Huawei Cloud Cce Ops Report Generator

Other

Use when generating consolidated CCE operations reports that combine daily inspection, capacity trend, availability risk, cost optimization, and on-call context into weekly, monthly, SLA, capacity, or stability reports with Markdown and HTML output. Trigger: user mentions "ops report", "运维报告", "report generation", "报告生成", "cluster report", "集群报告", "weekly report", "月度报告", "SLA report", "capacity report", "stability report", "operations summary", "运营总结", "consolidated report", "综合报告", "CCE reporting", "oncall report", "值班报告"

Install

openclaw skills install 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

Skill	Purpose
`huawei-cloud-cce-daily-cluster-inspector`	Daily health inspection and risk summarization
`huawei-cloud-cce-capacity-trend-forecaster`	Capacity trend analysis, bottleneck forecasting, HPA simulation
`huawei-cloud-cce-availability-risk-scanner`	Availability risk scanning (single replicas, PDB, AZ distribution)
`huawei-cloud-cce-cost-optimization-advisor`	Cost optimization analysis (idle resources, oversized requests)
`huawei-cloud-cce-auto-remediation-runner`	Execute remediation actions when user authorizes

Capabilities

One-shot consolidated ops report generation (huawei_generate_ops_report)
Five report types: weekly, monthly, sla, capacity, stability
Aggregated summaries from inspection, capacity, availability, cost, and on-call sources
Prioritized cross-source recommendations with risk levels
Markdown and HTML output with trend charts when capacity data is available
Optional raw payload traceability (include_raw=true)
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"

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

Variable	Required	Description
`HUAWEI_AK`	Yes	Huawei Cloud Access Key
`HUAWEI_SK`	Yes	Huawei Cloud Secret Key
`HUAWEI_REGION`	No	Default region (overrides `region` param if set)
`HUAWEI_PROJECT_ID`	No	Project ID (auto-obtained via IAM API when not set)
`HUAWEI_SECURITY_TOKEN`	No	Required when using temporary AK/SK

🚫 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:

Sub-Skill	Required Permissions
`huawei-cloud-cce-daily-cluster-inspector`	CCE cluster/node/workload/event read, AOM alarm read
`huawei-cloud-cce-capacity-trend-forecaster`	CCE cluster/node/nodepool/Deployment/HPA read, AOM metrics read
`huawei-cloud-cce-availability-risk-scanner`	CCE cluster/node/workload/PDB/Service/Ingress read, AOM metrics read
`huawei-cloud-cce-cost-optimization-advisor`	CCE cluster/node/nodepool/Deployment/HPA/Pod read, AOM metrics read

Core Commands

All actions are invoked via the dispatcher script:

python3 scripts/huawei-cloud.py <action> region=<region> cluster_id=<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=<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:

Action	Source Skill	Description
`huawei_cce_auto_inspection`	`huawei-cloud-cce-daily-cluster-inspector`	Full daily health inspection
`huawei_analyze_cce_capacity_trend`	`huawei-cloud-cce-capacity-trend-forecaster`	Capacity trend analysis with simulation
`huawei_scan_cce_availability_risk`	`huawei-cloud-cce-availability-risk-scanner`	Availability risk scan with remediation plan
`huawei_analyze_cce_cost_optimization`	`huawei-cloud-cce-cost-optimization-advisor`	Cost optimization analysis

Parameter Reference

`huawei_generate_ops_report` (Primary Action)

Parameter	Required	Default	Description
`region`	Yes	-	Huawei Cloud region (e.g., `cn-north-4`)
`cluster_id`	Yes	-	CCE cluster ID
`report_type`	No	`weekly`	Report type: `weekly`, `monthly`, `sla`, `capacity`, `stability`
`hours`	No	Auto (by type)	Analysis window in hours (overrides default for report type)
`short_hours`	No	24	Short-period lookback for cost analysis
`long_hours`	No	168	Long-period lookback for cost analysis
`exclude_namespaces`	No	`kube-system`	Comma-separated namespaces excluded from business analysis
`business_namespaces`	No	-	Comma-separated namespace allowlist for business Deployments
`gateway_keywords`	No	`nginx,gateway,ingress,proxy,kong,apisix,traefik`	Keywords for identifying gateway-class workloads
`output_dir`	No	-	Directory to persist Markdown, HTML, JSON reports and charts
`include_raw`	No	`false`	Include raw source payloads for traceability
`oncall_report_path`	No	-	Path to on-call report file for incident context
`oncall_summary`	No	-	Inline on-call summary text for incident context

