Troubleshooting with SysGauge: Guide to Interpreting Metrics
Overview
SysGauge is a system and performance monitoring tool that collects metrics for CPU, memory, disk, network, processes, and system events. This guide focuses on using SysGauge metrics to identify, diagnose, and resolve common system issues.
Key Metrics and What They Indicate
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CPU Utilization:
- High sustained CPU (80–100%) — indicates CPU-bound workloads, runaway processes, or insufficient CPU capacity.
- Spikes — short-lived tasks or scheduled jobs; correlate with process list to find culprits.
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Per-Core Usage:
- Imbalanced cores — single-threaded processes or CPU affinity settings.
- All cores high — system-wide load or parallel workloads.
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Load Average (if available):
- Load >> CPU count — overloaded system; may indicate CPU contention or heavy I/O wait.
- Load with high I/O wait — disk subsystem bottleneck.
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Memory Usage:
- High used memory with low swap — normal if cache/buffers dominate; monitor free+cache.
- High swap usage — indicates memory pressure; investigate memory leaks or increase RAM.
- Page faults — frequent major page faults signal insufficient RAM.
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Disk I/O and Latency:
- High IOPS with high latency — overloaded storage or fragmented IO patterns.
- High queue length — storage cannot keep up; check RAID, SAN, or virtualization layer.
- Low throughput but high latency — small random I/O; tune filesystem or use faster storage.
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Disk Space:
- Partition near 100% — causes application failures/logging issues; identify large files, rotate logs, or expand volumes.
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Network Throughput and Errors:
- Throughput saturation — upgrade NICs or optimize traffic.
- Packet errors/drops — check duplex/mismatch, cabling, driver issues, or switch problems.
- High retransmits — poor network quality or congestion.
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Process Metrics:
- High CPU or memory per process — identify misbehaving apps; restart, patch, or investigate code.
- Many short-lived processes — possible fork storms; examine service configuration.
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Event Logs and Alerts:
- Correlate SysGauge alerts with system/application logs to find root causes (e.g., kernel messages, application stack traces).
Troubleshooting Workflow (Step-by-Step)
- Confirm the symptom: Use SysGauge to reproduce or capture metric pattern (time, affected metric).
- Correlate metrics: Check CPU, memory, disk, and network concurrently to find where bottleneck appears first.
- Identify responsible process/service: Use process-level views and timestamps matching metric anomalies.
- Check logs: Review system and application logs for errors at the same time window.
- Isolate and mitigate: Restart or throttle offending process, apply temporary resource limits, or reroute traffic.
- Root cause analysis: Evaluate configuration, recent deployments, code changes, or hardware degradation.
- Remediate long-term: Patch software, increase resources, optimize code, tune kernel/filesystem/network settings.
- Verify fix: Monitor metrics post-change to ensure the issue is resolved.
Practical Examples
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Example 1 — High CPU due to a runaway process:
- SysGauge shows CPU at 95% and per-process CPU reveals a single process using 90%. Action: collect stack trace, restart process, analyze recent changes.
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Example 2 — Increased latency during backups:
- Disk I/O spikes and queue length increases during nightly backup window. Action: reschedule backups, use IO throttling, or move backups to less busy periods.
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Example 3 — Memory leak in application:
- Memory steadily increases over days with growing swap use. Action: profile application memory usage, fix leak, restart service, and add alerting for memory growth rate.
Alerts and Thresholds (Suggested Defaults)
- CPU: warn at 75%, critical at 90% sustained >5 minutes.
- Memory: warn when available memory <20%, critical when swap usage rises>10% of RAM.
- Disk usage: warn at 80%, critical at 95% per partition.
- Disk latency: warn when avg I/O >20 ms, critical >50 ms.
- Network: warn at 70% bandwidth, critical at 90%.
Tips for Effective Use
- Enable historical logging to identify trends and intermittent issues.
- Use dashboards to correlate multiple metrics visually.
- Configure alerts with context (thresholds + duration) to avoid alert fatigue.
- Combine SysGauge data with application logs, APM tools, and tracing for deeper diagnosis.
- Regularly review and adjust thresholds based on actual workload patterns.
If you want, I can produce a one-page printable checklist or a recommended SysGauge dashboard layout for troubleshooting.