--- title: "Database Performance Degradation Template" description: "Technical template for communicating database latency and performance issues to your engineering-focused audience." author: "openstatus" publishedAt: "2026-01-19" category: "template" faq: - question: "How do I decide between technical and user-friendly messaging?" answer: "Match your communication to your audience. For developer-focused products, include technical details like p95 latency, query times, and specific database components. For general users, focus on impact: 'slower response times' instead of 'elevated connection pool exhaustion.'" - question: "Should I share the root cause of database performance issues?" answer: "Yes, once resolved. Technical audiences appreciate transparency and can learn from your incidents. Share root cause, mitigation steps taken, and preventative measures. This builds trust and demonstrates engineering maturity." - question: "When should I trigger a database performance incident notification?" answer: "Trigger notifications when p95 latency exceeds 2x normal, error rates exceed 1%, connection timeouts occur, or when user reports indicate widespread slowness. Set up automated monitoring alerts to catch these thresholds early." --- Use this template when experiencing database performance issues, elevated latency, or query slowdowns. Ideal for engineering teams and technical stakeholders. ## When to Use This Template - Elevated database latency - Slow query performance - Connection pool exhaustion - Database infrastructure issues ## Template Messages ### Investigating We are experiencing elevated database latency affecting some features. Users may experience slower response times. Our database team is actively investigating and working to restore normal performance levels. ### Identified We have identified the root cause. Our team is implementing a fix. ### Monitoring Database performance improvements have been deployed. Latency is returning to normal levels. We are continuing to monitor. ### Resolved Database performance has been fully restored. All queries are executing at normal speeds. ## Real-World Examples ### GitHub: "Infrastructure update to data stores" **Context**: Data store infrastructure changes **Duration**: ~1.5 hours **Impact**: 1.8% combined failure rate, peaking at 10% **What they did well**: - Quantified impact with specific percentages - Identified multiple affected services - Committed to post-incident RCA (Root Cause Analysis) - Provided precise UTC timestamps **Sample messaging**: "Infrastructure update to data stores caused 1.8% combined failure rate, peaking at 10% across multiple services Jan 15, 16:40-18:20 UTC." ### Fly.io: "Network instability in IAD region" **Context**: Regional infrastructure issue **Approach**: Geographic specificity **What they did well**: - Identified specific region (IAD = Ashburn, Virginia) - Focused on infrastructure layer - Technical but clear naming This demonstrates the value of being specific about location when database issues are region-specific. ## Tips for Technical Communication 1. **Include specific metrics** when you have them (p95 latency, error rates, query times) 2. **Name the layer** - application, database, network, storage 3. **Be technical if your audience is technical** - don't oversimplify for engineers 4. **Quantify impact** - "affecting 2% of queries" is better than "some users" 5. **Share root cause** when resolved - technical teams appreciate learning ## Customization Ideas For **developer audiences**: ``` We are experiencing elevated p95 latency (2.5s vs normal 150ms) on write operations to our primary PostgreSQL cluster. Root cause: Connection pool exhaustion due to long-running transactions from the reporting service. Mitigation: Killed long-running queries, increased pool size from 100 to 150 connections, added query timeouts. ``` For **general users**: ``` We are experiencing slower than normal response times for some features. Our team is working to resolve this quickly. ``` ## Warning Signs to Monitor Watch for these indicators that might trigger using this template: - P95 latency > 2x normal - Error rate > 1% - Connection timeouts - User reports of slowness - Database monitoring alerts