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huawei-cloud-cce-metric-analyzer

Huawei Cloud CCE Metric analysis skill using the Python dispatcher with hcloud-backed cloud service queries. Use this skill when the user wants to: (1) query Pod/Node/CoreDNS/nginx-ingress/autoscaler/

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Imported from huaweicloud/huaweicloud-skills (skills/container/cce/huawei-cloud-cce-metric-analyzer/SKILL.md). Install upstream with npx skills add huaweicloud/huaweicloud-skills --skill huawei-cloud-cce-metric-analyzer. Copyright stays with the author.

Huawei Cloud CCE Metric Analyzer

Overview

Query and analyze metrics for CCE clusters (Pod/Node CPU/memory/disk) and cloud resources (ECS, ELB, EIP, NAT). Supports threshold-based anomaly detection, status classification (critical/warning/normal), and full-cluster monitoring aggregation.

Architecture: python3 scripts/huawei-cloud.py dispatcher → hcloud (KooCLI) cloud service queries + signed AOM Prometheus HTTP queries + limited kubectl reads only when Kubernetes resource relationships are required → Pod/Node metrics, ECS/ELB/EIP/NAT metrics → Threshold classification → Anomaly detection

Execution method: Cloud service queries are executed through the local hcloud CLI. AOM Prometheus query_range calls are the only exception and use signed HTTPS requests because the required Prometheus range-query path is not compatible with hcloud. Do not call Huawei Cloud SDKs, curl IAM flows, openstack, or hand-written cloud APIs outside the bundled dispatcher.

Related Skills: use pod/node diagnosers, Kubernetes event analyzer, capacity/cost skills, or auto-remediation runner for follow-up diagnosis or explicitly requested remediation.

Capabilities:

  • Pod CPU/memory TopN ranking and single Pod time-series metrics
  • Node CPU/memory/disk TopN ranking and single Node time-series metrics
  • Node GPU and xGPU metrics, including GPU utilization, memory, temperature, power, schedule policy, xGPU allocation, usage, and health
  • CoreDNS QPS, error rate excluding NXDOMAIN, NXDOMAIN rate, P95 latency, replica count, and per-Pod CPU/memory metrics
  • nginx-ingress QPS, 4xx/5xx rate, success rate, P95 latency, active connections, per-Pod CPU/memory, and Ingress TLS certificate expiration status
  • Autoscaler unschedulable Pods, node state count, scale-up/down events, errors, node groups, HPA current/desired replicas, and per-Pod CPU/memory metrics
  • Kubernetes control-plane metrics for apiserver, etcd, controller-manager, and scheduler
  • ECS instance CPU/memory/disk/network metrics
  • ELB connection, bandwidth, QPS metrics
  • EIP bandwidth, traffic, packet loss metrics
  • NAT Gateway SNAT connection metrics
  • Full-cluster monitoring aggregation with anomaly detection (80% threshold)
  • Threshold-based status classification (critical/warning/normal/unknown)

Typical Use Cases: query Pod/Node TopN, GPU/xGPU, CoreDNS, nginx-ingress, autoscaler, control-plane, ECS/ELB/EIP/NAT metrics, full-cluster aggregation, and threshold-based anomaly detection.

Prerequisites

1. Runtime Dependencies

  • Python 3.8+ for the dispatcher and result processing
  • hcloud (KooCLI) 7.2.2+ for CCE/ECS/ELB/VPC/EIP/NAT/CES/IAM cloud service queries
  • kubectl only for Kubernetes resource reads that cannot be derived from AOM/hcloud, such as Pod label_selector filtering, Ingress TLS certificate checks, and LoadBalancer Service discovery for ELB/EIP association; clusters without external EIP require the kubectl cce plugin from kubectl-cce-plugin/README.md
  • Prometheus-related monitoring data is queried from AOM Prometheus with signed HTTPS requests; the cluster must have the Prometheus add-on integrated with AOM, otherwise these tools may return empty metric series
  • Controller-manager, scheduler, and etcd metrics require the kube-controller-manager, kube-scheduler, and etcd-server ServiceMonitors to be enabled separately in AOM; otherwise these tools may return empty metric series
  • Autoscaler, ingress-controller, and NVIDIA GPU metrics require the corresponding autoscaler, ingress-controller, and nvidia-gpu-device-plugin PodMonitors to be enabled separately in AOM; ingress request metrics also require nginx_ingress_controller_requests to be explicitly allowed in the ingress-controller PodMonitor
  • Run environment check before first use (see Verification section)
  • Install and use kubectl-cce according to references/kubectl-cce.md

