Part 6: Monitoring & Bottleneck Identification (Performance Testing Revision Cheat Sheet)

 

📌 Purpose

Monitoring during performance testing helps identify bottlenecks that impact system scalability, stability, and responsiveness.

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🎯 Key Monitoring Areas

1. Server-Side Monitoring

   • CPU Usage: High utilization → CPU-bound system.

   • Memory Usage: Memory leaks, garbage collection issues.

   • Disk I/O: Slow reads/writes, storage saturation.

   • Network Utilization: Bandwidth bottlenecks, packet loss.

2. Application-Level Monitoring

   • Thread/Connection Pools: Exhaustion causes errors/timeouts.

   • Garbage Collection (GC) Metrics: Frequent GC pauses (Java/.NET apps).

   • Error Rates: HTTP 5xx, DB errors, API failures.

3. Database Monitoring

   • Query Response Times: Slow SQL queries, missing indexes.

   • Locks & Deadlocks: Concurrent transaction issues.

   • Connection Pool Usage: Exhausted connections → blocked requests.

4. Network & Infrastructure Monitoring

   • Latency & Packet Loss: Impacts distributed systems.

   • Load Balancers: Uneven distribution.

   • Firewall / Proxy Delays.

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🎯 Bottleneck Identification Steps

1. Compare Metrics Across Layers

   • High CPU but low DB → app server issue.

   • Low CPU but high DB latency → database bottleneck.

2. Use APM & Monitoring Tools

   • Dynatrace, AppDynamics, New Relic, Datadog, Prometheus + Grafana.

3. Correlate With Test Timeline

   • Match spikes in response time with resource usage graphs.

4. Confirm Root Cause

   • Validate with logs, profiling, or deep-dive analysis.

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🛠️ Deliverables

• Monitoring dashboards (real-time + historical).

• Identified bottlenecks (CPU, DB, memory, network).

• Performance issue hypothesis for further debugging.