Huawei Cloud Cce Ops Report Generator

Huawei Cloud CCE Ops Report Generator

⚠️ Execution Method (Must Read): This skill executes queries via the local Python dispatcher script. Using hcloud, openstack, or other CLI tools or direct API calls is prohibited.

• The dispatcher script is located at scripts/huawei-cloud.py within the skill directory
• All scripts and environment check scripts are inside the skill package. You must use skill action=exec to execute them. Do not run them directly in a shell.
• Do not attempt hcloud, openstack, curl IAM, or any other CLI/API methods. This skill does not depend on those tools.
• All paths are relative to the skill directory, which is the directory where this SKILL.md is located.

Overview

This skill generates consolidated operations reports for Huawei Cloud CCE clusters. It aggregates outputs from daily inspection, capacity trend forecasting, availability risk scanning, cost optimization analysis, and optional on-call context into structured reports (weekly, monthly, SLA, capacity, stability). Default behavior is read-only analysis and report generation.

Architecture: Python dispatcher (scripts/huawei-cloud.py) → huawei_generate_ops_report → aggregates from huawei-cloud-cce-daily-cluster-inspector, huawei-cloud-cce-capacity-trend-forecaster, huawei-cloud-cce-availability-risk-scanner, huawei-cloud-cce-cost-optimization-advisor, on-call context → Markdown + HTML + JSON reports

Related Skills

Capabilities

1. One-shot consolidated ops report generation (huawei_generate_ops_report)
2. Five report types: weekly, monthly, sla, capacity, stability
3. Aggregated summaries from inspection, capacity, availability, cost, and on-call sources
4. Prioritized cross-source recommendations with risk levels
5. Markdown and HTML output with trend charts when capacity data is available
6. Optional raw payload traceability (include_raw=true)
7. Graceful degradation: reports continue even if individual sources fail, marking data gaps clearly

Typical Use Cases

• "Generate a weekly ops report for my CCE cluster"
• "Create a monthly operations summary with capacity and availability findings"
• "Produce an SLA report combining inspection and on-call data"
• "Consolidate capacity trends and cost optimization into a stability report"
• "Generate a report with on-call context from last week's incidents"
• "Export a consolidated ops report in HTML with charts"

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Prerequisites

Python Dependencies

The dispatcher script requires Python >= 3.6 and the following packages:

• huaweicloudsdkcore
• huaweicloudsdkcce
• huaweicloudsdkaom
• huaweicloudsdkhss
• huaweicloudsdkvpc
• huaweicloudsdkecs
• huaweicloudsdkces
• huaweicloudsdkevs
• huaweicloudsdkeip
• huaweicloudsdkelb
• huaweicloudsdkiam
• kubernetes
• matplotlib
• numpy

Install: pip3 install huaweicloudsdkcore huaweicloudsdkcce huaweicloudsdkaom huaweicloudsdkhss huaweicloudsdkvpc huaweicloudsdkecs huaweicloudsdkces huaweicloudsdkevs huaweicloudsdkeip huaweicloudsdkelb huaweicloudsdkiam kubernetes matplotlib numpy

Credential Configuration

🚫 Never expose or log AK/SK values. Credentials exist only in the current request call stack and are released after each invocation. Do not write credentials to files, logs, or responses.

✅ Use environment variables HUAWEI_AK / HUAWEI_SK for authentication. The dispatcher reads them automatically.

IAM Permission Requirements

This skill aggregates data from multiple sub-skills. It requires all permissions needed by:

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Core Commands

All actions are invoked via the dispatcher script:

python3 scripts/huawei-cloud.py  region= cluster_id= [key=value ...]

1. Primary Action: Generate Ops Report

The primary action aggregates all sub-skill outputs into a consolidated report:

python3 scripts/huawei-cloud.py huawei_generate_ops_report \
  region=cn-north-4 cluster_id= \
  report_type=weekly \
  output_dir=./output

Returns: consolidated summary, cross-source recommendations, data gaps, and output files (Markdown, HTML, JSON, optional SVG charts).

2. Supporting Context Actions

For follow-up deep dives after report generation:

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Parameter Reference

huawei_generate_ops_report (Primary Action)

Default Hours by Report Type

Common Region IDs

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Output Format

See references/output-schema.md for the complete JSON response schema.

Output Files

When output_dir is specified, the following files are generated:

Key Output Fields

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Workflow

1. Collect region, cluster_id, report type, time window, namespace scope, and output directory from user
2. Execute huawei_generate_ops_report — it aggregates from all five sources internally
3. Review generated Markdown report first, then HTML report for charts and visualization
4. For high-risk findings, trace back to source sections:
   • Daily anomalies → huawei-cloud-cce-daily-cluster-inspector
   • Risk level and issue categories → huawei-cloud-cce-availability-risk-scanner
   • Oversized requests / low utilization → huawei-cloud-cce-cost-optimization-advisor
   • Trend slope / bottleneck projection → huawei-cloud-cce-capacity-trend-forecaster
5. If customer asks for remediation, switch to explicit change workflow and require authorization — hand off to huawei-cloud-cce-auto-remediation-runner

Data Gap Handling

• If a source report fails, the aggregate report continues and marks that source as degraded
• If on-call input is missing, mark as a context gap instead of failing the report
• Preserve source file pointers and optional raw payloads (include_raw=true) for auditability

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Verification

1. Run a weekly report with a known cluster:

   python3 scripts/huawei-cloud.py huawei_generate_ops_report \
     region=cn-north-4 cluster_id= \
     report_type=weekly output_dir=./output
   

2. Verify success=true and all four source summaries are present
3. Check that recommendations lists cross-source items with [source][risk_level] prefixes
4. Verify data_gaps is empty when all sources succeed
5. Confirm ops-weekly-report.md and ops-weekly-report.html are generated in output_dir
6. Test with include_raw=true and verify ops-weekly-raw.json contains source payloads
7. Test with oncall_summary="Test incident" and verify on-call context appears in summary

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Best Practices

1. Always use huawei_generate_ops_report as the primary action; it aggregates all sources in one call
2. Choose report type matching the reporting cycle: weekly for weekly reviews, monthly for monthly summaries, sla for SLA tracking, capacity for capacity planning, stability for stability assessment
3. Use output_dir to persist reports for audit and stakeholder review
4. For traceability, use include_raw=true to preserve source payloads
5. If on-call context is available, pass it via oncall_report_path or oncall_summary to enrich the report
6. For high-risk findings, trace back to the relevant sub-skill for detailed remediation plans
7. Do NOT execute write actions (HPA apply, scale, node pool resize, workload mutation) unless the user explicitly authorizes remediation — hand off to huawei-cloud-cce-auto-remediation-runner

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Reference Documents

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Notes

• Read-only by design — this skill does NOT modify workloads, HPA, node pools, or cluster configuration
• Remediation hand-off — all mutation suggestions are handed off to huawei-cloud-cce-auto-remediation-runner with user authorization
• Never expose or log AK/SK or environment variable values
• All actions are executed via python3 scripts/huawei-cloud.py ; do not use hcloud CLI or direct API calls
• Data gaps — the report continues generation even when individual sources fail; gaps are clearly marked
• On-call optional — when on-call context is unavailable, the report still generates with a marked context gap

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Common Pitfalls