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Analyze CPU/Memory Usage Anomaly Causes to Prevent Service and Infrastructure Downtime

UCIndex: UC03

Challenge: Resource Anomalies May Lead to Service Avalanche​

In complex distributed systems, CPU or memory usage anomalies are the most common root causes of failures:

  • CPU consistently maxed out → Requests cannot be scheduled in time, latency continues to rise
  • Memory leaks or spikes → OOM Kill causes services to exit directly
  • Difficult troubleshooting: Traditional monitoring can only show "high resource usage" but cannot quickly answer:
    • Which service's which API consumed a lot of CPU?
    • Is it a memory leak or a transient burst?
    • Is the root cause application logic, increased data volume, or downstream dependency anomalies?

Once troubleshooting is slow, it may trigger service avalanche or even infrastructure downtime.

Solution: eBPF Kernel-Level Analysis and Intelligent Diagnosis​

Syncause integrates host monitoring metrics and process/container monitoring metrics to identify the resource usage ratio of processes/containers on hosts, intelligently determining the preliminary causes of resource anomalies. Based on eBPF technology, by collecting application runtime conditions in the kernel, it answers deeper reasons for resource anomalies:

  • CPU dimension: Captures function-level CPU consumption, scheduling waits, context switches
  • Memory dimension: Tracks memory allocation and release, identifies leaks and high-frequency allocation hotspots
  • System dimension: Combines I/O, lock waits and other data to analyze root causes behind resource usage

When you suspect service resource anomalies, just ask in natural language:

Why is the CPU load on host node-94 so high?

Syncause can quickly answer:

  • "The high CPU load on node-94 is caused by high CPU usage of the payment service, and the high CPU usage of payment is due to massive calls to the API interface /api/pay/cancel"

Effects and Value​

  • Minute-level identification of CPU/memory anomaly root causes — from "resources maxed out" to "which service's which API has problems"
  • Prevent service avalanche — discover and resolve resource bottlenecks before downtime
  • Cross-layer visibility — integrated analysis of application logic, dependency calls, and system resources
  • Natural language interaction — engineers don't need deep stack analysis, just ask one question

Usage Steps​

  1. Open Syncause and start communicating with the SRE Agent
  2. Ask directly in natural language:
Why is the CPU load on host node-94 so high?
  1. Syncause automatically queries and analyzes:
    • Kernel-level CPU/memory data
    • Metrics (Prometheus, etc.) and logs (Loki, etc.)
    • Dependency calls and system context

(Screenshot)

  1. Get root causes and explanatory conclusions:
    • Host CPU usage, container CPU usage
    • Service request volume curves
    • Corresponding chart/log evidence

Experience Syncause immediately: Use it to capture the real root causes of CPU/memory anomalies, prevent issues before they cause downtime, and let the AI Agent become your team's stability guardian.