Default Hours by Report Type

Report Type	Default Hours
`weekly`	168
`monthly`	744
`sla`	168
`capacity`	168
`stability`	168

Common Region IDs

Region Name	Region ID
North China - Beijing 4	`cn-north-4`
North China - Beijing 1	`cn-north-1`
East China - Shanghai 1	`cn-east-3`
East China - Shanghai 2	`cn-east-2`
South China - Guangzhou	`cn-south-1`
South China - Shenzhen	`cn-south-4`
Southwest China - Guiyang 1	`cn-southwest-2`
Asia Pacific - Bangkok	`ap-southeast-2`
Asia Pacific - Singapore	`ap-southeast-1`
Asia Pacific - Hong Kong	`ap-southeast-3`
Europe - Paris	`eu-west-0`

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:

File	Description
`ops-<type>-summary.json`	Full structured JSON output with summaries, recommendations, and sources
`ops-<type>-report.md`	Markdown report with cross-source analysis and recommendations
`ops-<type>-report.html`	HTML report with embedded SVG trend charts
`ops-capacity-trend.svg`	Capacity trend curve chart (when capacity data available)
`ops-capacity-simulation.svg`	Capacity simulation chart (when simulation data available)
`ops-<type>-raw.json`	Raw source payloads (when `include_raw=true`)

Key Output Fields

Field	Description
`scope`	Report scope: region, cluster_id, excluded namespaces, gateway keywords
`report`	Report metadata: type, hours, short_hours, long_hours
`summary.daily_cluster_inspector`	Health status and anomaly count
`summary.capacity_trend_forecaster`	CPU/memory averages, trend direction, simulation status
`summary.availability_risk_scanner`	Risk level and issue count
`summary.cost_optimization_advisor`	Underutilized nodes and oversized requests count
`summary.oncall_copilot`	On-call context status, source, and summary
`recommendations`	Prioritized cross-source recommendation list with source and risk level
`data_gaps`	List of sources that failed or had missing data
`sources`	Per-source success status and file paths
`files`	Output file paths for all generated artifacts

Workflow

Collect region, cluster_id, report type, time window, namespace scope, and output directory from user
Execute huawei_generate_ops_report — it aggregates from all five sources internally
Review generated Markdown report first, then HTML report for charts and visualization
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
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

Verification

Run a weekly report with a known cluster:

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

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

Best Practices

Always use huawei_generate_ops_report as the primary action; it aggregates all sources in one call
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
Use output_dir to persist reports for audit and stakeholder review
For traceability, use include_raw=true to preserve source payloads
If on-call context is available, pass it via oncall_report_path or oncall_summary to enrich the report
For high-risk findings, trace back to the relevant sub-skill for detailed remediation plans
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

Reference Documents

Document	Description
`references/workflow.md`	Detailed execution process, scope validation, and data gap handling
`references/output-schema.md`	Complete JSON response schema for report output

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 <action>; 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

Common Pitfalls

Pitfall	Correct Approach
Assuming report fails when one source fails	The report continues with degraded sources; data gaps are explicitly listed
Skipping on-call context entirely when unavailable	Mark as a context gap; the report still provides value from other sources
Executing remediation directly from report findings	All remediation requires explicit user authorization; hand off to `huawei-cloud-cce-auto-remediation-runner`
Not using `output_dir` for persistent reports	Always specify `output_dir` for audit traceability and stakeholder access
Treating recommendations as action items without risk context	Each recommendation includes `[source][risk_level]` prefix; prioritize by risk level
Ignoring `include_raw` for compliance requirements	Use `include_raw=true` when audit traceability of source data is required
Using wrong `report_type` for the reporting cycle	Match report type to cycle: weekly=168h, monthly=744h, sla/capacity/stability=168h by default