2. Credential Configuration

  • Valid Huawei Cloud credentials via hcloud profile or 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
    • ✅ Credential priority for hcloud calls is: explicit tool parameters > local hcloud profile > environment variables
    • ✅ AOM Prometheus signed HTTP and Kubernetes certificate setup cannot use encrypted hcloud profile material, so they use explicit tool parameters first and environment variables as the signing fallback
    • ✅ Prefer IAM users over root account for cloud operations
    • ✅ Enable MFA for sensitive operations

Configuration Method:

hcloud configure list

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

3. IAM Permission Requirements

API Action Permission Purpose
cce:cluster:get Get cluster View CCE cluster details
aom:instance:list List AOM instances Discover AOM Prometheus instance for metrics
aom:metricsData:get Get metrics data Query Pod/Node CPU/memory/disk metrics
ces:metricsData:get Get CES metrics Query ECS/ELB/EIP/NAT cloud resource metrics
ecs:cloudServers:list List ECS servers Correlate ECS instance IDs
elb:loadbalancers:list List ELB instances Correlate ELB IDs
vpc:eips:list List EIPs Correlate EIP IDs
nat:natGateways:list List NAT Gateways Correlate NAT Gateway IDs

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

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

KooCLI命令格式标准

Do not ask users to run raw hcloud commands directly. Use the dispatcher format:

python3 scripts/huawei-cloud.py <tool-name> key=value key=value

The dispatcher converts cloud service queries to KooCLI calls. AOM Prometheus range queries use signed HTTPS requests because that path is not compatible with hcloud. Avoid Kubernetes resource reads unless the tool explicitly needs Pod labels, Ingress TLS Secrets, or LoadBalancer Services. Quote values containing spaces, >, <, |, JSON, or PromQL; never print or persist AK/SK, security tokens, kubeconfig files, or temporary payloads; keep Kubernetes/AOM PromQL scoped with cluster="<cluster_id>".

1. CCE Pod Metrics

# Pod TopN — cluster-wide CPU/memory ranking
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

# Pod TopN with label selector
python3 scripts/huawei-cloud.py huawei_get_cce_pod_metrics_topN \
  region=cn-north-4 cluster_id=<cluster-id> \
  namespace=default label_selector="app=nginx,version=v1" top_n=10 hours=1

# Single Pod time-series
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

# Single Pod GPU and xGPU metrics
python3 scripts/huawei-cloud.py huawei_get_cce_pod_gpu_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  pod_name=my-gpu-app-xxx namespace=default hours=1

2. CCE Node Metrics

# Node TopN — cluster-wide CPU/memory/disk ranking
python3 scripts/huawei-cloud.py huawei_get_cce_node_metrics_topN \
  region=cn-north-4 cluster_id=<cluster-id> \
  top_n=10 hours=1

# Single Node time-series
python3 scripts/huawei-cloud.py huawei_get_cce_node_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  node_ip=10.0.0.1 hours=1

# Node GPU and xGPU metrics
python3 scripts/huawei-cloud.py huawei_get_cce_node_gpu_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  node_ip=10.0.0.1 hours=1

3. CCE CoreDNS Metrics

# CoreDNS key metrics: QPS, error rate excluding NXDOMAIN, NXDOMAIN rate, P95 latency, replicas, CPU, and memory
python3 scripts/huawei-cloud.py huawei_get_cce_coredns_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  namespace=kube-system pod_regex=".*coredns.*" hours=1

4. CCE nginx-ingress Metrics

# nginx-ingress request processing and Ingress TLS certificate expiration
python3 scripts/huawei-cloud.py huawei_get_cce_nginx_ingress_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  namespace=kube-system pod_regex=".*nginx.*ingress.*|.*ingress.*nginx.*" \
  ingress_namespace=default cert_expire_warning_days=30 hours=1

5. CCE Autoscaler Metrics

# Cluster Autoscaler and HPA metrics
python3 scripts/huawei-cloud.py huawei_get_cce_autoscaler_metrics \
  region=cn-north-4 cluster_id=<cluster-id> \
  namespace=kube-system pod_regex=".*cluster.*autoscaler.*|.*autoscaler.*" \
  include_hpa=true hours=1

