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    Ad Service Manual Garbage Collection

    Failure scenario

    This performance issue is triggered by enabling the adManualGc flag in the Flagd config (ConfigMap on Kubernetes) or Flagd UI.

    When activated, this flag forces manual garbage collection in the ad service.

    Root Cause Analysis by Coroot

    Coroot AI RCA analysis of ad service manual garbage collection showing root cause identification and recommendations

    How it works

    1. Anomaly detection

    Coroot identified an anomaly in the frontend-proxy service, detecting increased latency and failed requests.

    2. eBPF-based metrics correlation

    Using eBPF metrics, Coroot connected the frontend-proxy’s performance issues to the frontend service, and finally to the ad service.

    3. Understanding the cause

    The increase in the ad service latency correlates with JVM safepoints caused by garbage collection activity

    Results

    2/3
    Detection of the problematic service:

    Coroot identified the ad service as the source of the issue.

    Immediate fixes provided:

    Partial. Increasing the memory limit might help in real scenarios, but the best solution is to profile the application's memory usage and address the root cause.

    Additional details:

    Coroot did not detect feature flag involvement because it was missing from the trace attributes, but it did identify JVM GC pressure as a contributing factor.

    LLM Usage Details

    Model: Anthropic Claude Sonnet 4 (claude-sonnet-4-20250514)
    Token usage: 18,265 input tokens • 630 output tokens
    Estimated cost: ~$0.06 USD

    Based on $3 per 1M input tokens, $15 per 1M output tokens

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