azure-monitor

name	azure-monitor
description	Use when working with Azure Monitor — azure Monitor metrics querying, Log Analytics workspace management, alert rule configuration, action groups, and diagnostic settings via Azure CLI.
connection_type	azure
preload	false

Azure Monitor Skill

Manage and analyze Azure Monitor resources using az monitor commands.

Discovery-First Rule

ALWAYS discover before acting. Never assume workspace names, alert rule names, metric names, or action group names.

# Discover Log Analytics workspaces
az monitor log-analytics workspace list --output json \
  --query "[].{name:name, rg:resourceGroup, sku:sku.name, retentionDays:retentionInDays, dailyCapGB:workspaceCapping.dailyQuotaGb}"

# Discover metric alert rules
az monitor metrics alert list --output json \
  --query "[].{name:name, rg:resourceGroup, severity:severity, enabled:enabled, targetResource:scopes[0]}"

Parallel Execution Requirement

ALL independent operations MUST run in parallel using background jobs (&) and wait.

for ws in $(echo "$workspaces" | jq -c '.[]'); do
  {
    name=$(echo "$ws" | jq -r '.name')
    rg=$(echo "$ws" | jq -r '.rg')
    az monitor log-analytics workspace show --workspace-name "$name" --resource-group "$rg" --output json
  } &
done
wait

Helper Functions

# Run a Log Analytics query
run_log_query() {
  local workspace="$1" query="$2" timespan="${3:-PT1H}"
  az monitor log-analytics query --workspace "$workspace" --analytics-query "$query" --timespan "$timespan" --output json
}

# List available metrics for a resource
list_metrics() {
  local resource_id="$1"
  az monitor metrics list-definitions --resource "$resource_id" --output json \
    --query "[].{name:name.value, displayName:name.localizedValue, unit:unit, aggregations:supportedAggregationTypes}"
}

# Get metric values
get_metrics() {
  local resource_id="$1" metrics="$2" interval="${3:-PT1H}" aggregation="${4:-Average}"
  az monitor metrics list --resource "$resource_id" --metric $metrics \
    --interval "$interval" --aggregation $aggregation --output json
}

# List action groups
list_action_groups() {
  local rg="$1"
  az monitor action-group list --resource-group  --output json \
    --query 
}

Common Operations

1. Workspace Overview and Usage

workspaces=$(az monitor log-analytics workspace list --output json --query "[].{name:name, rg:resourceGroup, id:customerId}")
for ws in $(echo "$workspaces" | jq -c '.[]'); do
  {
    name=$(echo "$ws" | jq -r '.name')
    rg=$(echo "$ws" | jq -r '.rg')
    ws_id=$(echo "$ws" | jq -r '.id')
    az monitor log-analytics workspace show --workspace-name "$name" --resource-group "$rg" --output json \
      --query "{name:name, sku:sku.name, retentionDays:retentionInDays, dailyCap:workspaceCapping.dailyQuotaGb, ingestionStatus:workspaceCapping.quotaNextResetTime}"
    # Check data volume
    run_log_query "$ws_id" "Usage | where TimeGenerated > ago(24h) | summarize DataGB=sum(Quantity)/1024 by DataType | sort by DataGB desc | take 10" "P1D"
  } &
done
wait

2. Alert Rules Audit

# Metric alerts
az monitor metrics alert list --output json \
  --query "[].{name:name, severity:severity, enabled:enabled, condition:criteria.allOf[0].{metric:metricName,operator:operator,threshold:threshold}, actions:actions[].actionGroupId}"

# Log alerts (scheduled query rules)
az monitor scheduled-query list --output json \
  --query "[].{name:name, severity:severity, enabled:enabled, evaluationFrequency:evaluationFrequency, windowSize:windowSize}"

# Activity log alerts
az monitor activity-log alert list --output json \
  --query "[].{name:name, enabled:enabled, scopes:scopes, condition:condition}"

3. Log Analytics Queries

# Recent errors across all tables
run_log_query "$WORKSPACE_ID" "union withsource=TableName * | where TimeGenerated > ago(1h) | where Level == 'Error' or severityLevel >= 3 | summarize count() by TableName | sort by count_ desc"

# Heartbeat check for monitored VMs
run_log_query "$WORKSPACE_ID" "Heartbeat | summarize LastHeartbeat=max(TimeGenerated) by Computer | where LastHeartbeat < ago(15m)"

# Ingestion latency
run_log_query "$WORKSPACE_ID" "Heartbeat | where TimeGenerated > ago(1h) | extend IngestionDelay=ingestion_time()-TimeGenerated | summarize avg(IngestionDelay), max(IngestionDelay) by bin(TimeGenerated, 5m)"

4. Diagnostic Settings Audit

# Check diagnostic settings for a resource
az monitor diagnostic-settings list --resource "$RESOURCE_ID" --output json \
  --query "[].{name:name, workspace:workspaceId, storageAccount:storageAccountId, eventHub:eventHubAuthorizationRuleId, logs:logs[].{category:category, enabled:enabled, retention:retentionPolicy.days}, metrics:metrics[].{category:category, enabled:enabled}}"

5. Action Group Configuration

az monitor action-group list --output json \
  --query "[].{name:name, rg:resourceGroup, enabled:enabled, email:emailReceivers[].{name:name,address:emailAddress}, sms:smsReceivers[].{name:name,phone:phoneNumber}, webhook:webhookReceivers[].{name:name,uri:serviceUri}, logicApp:logicAppReceivers[].{name:name}, azureFunction:azureFunctionReceivers[].{name:name}}"

Output Format

Present results as a structured report:

Azure Monitor Report
════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

1. Metric namespaces: Different resource types expose different metrics. Always use list-definitions to discover available metrics before querying.
2. Log Analytics timespan format: Use ISO 8601 duration format (e.g., PT1H, P1D, P7D), not date ranges.
3. Daily cap resets: When daily ingestion cap is hit, data is dropped until the next reset time. Check quotaNextResetTime.
4. Alert action groups: An alert without action groups will fire but nobody gets notified. Always verify action group linkage.
5. KQL vs SQL: Log Analytics uses Kusto Query Language (KQL), not SQL. Common mistakes include using SELECT instead of project and GROUP BY instead of summarize.