6. Kubernetes Control Plane Metrics

python3 scripts/huawei-cloud.py huawei_get_cce_apiserver_metrics \
  region=cn-north-4 cluster_id=<cluster-id> hours=1

python3 scripts/huawei-cloud.py huawei_get_cce_etcd_metrics \
  region=cn-north-4 cluster_id=<cluster-id> hours=1

python3 scripts/huawei-cloud.py huawei_get_cce_controller_manager_metrics \
  region=cn-north-4 cluster_id=<cluster-id> namespace=kube-system hours=1

python3 scripts/huawei-cloud.py huawei_get_cce_scheduler_metrics \
  region=cn-north-4 cluster_id=<cluster-id> namespace=kube-system hours=1

7. Cloud Resource Metrics

# ECS instance metrics
python3 scripts/huawei-cloud.py huawei_get_ecs_metrics \
  region=cn-north-4 instance_id=<instance-id>

# ELB metrics
python3 scripts/huawei-cloud.py huawei_get_elb_metrics \
  region=cn-north-4 elb_id=<loadbalancer-id> hours=1

# EIP metrics
python3 scripts/huawei-cloud.py huawei_get_eip_metrics \
  region=cn-north-4 eip_id=<eip-id> hours=1

# NAT Gateway metrics
python3 scripts/huawei-cloud.py huawei_get_nat_gateway_metrics \
  region=cn-north-4 nat_gateway_id=<nat-gateway-id> hours=1

8. Cluster Monitoring Aggregation

# Aggregate all monitoring data with anomaly detection
python3 scripts/huawei-cloud.py huawei_cce_cluster_monitoring_aggregation \
  region=cn-north-4 cluster_id=<cluster-id> \
  start_time="2026-05-30 00:00:00" end_time="2026-05-30 23:59:59" \
  namespace=default top_n=10

This tool aggregates: Pod TopN CPU/memory, Node TopN CPU/memory/disk, ELB metrics (matched through LoadBalancer Services fetched by kubectl), NAT Gateway metrics, EIP metrics (bandwidth, packet loss), and anomaly detection using 80% threshold.

It also includes CoreDNS, nginx-ingress, and autoscaler summaries. Cloud resources are scoped to the current cluster when an association can be proven: ELB is matched through LoadBalancer Service IP/EIP, NAT Gateway is filtered by the cluster VPC, and EIP is limited to associated ELB/NAT/Service IPs.

LoadBalancer Service discovery uses kubectl with generated kubeconfig through the cluster EIP when external access is available. If the cluster has no EIP, it uses the kubectl cce plugin. If neither path works, aggregation fails.

Risk Levels

This skill is read-only. It does not create, update, delete, restart, scale, or modify Huawei Cloud or Kubernetes resources.

Level Meaning Execution Guidance
R3 No-risk read-only query or local analysis May run automatically
R2 Low-risk change, such as creating monitoring configuration without deleting resources or increasing service capacity/cost Not used by current tools
R1 Risky operation, such as restart-like impact, disabling protection, or changes that may increase cost or reduce observability Not used by current tools
R0 Critical operation, such as deleting clusters, applications, or broad-impact monitoring protections Not used by current tools
Tool Operation Type Risk Level Description
huawei_get_cce_pod_metrics_topN Query R3 Read Pod CPU/memory/disk TopN metrics from AOM Prometheus
huawei_get_cce_pod_metrics Query R3 Read single Pod CPU/memory/disk time-series metrics
huawei_get_cce_node_metrics_topN Query R3 Read Node CPU/memory/disk TopN metrics from AOM Prometheus
huawei_get_cce_node_metrics Query R3 Read single Node CPU/memory/disk time-series metrics
huawei_get_cce_node_gpu_metrics Query R3 Read single Node GPU and xGPU metrics from AOM Prometheus
huawei_get_cce_pod_gpu_metrics Query R3 Read single Pod GPU and xGPU metrics from AOM Prometheus
huawei_get_cce_coredns_metrics Query R3 Read CoreDNS QPS, error rate excluding NXDOMAIN, NXDOMAIN rate, P95 latency, replicas, and per-Pod CPU/memory metrics
huawei_get_cce_nginx_ingress_metrics Query R3 Read nginx-ingress request-processing metrics and Ingress TLS certificate expiration status; QPS falls back to nginx process request counters when request-dimension metrics are absent
huawei_get_cce_autoscaler_metrics Query R3 Read Cluster Autoscaler scaling metrics, HPA replica state, and autoscaler Pod CPU/memory metrics
huawei_get_cce_apiserver_metrics Query R3 Read kube-apiserver QPS, error rate, latency, and inflight request metrics
huawei_get_cce_etcd_metrics Query R3 Read etcd leader, proposal, DB size, disk latency, CPU, and memory metrics
huawei_get_cce_controller_manager_metrics Query R3 Read control-plane workqueue depth, adds, retries, queue latency, and work duration metrics
huawei_get_cce_scheduler_metrics Query R3 Read scheduler attempts, pending Pods, scheduling latency, and queue metrics
huawei_get_ecs_metrics Query R3 Read ECS monitoring data through hcloud/CES
huawei_get_elb_metrics Query R3 Read ELB monitoring data through hcloud/CES
huawei_get_eip_metrics Query R3 Read EIP monitoring data through hcloud/CES
huawei_get_nat_gateway_metrics Query R3 Read NAT Gateway monitoring data through hcloud/CES
huawei_cce_cluster_monitoring_aggregation Query + local analysis R3 Aggregate Pod/Node/cloud-resource metrics and classify anomalies locally

