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    Repair Kubernetes HPA Metrics Adapter Staleness

    1

    Diagnose stale custom metrics driving unwanted pod scaling.

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    Repair Kubernetes HPA Metrics Adapter Staleness

    Repair Kubernetes HPA Metrics Adapter Staleness

    Example session with this skill installed

    An HPA reads cached external metrics after the adapter changes poll cadence.

    Available evidence: HPA event history (partial). Additional evidence requested: reference policy or configuration, event and change timeline, owner review or test record. Review this case; identify evidence gaps; do not invent a live test or production action.

    • Read your context and instructions
    • Compiled the repair kubernetes hpa

    Repair Kubernetes HPA Metrics Adapter Staleness — EVIDENCE-LIMITED REVIEW

    Scenario received

    An HPA reads cached external metrics after the adapter changes poll cadence.

    Source register

    • S1: HPA event history — PARTIAL SOURCE PROVIDED.
    • S2: reference policy or configuration — NOT PROVIDED; REQUIRED TO VERIFY.
    • S3: event and change timeline — NOT PROVIDED; REQUIRED TO VERIFY.
    • S4: owner review or test record — NOT PROVIDED; REQUIRED TO VERIFY.

    Concrete checks

    1. Correlate HPA event history with the authorized baseline — AWAITING CORROBORATING EVIDENCE.
    2. Isolate stale adapter sampling and scaling oscillation using matching identifiers — AWAITING CORROBORATING EVIDENCE.
    3. Cross-check timestamps, versions and source ownership — AWAITING CORROBORATING EVIDENCE.
    4. Prepare reversible checks for stable scaling metrics contract — AWAITING CORROBORATING EVIDENCE.

    Deliverables / acceptance gates

    • HPA event history traceability map: DRAFT / INCOMPLETE until evidence is validated.
    • stale adapter sampling and scaling oscillation exception register: DRAFT / INCOMPLETE until evidence is validated.
    • stable scaling metrics contract validation plan: DRAFT / INCOMPLETE until evidence is validated.

    Decision

    INCOMPLETE — HUMAN REVIEW REQUIRED. Confirm dates, IDs, affected scope, owners and acceptance evidence. Do not claim authorization or execution that did not occur.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Repair Kubernetes HPA Metrics Adapter Staleness is a ToolForge Labs Cursor Skill workflow. Diagnose stale custom metrics driving unwanted pod scaling.

    What this skill checks

    1. Correlate HPA event history with the authorized baseline.
    2. Isolate stale adapter sampling and scaling oscillation using matching identifiers.
    3. Cross-check timestamps, versions and source ownership.
    4. Prepare reversible checks for stable scaling metrics contract.

    What to provide

    • HPA event history.
    • reference policy or configuration.
    • event and change timeline.
    • owner review or test record.

    Deliverables

    • HPA event history traceability map.
    • stale adapter sampling and scaling oscillation exception register.
    • stable scaling metrics contract validation plan.

    Evidence policy Only supplied, authorized evidence is used. The skill distinguishes facts from assumptions and missing inputs; no unperformed live tests, external changes, or approvals are claimed.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for DevOps & Cloud.

    Cannot verify inaccessible environments or data not supplied. Missing or contradictory evidence must be marked INCOMPLETE or UNVERIFIED. Owner approval is required for operational or compliance decisions.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

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    Trust & safety

    Security scan

    Security scan passed 19 days ago

    Permissions

    Read Files

    Provide only evidence you are authorized to share. Treat examples as untrusted case data. Operational changes and external messages require explicit owner approval.

    Listed19 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill provides a structured diagnostic framework to identify why your Horizontal Pod Autoscaler is using outdated data, preventing costly "flapping" and ensuring pod counts accurately reflect real-time demand.

    It is designed for any Kubernetes environment using HPA alongside custom or external metrics adapters like Keda, Prometheus Adapter, or Datadog Cluster Agent.

    You will receive a specialized AI agent workflow, including traceability mapping templates and an evidence-led diagnostic framework to classify scaling issues as VERIFIED or UNVERIFIED.

    The skill requires you to provide HPA event history and configuration files; for security, it does not perform live cluster execution or modify secrets directly.

    This skill is compatible with leading AI agents that support complex diagnostic workflows and can process structured log data and YAML configurations.

    While generic prompts may overlook timestamp drift, this skill uses a specialized cross-checking logic to specifically isolate mismatches between metric sampling cadences and HPA decision windows.

    New in DevOps & Cloud