360 Secure SkillHub
360 安全技能中心

Huawei Cloud Cce Metric Analyzer

该 Skill 通过 Python 调度脚本调用华为云 CCE、AOM、CES 接口，查询 Pod/Node CPU、内存、磁盘 TopN 与时间序列，以及 ECS、ELB、EIP、NAT 资源指标；支持 80% 阈值异常检测、状态分级和集群监控聚合。它只读，不执行资源修改或自动修复。

pintudeyudi
pintudeyudi
热度 78.25
最近更新 2026-06-16 17:50:32
分类：数据依赖：代码执行 / 第三方 API应用场景：数据处理 / 报告撰写 / DevOps

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add huawei-cloud-cce-metric-analyzer
Metadata
id
huawei-cloud-cce-metric-analyzer
name
huawei-cloud-cce-metric-analyzer
description
Huawei Cloud CCE Metric analysis skill using Python SDK dispatcher. Use this skill when the user wants to: (1) query Pod/Node CPU/memory/disk 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", "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", "resource ranking", "资源排名"
tags
["cce","metrics","aom","observability","analysis"]

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 → Huawei Cloud Python SDK + AOM Prometheus → Pod/Node metrics, ECS/ELB/EIP/NAT metrics → Threshold classification → Anomaly detection

Related Skills:

  • huawei-cloud-cce-pod-failure-diagnoser - Pod CrashLoopBackOff, OOMKilled, restart storms
  • huawei-cloud-cce-node-failure-diagnoser - Node health, resource pressure diagnosis
  • huawei-cloud-cce-kubernetes-event-analyzer - Warning events, failure patterns
  • huawei-cloud-cce-capacity-trend-forecaster - Capacity planning and trend forecasting
  • huawei-cloud-cce-cost-optimization-advisor - Resource cost optimization
  • huawei-cloud-cce-auto-remediation-runner - Remediation actions (scale, resize, drain)

Capabilities:

  • Pod CPU/memory TopN ranking and single Pod time-series metrics
  • Node CPU/memory/disk TopN ranking and single Node time-series metrics
  • 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:

  • "Show Pods with the highest CPU usage in my cluster"
  • "Get Node memory usage ranking"
  • "Check ECS instance resource metrics"
  • "What is the ELB QPS for my load balancer?"
  • "Show EIP bandwidth usage"
  • "Aggregate all monitoring data for the cluster"
  • "Which resources have exceeded critical thresholds?"
  • "Detect resource anomalies in the last hour"

Prerequisites

1. Python Dependencies

  • Python 3.8+ with huaweicloudsdkcce, huaweicloudsdkcore, huaweicloudsdkaom, huaweicloudsdkces 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

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>...

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

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

3. 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

4. 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 (with LoadBalancer service association), NAT Gateway metrics, EIP metrics (bandwidth, packet loss), and anomaly detection using 80% threshold.

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 Override AK HUAWEI_AK
sk Optional Override SK HUAWEI_SK
project_id Optional Project ID Auto from IAM

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

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

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_ecs_metrics Parameters

Parameter Required Description Default
instance_id Yes ECS instance ID N/A

huawei_get_elb_metrics Parameters

Parameter Required Description Default
elb_id Yes ELB loadbalancer ID N/A
hours No Metrics lookback hours 1

huawei_get_eip_metrics Parameters

Parameter Required Description Default
eip_id Yes EIP ID N/A
hours No Metrics lookback hours 1

huawei_get_nat_gateway_metrics Parameters

Parameter Required Description Default
nat_gateway_id Yes NAT Gateway ID N/A
hours No Metrics lookback hours 1

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

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
  • 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)

Cloud resource metric fields (ECS/ELB/EIP/NAT):

  • ECS: cpu_util, mem_util, disk_util, network_incoming/outgoing_bytes_rate, disk_read/write_bytes_rate
  • ELB: m1_cps, m14_l7_rt, mb_l7_qps, mc-me-mf_l7_http_2xx-5xx
  • EIP: upstream/downstream_bandwidth, upstream/downstream_bandwidth_usage, upstream/downstream_traffic, packet_loss_rate
  • NAT: snat_connection, inbound/outbound_bandwidth, snat_connection_ratio

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 TopN for cluster-wide overview — use Pod/Node TopN before drilling into individual resources
  2. Time-bound queries — keep hours small (1-4) for recent analysis; cap at 24 hours for historical reviews
  3. Use namespace filtering — always provide namespace to reduce noise in Pod TopN results
  4. Check status classification — focus on critical and warning resources first; normal resources can be skipped
  5. Use aggregation for full-cluster health checks — huawei_cce_cluster_monitoring_aggregation gives a one-shot overview of all resource metrics with anomaly detection
  6. Correlate with events — if metrics show anomalies, check huawei-cloud-cce-kubernetes-event-analyzer for related warning events
  7. Hand off, don't remediate — this skill is read-only; hand off to diagnosis skills for root cause analysis
  8. Sanitize output — do not expose production pod names, node IPs, or cluster IDs in public summaries; use redacted examples

Reference Documents

Document Description
Workflow Metric query sequence, Pod/Node workflows, threshold detection, next-step handoff
Risk Rules Read-only constraints, data redaction rules, time-bounding, threshold caveats
Output Schema JSON response format for CCE metrics, cloud resource metrics, time-series, status values

Notes

  • This skill is strictly read-only — it only queries and analyzes metrics; no modifications are made to resources or configurations
  • Thresholds (CPU >80%, Memory >85%, Disk >85%) are predefined baselines — actual thresholds may vary by workload SLO; recommend users customize thresholds based on their specific requirements
  • 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 metric queries
  • 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 — forward to huawei-cloud-cce-auto-remediation-runner only if explicitly requested and validated

Common Pitfalls

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 exists; check CES IAM permission
Custom PromQL syntax error cpu_query / memory_query returns empty Use default auto-generated PromQL; only customize if familiar with AOM PromQL syntax
Permission denied on CES metrics Cloud resource metrics fail Verify ces:metricsData:get IAM permission
Aggregation missing time range start_time / end_time required but not provided Always specify both time boundaries for aggregation queries
Node IP format mismatch Single Node metrics fail Use the exact node IP as shown in cluster node listing (e.g. 10.0.0.1)