Parameter Reference

Common Parameters

Parameter Required/Optional Description Default
region Required Huawei Cloud region HUAWEI_REGION
cluster_id Required CCE cluster ID N/A
namespace Recommended Kubernetes namespace default
ak Optional Explicit AK; highest priority for all calls profile/env fallback
sk Optional Explicit SK; highest priority for all calls profile/env fallback
project_id Optional Explicit Project ID; hcloud uses profile before env fallback Auto from IAM/profile

huawei_get_cce_pod_metrics_topN Parameters

Parameter Required Description Default
namespace No Namespace filter all
label_selector No Label selector (e.g. app=web) N/A
top_n No Number of top items 10
hours No Metrics lookback hours 1
node_ip No Filter Pods on specific node N/A
cpu_query No Custom CPU PromQL Auto
memory_query No Custom memory PromQL Auto
disk_query No Custom disk PromQL Auto

huawei_get_cce_pod_metrics Parameters

Parameter Required Description Default
pod_name Yes Target Pod name N/A
namespace No Namespace default
hours No Metrics lookback hours 1
cpu_query No Custom CPU PromQL Auto
memory_query No Custom memory PromQL Auto
disk_query No Custom disk PromQL Auto

huawei_get_cce_pod_gpu_metrics Parameters

Parameter Required Description Default
pod_name Yes Target Pod name N/A
namespace No Target Pod namespace all
hours No Metrics lookback hours 1
gpu_selector No Custom GPU metric label selector. Use this when GPU metrics do not use the pod or namespace labels pod="<pod_name>",namespace="<namespace>"

Optional custom PromQL overrides are supported for GPU utilization, memory, schedule policy, xGPU allocation/usage, and xGPU health metrics.

huawei_get_cce_node_metrics_topN Parameters

Parameter Required Description Default
top_n No Number of top items 10
hours No Metrics lookback hours 1

huawei_get_cce_node_metrics Parameters

Parameter Required Description Default
node_ip Yes Target Node IP N/A
hours No Metrics lookback hours 1

huawei_get_cce_node_gpu_metrics Parameters

Parameter Required Description Default
node_ip Yes Target Node IP or node name N/A
hours No Metrics lookback hours 1
gpu_selector No Custom GPU metric label selector. Use this when GPU metrics do not use the node label `node=~"<node_ip>

Optional custom PromQL overrides are supported for GPU utilization, memory, temperature, power, schedule policy, xGPU allocation/usage, and xGPU health metrics.

huawei_get_cce_coredns_metrics Parameters

Parameter Required Description Default
namespace No CoreDNS namespace kube-system
pod_regex No Regex used to match CoreDNS Pods .*coredns.*
hours No Metrics lookback hours 1

Optional custom PromQL overrides are supported for QPS, error rate, NXDOMAIN rate, P95 latency, CPU, memory, and replica count.

