Huawei Cloud CCE Pod Failure Diagnoser

Overview

This skill diagnoses single-resource Pod failures in Huawei Cloud CCE clusters, including CrashLoopBackOff, ImagePullBackOff, OOMKilled, Pending, Evicted, and frequent restart storms. It confirms scope, then builds an evidence chain through Kubernetes Pod status, container state, Events, previous/current logs, and optional metrics.

Architecture: python3 scripts/huawei-cloud.py dispatcher → Huawei Cloud Python SDK + Kubernetes client → Pod status, Events, logs, metrics

Related Skills:

• huawei-cloud-cce-workload-failure-diagnoser - Workload rollout, stuck rolling updates, unavailable replicas
• huawei-cloud-cce-node-failure-diagnoser - Node health, resource pressure, NPD events
• huawei-cloud-cce-network-failure-diagnoser - Network connectivity, DNS, ELB diagnosis
• huawei-cloud-cce-storage-failure-diagnoser - PVC/PV mount, storage provisioning failures
• huawei-cloud-cce-root-cause-analyzer - Cross-domain root cause analysis and reports
• huawei-cloud-cce-auto-remediation-runner - Remediation actions (scale, resize, drain, etc.)

Capabilities:

• One-shot Pod failure diagnosis with top causes (huawei_pod_failure_diagnose)
• Read Pod phase, reason, container state, last state, restart count, owner, node (huawei_get_cce_pods)
• Fetch Pod current and previous container logs (huawei_get_pod_logs)
• Query Kubernetes Events for a namespace or cluster (huawei_get_cce_events)
• View Pod CPU/memory metrics and TopN metrics (huawei_get_cce_pod_metrics, huawei_get_cce_pod_metrics_topN)
• Comprehensive workload diagnosis (huawei_workload_diagnose, huawei_workload_diagnose_by_alarm)
• Generate structured diagnosis report (huawei_generate_diagnosis_report)

Typical Use Cases:

• "My Pod is in CrashLoopBackOff, find the root cause"
• "Pod keeps restarting, check previous logs"
• "Pod stuck in Pending, why can't it schedule?"
• "ImagePullBackOff error, check events and registry access"
• "Pod was OOMKilled, show memory metrics"
• "Pod was Evicted, check node pressure"
• "List all abnormal Pods in a namespace"
• "Show Pod resource usage for the last hour"

Prerequisites

1. Python Dependencies

• Python 3.8+ with huaweicloudsdkcce, huaweicloudsdkcore, kubernetes packages
• Run environment check before first use (see Verification section)

2. Credential Configuration

• Valid Huawei Cloud credentials (AK/SK mode)
• Security Rules:
  • 🚫 Never expose AK/SK values in code, conversation, or commands
  • 🚫 Never use echo $HUAWEI_AK or echo $HUAWEI_SK to check credentials
  • ✅ Use environment variables: HUAWEI_AK, HUAWEI_SK, HUAWEI_REGION
  • ✅ Prefer IAM users over root account for cloud operations
  • ✅ Enable MFA for sensitive operations

Configuration Method (Environment Variables Only):

export HUAWEI_AK=<your-ak>
export HUAWEI_SK=<your-sk>
export HUAWEI_REGION=cn-north-4

⚠️ Important Security Notes:

• Never commit credentials to version control
• Use IAM users with minimal required permissions
• Enable MFA for sensitive operations
• Rotate AK/SK regularly

3. IAM Permission Requirements

Permission Failure Handling:

1. When any command fails due to IAM permission errors, display the required permission list
2. Guide the user to create a custom policy in the IAM console and grant authorization
3. Pause execution and wait for user confirmation that permissions have been granted

Core Commands/Tools

All commands use the Python dispatcher script: python3 scripts/huawei-cloud.py <action> <key=value>...

1. Primary Diagnosis — huawei_pod_failure_diagnose

One-shot action that fetches Pod status, Events, logs, and optional metrics, then outputs top causes.

python3 scripts/huawei-cloud.py huawei_pod_failure_diagnose \
  region=cn-north-4 cluster_id=<cluster-id> namespace=default \
  pod_name=my-app-xxx workload_name=my-app \
  include_logs=true include_metrics=false \
  tail_lines=80 hours=1 max_pods=20 event_limit=500

Parameters:

• pod_name or workload_name or labels — at least one targeting parameter recommended
• include_logs=true — fetch previous and current container logs (default: true)
• include_metrics=true — fetch Pod CPU/memory metrics (default: false)
• tail_lines — number of log tail lines (default: 80)
• hours — metrics lookback window in hours (default: 1)
• max_pods — max Pods to analyze per workload (default: 20)

