Common Observability Issues

Overview

Observability programs often fail due to weak signal quality, poor ownership, and inconsistent instrumentation.

Frequent Issues

• Missing trace context propagation
• Unbounded metric cardinality
• Inconsistent log schemas
• Alert fatigue from noisy rules
• Dashboards without business relevance

flowchart LR
    A[Poor Instrumentation] --> B[Low Signal Quality]
    B --> C[Slow Incident Response]
    C --> D[Higher Downtime Risk]

Practical Example

A service fleet emitted request metrics with raw user identifiers as labels, causing high cardinality and scraping instability.

Production Example

Teams typically resolve recurring issues by introducing observability standards, CI linting for telemetry, and ownership metadata for dashboards and alert rules.

Common Pitfalls

• Treating observability as tooling-only work
• No review process for new telemetry fields
• Delaying instrumentation until after incidents

Key Takeaways

• Signal quality and governance are core observability concerns.
• Standardization improves cross-team troubleshooting speed.
• Early instrumentation reduces operational blind spots.