huawei_get_cce_nginx_ingress_metrics Parameters

Parameter Required Description Default
namespace No Namespace of nginx-ingress controller Pods. Use an empty value to query all namespaces kube-system
pod_regex No Regex used to match nginx-ingress controller Pods `.*nginx.ingress.
ingress_namespace No Namespace filter for Ingress TLS certificate checks all
hours No Metrics lookback hours 1
cert_expire_warning_days No Days before expiry to mark certificates as warning 30
check_certificates No Whether to inspect Ingress TLS Secrets for expiration status true

Ingress-controller metrics depend on the corresponding AOM PodMonitor. The nginx_ingress_controller_requests metric must be explicitly allowed in the ingress-controller PodMonitor; otherwise request-dimension metrics such as 4xx/5xx QPS, success rate, and latency may be empty, and QPS may only use the nginx_ingress_controller_nginx_process_requests_total fallback when available.

Optional custom PromQL overrides are supported for QPS, 4xx/5xx, success rate, P95 latency, active connections, CPU, and memory.

huawei_get_cce_autoscaler_metrics Parameters

Parameter Required Description Default
namespace No Namespace of Cluster Autoscaler Pods. Use an empty value to query all namespaces kube-system
pod_regex No Regex used to match autoscaler Pods `.*cluster.autoscaler.
hpa_namespace No Namespace filter for HPA replica metrics all
hours No Metrics lookback hours 1
include_hpa No Whether to query HPA current/desired replica metrics true

Optional custom PromQL overrides are supported for unschedulable Pods, node states, scale events, errors, node groups, HPA replicas, CPU, and memory.

Kubernetes Control Plane Tool Parameters

Applies to huawei_get_cce_apiserver_metrics, huawei_get_cce_etcd_metrics, huawei_get_cce_controller_manager_metrics, and huawei_get_cce_scheduler_metrics.

huawei_get_cce_apiserver_metrics defaults to cluster="<cluster_id>",component="apiserver" and does not add namespace or Pod labels. Its default P95 latency excludes WATCH|CONNECT requests and also returns latency_p95_by_verb_ms for diagnosis. Use metric_selector only when the Prometheus labels differ.

huawei_get_cce_etcd_metrics defaults to cluster="<cluster_id>" and does not add namespace or Pod labels. Use metric_selector only when the Prometheus labels differ.

huawei_get_cce_controller_manager_metrics defaults to cluster="<cluster_id>" because CCE AOM workqueue metrics may not expose stable controller-manager Pod labels. It returns both aggregate workqueue metrics and per-queue name breakdowns.

huawei_get_cce_scheduler_metrics defaults to cluster="<cluster_id>" and returns aggregate metrics plus result, profile/result, and queue breakdowns.

Controller-manager, scheduler, and etcd metrics depend on AOM ServiceMonitor collection being enabled for the corresponding kube-controller-manager, kube-scheduler, and etcd-server endpoints. If ServiceMonitor is not enabled, the tools can run successfully but return empty series.

Parameter Required Description Default
namespace No Namespace of control-plane Pods. Use an empty value to query all namespaces kube-system
pod_regex No Regex used to match target component Pods component-specific
metric_selector No Custom apiserver/etcd/controller-manager/scheduler metric label selector apiserver: cluster="<cluster_id>",component="apiserver"; etcd/controller-manager/scheduler: cluster="<cluster_id>"
hours No Metrics lookback hours 1

Cloud Resource Tool Parameters

Tool Required ID Parameter Optional Parameters
huawei_get_ecs_metrics instance_id none
huawei_get_elb_metrics elb_id hours
huawei_get_eip_metrics eip_id hours
huawei_get_nat_gateway_metrics nat_gateway_id hours

huawei_cce_cluster_monitoring_aggregation Parameters

Parameter Required Description Default
start_time Yes Start time (YYYY-MM-DD HH:MM:SS) N/A
end_time Yes End time (YYYY-MM-DD HH:MM:SS) N/A
namespace No Namespace filter default
top_n No Number of top items 10
security_token No Temporary security token for AK/SK session credentials env fallback

Output Format

See Output Schema for the complete JSON response structure.

