Telemetry Cost Optimization: Metrics, Logs, and Traces at Scale

Telemetry is observability's fuel — most organizations burn far more than they need. The goal: same or better signal quality at 40-60% lower cost.

The Cost Pyramid

Logs dominate at 50-65% of total spend. Metrics at 20-30%. Traces at 10-20%.

Pillar 1: Log Optimization

Pipeline filtering — drop health checks and trace-level logs before ingestion (5-15% savings). Sampling — keep all errors, sample info at 10% (50-90% savings for sampled sources). Retention tiering — errors 30d hot, debug 3d, audit cold for years (40-60% storage savings).

Pillar 2: Metrics Optimization

Label pruning — drop instance from aggregated metrics for 100x reduction. Recording rules — pre-aggregate for dashboards, drop raw high-cardinality data. Collection intervals — 60s for slow-changing metrics vs 10s default = 6x reduction.

Pillar 3: Trace Optimization

Tail sampling — keep errors and slow traces, sample rest at 5% (50-90% savings). Span-to-metrics — extract RED metrics before sampling so aggregate accuracy is preserved. See Head vs Tail Sampling and Span Metrics Connector.

Combined Impact

Technique	Savings
Drop health check logs	5-15%
Sample debug logs	20-35%
Tier retention	30-50% storage
Prune cardinality	20-40%
Increase intervals	40-60%
Tail sampling	50-90%

Combined: 40-60% total cost reduction with improved signal-to-noise.

Optimization stack rank (by ROI × effort)

Rank	Action	Typical savings	Effort
1	Drop health-check / heartbeat logs	10–25% logs	Low
2	Label allowlists on HTTP metrics	20–60% metrics	Medium
3	Tail-sample traces (keep errors)	40–70% APM	Medium
4	Reduce log retention tiers	15–30% storage	Low
5	Vendor migration	20–40% total	High

Run ranks 1–4 before evaluating rank 5 — most teams never need a migration to hit budget.

What to do this week

• [ ] Complete the 7-point waste checklist
• [ ] Deploy one collector drop rule for health-check logs
• [ ] Audit DEBUG-level logging in production
• [ ] Re-run calculator after changes

Sources & further reading

• Observability cost reduction guide — deep cut strategies
• OpenTelemetry Collector processors — filter and batch at the edge

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Related Reading

• Reducing Log Ingestion and Storage
• Managing Metrics Cardinality
• Cost-Effective Distributed Tracing
• Telemetry Data Lifecycle Management
• Observability Cost Reduction Playbook

Use the SignalCost Calculator → to model these scenarios with your own numbers.