the ideal state — you are shipping often and reliably.
- High CFR with low deployment frequency is the most dangerous pattern — infrequent, large deployments that often break.
- One service with high CFR while others are healthy suggests a problem specific to that service’s test coverage, complexity, or deployment process.
- CFR trending upward may indicate degrading test quality, increasing system complexity, or a growing gap between development and production environments.
Reducing change failure rate
- Ship smaller changes more frequently (smaller blast radius)
- Improve pre-merge CI — catch failures before code reaches production
- Add canary or staged rollout strategies
- Implement feature flags to decouple deployment from release
- Review failed deployments in Periscope to identify patterns
MCP tool
Query change failure rate from your AI coding assistant:Mean time to recovery
When failures happen, MTTR measures how fast you recover.