Key output fields:

  • success — boolean, true if query completed
  • region — Huawei Cloud region
  • cluster_id / cluster_name — CCE cluster identity
  • aom_instance_id — AOM Prometheus instance used for metric queries
  • metrics — Dict with cpu/memory/disk data per resource, including status classification
  • certificate_check — nginx-ingress Ingress TLS certificate expiration summary when certificate checking is enabled
  • time_series — Historical data points with timestamp, time, average, min, max
  • status — Threshold classification: critical (>80% CPU, >85% memory/disk), warning (>50% CPU/memory, >70% disk), normal (below warning), unknown (no data)

Workflow

  1. Resolve region, cluster ID, and credentials using the documented priority.
  2. Discover the AOM Prometheus instance from the CCE cluster add-on binding.
  3. Start with Pod/Node TopN or aggregation, then drill into a Pod, Node, component, or cloud resource.
  4. Keep PromQL scoped by cluster="<cluster_id>"; add namespace, pod, or resource filters only to reduce noise.
  5. Use status classification as an investigation lead, then correlate anomalies with events or alarm history.

Verification

  1. Run python3 scripts/huawei-cloud.py huawei_get_cce_pod_metrics_topN region=cn-north-4 cluster_id=<cluster-id> namespace=default top_n=5 to verify Pod metric queries
  2. Run python3 scripts/huawei-cloud.py huawei_get_cce_node_metrics_topN region=cn-north-4 cluster_id=<cluster-id> top_n=5 to verify Node metric queries
  3. Run python3 scripts/huawei-cloud.py huawei_get_ecs_metrics region=cn-north-4 instance_id=<instance-id> to verify CES metric connectivity

Best Practices

  1. Start with Pod/Node TopN before drilling into individual resources.
  2. Keep hours small (1-4) for recent analysis; cap historical reviews at 24 hours.
  3. Provide namespace to reduce Pod noise while preserving the cluster filter.
  4. Focus on critical and warning resources first.
  5. Use huawei_cce_cluster_monitoring_aggregation for full-cluster health checks.
  6. Correlate metric anomalies with huawei-cloud-cce-kubernetes-event-analyzer.
  7. Do not expose production Pod names, node IPs, or cluster IDs in public summaries.

Notes

  • This skill is strictly read-only and never modifies resources or configurations.
  • Thresholds are predefined baselines; tune them against workload SLOs before making operational decisions.
  • AK/SK must never be hardcoded; use hcloud profile for normal hcloud calls or environment fallback for signed AOM/Kubernetes calls.
  • scripts/huawei-cloud.py is the only user-facing execution method
  • AOM Prometheus instance is auto-discovered; no need to manually specify aom_instance_id
  • Cloud resource metrics (ECS/ELB/EIP/NAT) use CES (Cloud Eye Service), not AOM
  • Do not make automatic scaling or remediation decisions based solely on metric analysis.

Troubleshooting

Pitfall Symptom Quick Fix
Missing cluster_id Action fails immediately Provide cluster_id from cluster listing
AOM Prometheus instance not found Metric queries return empty results Ensure AOM Prom instance is created for the cluster; check aom:instance:list permission
Large time window without namespace filter Slow response, too many results Narrow hours to 1-4 and add namespace filter
Cloud resource ID not found ECS/ELB/EIP/NAT query returns error Verify resource ID and CES IAM permission
Custom PromQL syntax error Custom query returns empty Use default PromQL unless familiar with AOM PromQL
Aggregation missing time range start_time / end_time missing Provide both time boundaries

Limitations

  • AOM Prometheus data requires the cluster Prometheus add-on to be integrated with AOM.
  • Control-plane ServiceMonitors and component PodMonitors must be enabled before related metrics appear.
  • Query results reflect collected monitoring data only; missing series are not proof that the workload is healthy.
  • This skill does not remediate, scale, restart, create, update, or delete cloud or Kubernetes resources.

References

Document Description
Workflow Metric query sequence, threshold detection, next-step handoff
Risk Rules Read-only constraints, data redaction, time-bounding, threshold caveats
Output Schema JSON response schema for metric and status output
CLI Installation Guide hcloud, kubectl, kubectl-cce, and dispatcher setup
IAM Policies Required read-only Huawei Cloud and Kubernetes permissions
Verification Method Static checks and smoke tests
Acceptance Criteria Functional, security, documentation, and quality gates