2. Read-Only Evidence — Raw Data Retrieval

# List Pods with phase, reason, container state, restart count, node
python3 scripts/huawei-cloud.py huawei_get_cce_pods \
  region=cn-north-4 cluster_id=<cluster-id> namespace=default labels=app=my-app

# Fetch Pod logs (previous=true for CrashLoopBackOff/OOMKilled)
python3 scripts/huawei-cloud.py huawei_get_pod_logs \
  region=cn-north-4 cluster_id=<cluster-id> pod_name=my-app-xxx \
  namespace=default container=app previous=true tail_lines=100

# Query Kubernetes Events
python3 scripts/huawei-cloud.py huawei_get_cce_events \
  region=cn-north-4 cluster_id=<cluster-id> namespace=default limit=500

# View Pod CPU/memory metrics
python3 scripts/huawei-cloud.py huawei_get_cce_pod_metrics \
  region=cn-north-4 cluster_id=<cluster-id> pod_name=my-app-xxx \
  namespace=default hours=1

# TopN Pod metrics by CPU or memory
python3 scripts/huawei-cloud.py huawei_get_cce_pod_metrics_topN \
  region=cn-north-4 cluster_id=<cluster-id> namespace=default \
  top_n=10 hours=1

3. Comprehensive Diagnosis — Workload-Level

# Workload-level diagnosis (Pods + rollout + metrics)
python3 scripts/huawei-cloud.py huawei_workload_diagnose \
  region=cn-north-4 cluster_id=<cluster-id> \
  workload_name=my-app namespace=default hours=6

# Workload diagnosis triggered by alarm
python3 scripts/huawei-cloud.py huawei_workload_diagnose_by_alarm \
  region=cn-north-4 cluster_id=<cluster-id> \
  alarm_info=<alarm-json> hours=6

# Generate structured diagnosis report
python3 scripts/huawei-cloud.py huawei_generate_diagnosis_report \
  region=cn-north-4 cluster_id=<cluster-id>

Parameter Reference

Common Parameters

huawei_pod_failure_diagnose Parameters

*At least one of pod_name, workload_name, or labels should be provided for targeted diagnosis.

huawei_get_pod_logs Parameters

Output Format

See Output Schema for the complete JSON response structure.

Key output fields:

• success — boolean, true if diagnosis completed
• summary.diagnosis_status — abnormal, no_known_failure_detected, or no_matching_abnormal_pods
• pods[].issues[].type — failure type: CrashLoopBackOff, ImagePullBackOff, OOMKilled, PendingScheduling, PendingStorage, Evicted, FrequentRestart, PodNotReady
• pods[].issues[].confidence — confidence score (0-1)
• top_causes — ranked top causes with evidence and recommendations
• recommended_actions — read-only next checks; mutation actions deferred to huawei-cloud-cce-auto-remediation-runner

Verification

1. Run python3 scripts/huawei-cloud.py huawei_get_cce_pods region=cn-north-4 cluster_id=<cluster-id> to verify cluster connectivity
2. Run python3 scripts/huawei-cloud.py huawei_get_cce_events region=cn-north-4 cluster_id=<cluster-id> limit=10 to verify Event query works
3. Run python3 scripts/huawei-cloud.py huawei_pod_failure_diagnose region=cn-north-4 cluster_id=<cluster-id> namespace=default on a healthy namespace and confirm diagnosis_status=no_known_failure_detected

Best Practices

1. Use huawei_pod_failure_diagnose as first choice — it aggregates Pod status, Events, logs, and metrics in one call
2. Check previous logs for CrashLoopBackOff/OOMKilled — set previous=true to see the last crashed container output
3. Prioritize Events for ImagePullBackOff — container logs typically don't exist for image pull failures; read Events first
4. Escalate to related skills — Pending scheduling → node/autoscaling skills; Pending storage → storage diagnosis; workload-level → huawei-cloud-cce-workload-failure-diagnoser
5. Scope with namespace — always provide namespace to reduce result noise
6. Sanitize output — the dispatcher automatically sanitizes logs; never copy raw passwords, tokens, or AK/SK from log excerpts

Reference Documents

Notes

• This skill does not scale, delete, or restart workloads or nodes — mutation actions must be handed off to huawei-cloud-cce-auto-remediation-runner
• All diagnostic actions are read-only — no side effects on cluster state
• Log excerpts are sanitized — suspected passwords, tokens, AK/SK, and Authorization headers are redacted in output
• AK/SK must never be hardcoded — use environment variables only
• The Python dispatcher script (scripts/huawei-cloud.py) is the only execution method — do not use hcloud CLI or direct API calls for Pod diagnosis
• For Pending Pods with FailedScheduling, consider switching to huawei-cloud-cce-node-failure-diagnoser or huawei-cloud-cce-autoscaling-diagnoser

Common Pitfalls