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml
targets:
  - https://api.opensmartroute.ai/api/v1/registry/huaweicloud-huaweicloud-skills-huawei-cloud-cce-metric-analyzer/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

huaweicloud-huaweicloud-skills-huawei-cloud-cce-metric-analyzer.ocm.jsonjson
{
  "ocm": "1",
  "id": "huaweicloud-huaweicloud-skills-huawei-cloud-cce-metric-analyzer",
  "kind": "skill",
  "name": "huawei-cloud-cce-metric-analyzer",
  "description": "Huawei Cloud CCE Metric analysis skill using the Python dispatcher with hcloud-backed cloud service queries. Use this skill when the user wants to: (1) query Pod/Node/CoreDNS/nginx-ingress/autoscaler/control-plane CPU, memory, disk, QPS, latency, request, connection, certificate, scaling, or error-rate metrics, (2) get resource usage TopN rankings, (3) query ECS/ELB/EIP/NAT cloud resource metrics, (4) aggregate cluster monitoring data with anomaly detection, (5) detect threshold-based resource anomalies. Trigger: user mentions \"metric analysis\", \"指标分析\", \"CCE metrics\", \"CCE 指标\", \"AOM metrics\", \"AOM 指标\", \"CoreDNS metrics\", \"CoreDNS 指标\", \"nginx ingress metrics\", \"nginx-ingress 指标\", \"autoscaler metrics\", \"autoscaler 指标\", \"HPA metrics\", \"HPA 指标\", \"apiserver metrics\", \"etcd metrics\", \"controller manager metrics\", \"scheduler metrics\", \"control plane metrics\", \"控制面指标\", \"certificate expiration\", \"证书过期\", \"resource metrics\", \"资源指标\", \"CPU usage\", \"CPU 使用率\", \"memory usage\", \"内存使用率\", \"performance monitoring\", \"性能监控\", \"TopN",
  "publisher": "huaweicloud",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "data_analysis",
      "coding"
    ],
    "tags": [
      "skill-md",
      "cce",
      "metrics",
      "aom",
      "observability",
      "analysis",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Huawei Cloud CCE Metric analysis skill using the Python dispatcher with hcloud-backed cloud service queries. Use this skill when the user wants to: (1) query Pod/Node/CoreDNS/nginx-ingress/autoscaler/control-plane CPU, memory, disk, QPS, latency, request, connection, certificate, scaling, or error-rate metrics, (2) get resource usage TopN rankings, (3) query ECS/ELB/EIP/NAT cloud resource metrics, (4) aggregate cluster monitoring data with anomaly detection, (5) detect threshold-based resource anomalies. Trigger: user mentions \"metric analysis\", \"指标分析\", \"CCE metrics\", \"CCE 指标\", \"AOM metrics\", \"AOM 指标\", \"CoreDNS metrics\", \"CoreDNS 指标\", \"nginx ingress metrics\", \"nginx-ingress 指标\", \"autoscaler metrics\", \"autoscaler 指标\", \"HPA metrics\", \"HPA 指标\", \"apiserver metrics\", \"etcd metrics\", \"controller manager metrics\", \"scheduler metrics\", \"control plane metrics\", \"控制面指标\", \"certificate expiration\", \"证书过期\", \"resource metrics\", \"资源指标\", \"CPU usage\", \"CPU 使用率\", \"memory usage\", \"内存使用率\", \"performance monitoring\", \"性能监控\", \"TopN"
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/huaweicloud/huaweicloud-skills",
      "path": "skills/container/cce/huawei-cloud-cce-metric-analyzer/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/huaweicloud/huaweicloud-skills/blob/HEAD/skills/container/cce/huawei-cloud-cce-metric-analyzer/SKILL.md",
      "key": "huaweicloud/huaweicloud-skills/skills/container/cce/huawei-cloud-cce-metric-analyzer/SKILL.md"
    }
  },
  "instructions": "# Huawei Cloud CCE Metric Analyzer\n\n## Overview\n\nQuery and analyze metrics for CCE clusters (Pod/Node CPU/memory/disk) and cloud resources (ECS, ELB, EIP, NAT). Supports threshold-based anomaly detection, status classification (critical/warning/normal), and full-cluster monitoring aggregation.\n\n**Architecture**: `python3 scripts/huawei-cloud.py` dispatcher → hcloud (KooCLI) cloud service queries + signed AOM Prometheus HTTP queries + limited kubectl reads only when Kubernetes resource relationships are required → Pod/Node metrics, ECS/ELB/EIP/NAT metrics → Threshold classification → Anomaly de",
  "cost": {
    "context_tokens": 7348
  }
}

Fetch it by URL: GET /api/v1/registry/huaweicloud-huaweicloud-skills-huawei-cloud-cce-metric-analyzer/manifest?version=1.0.0

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