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azure-cosmos-db

Use when working with Azure Cosmos Db — azure Cosmos DB throughput analysis, partition key distribution, consistency levels, metrics monitoring, and database management via Azure CLI.

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SKILL.md(원문)

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Cosmos DB Skill

Manage and analyze Azure Cosmos DB accounts using az cosmosdb commands.

Discovery-First Rule

ALWAYS discover before acting. Never assume account names, database names, container names, or throughput values.

# Discover Cosmos DB accounts
az cosmosdb list --output json \
  --query "[].{name:name, rg:resourceGroup, kind:kind, apiKind:databaseAccountOfferType, locations:locations[].locationName, consistencyPolicy:consistencyPolicy.defaultConsistencyLevel}"

Parallel Execution Requirement

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

for acct in $(echo "$accounts" | jq -c '.[]'); do
  {
    name=$(echo "$acct" | jq -r '.name')
    rg=$(echo "$acct" | jq -r '.rg')
    az cosmosdb sql database list --account-name "$name" --resource-group "$rg" --output json
  } &
done
wait

Helper Functions

# List SQL databases in an account
list_databases() {
  local acct="$1" rg="$2"
  az cosmosdb sql database list --account-name "$acct" --resource-group "$rg" --output json \
    --query "[].{name:name, throughput:options.throughput, autoscaleMax:options.autoscaleMaxThroughput}"
}

# List containers in a database
list_containers() {
  local acct="$1" rg="$2" db="$3"
  az cosmosdb sql container list --account-name "$acct" --resource-group "$rg" --database-name "$db" --output json \
    --query "[].{name:name, partitionKey:resource.partitionKey.paths[0], indexingMode:resource.indexingPolicy.indexingMode, ttl:resource.defaultTtl}"
}

# Get container throughput
get_throughput() {
  local acct="$1" rg="$2" db="$3" container="$4"
  az cosmosdb sql container throughput show --account-name "$acct" --resource-group "$rg" \
    --database-name "$db" --name "$container" --output json \
    --query "{throughput:resource.throughput, autoscaleMax:resource.autoscaleMaximumThroughput, minimumThroughput:resource.minimumThroughput}"
}

# Get Cosmos DB metrics
get_cosmos_metrics() {
  local resource_id="$1" metric="$2"
  az monitor metrics list --resource "$resource_id" --metric "$metric" \
    --interval PT1H --aggregation Average Total --output json
}

Common Operations

1. Account and Database Overview

accounts=$(az cosmosdb list --output json --query "[].{name:name, rg:resourceGroup}")
for acct in $(echo "$accounts" | jq -c '.[]'); do
  {
    name=$(echo "$acct" | jq -r '.name')
    rg=$(echo "$acct" | jq -r '.rg')
    echo "=== Account: $name ==="
    az cosmosdb show --name "$name" --resource-group "$rg" --output json \
      --query "{consistency:consistencyPolicy.defaultConsistencyLevel, multiWrite:enableMultipleWriteLocations, locations:locations[].{loc:locationName, failoverPriority:failoverPriority}, backupPolicy:backupPolicy.type}"
    list_databases "$name" "$rg"
  } &
done
wait

2. Throughput Analysis

# Check RU consumption vs provisioned throughput
resource_id=$(az cosmosdb show --name "$ACCT" --resource-group "$RG" --query "id" -o tsv)
az monitor metrics list --resource "$resource_id" \
  --metric "TotalRequestUnits" "NormalizedRUConsumption" "ProvisionedThroughput" \
  --interval PT1H --aggregation Average Total Max --output json

# Check for 429 (throttled) requests
az monitor metrics list --resource "$resource_id" \
  --metric "TotalRequests" --interval PT1H --aggregation Count \
  --filter "StatusCode eq '429'" --output json

3. Partition Key Distribution

# Check partition key ranges and usage
az cosmosdb sql container show --account-name "$ACCT" --resource-group "$RG" \
  --database-name "$DB" --name "$CONTAINER" --output json \
  --query "{partitionKey:resource.partitionKey, conflictResolution:resource.conflictResolutionPolicy}"

# Get partition-level metrics (hot partitions)
az monitor metrics list --resource "$resource_id" \
  --metric "NormalizedRUConsumption" --interval PT5M --aggregation Max \
  --dimension "PartitionKeyRangeId" --output json

4. Consistency Level Review

# Check account-level consistency
az cosmosdb show --name "$ACCT" --resource-group "$RG" --output json \
  --query "{defaultConsistency:consistencyPolicy.defaultConsistencyLevel, maxStaleness:consistencyPolicy.maxStalenessPrefix, maxInterval:consistencyPolicy.maxIntervalInSeconds}"

5. Backup and Replication Status

az cosmosdb show --name "$ACCT" --resource-group "$RG" --output json \
  --query "{backupPolicy:backupPolicy, locations:locations[].{name:locationName, priority:failoverPriority, isZoneRedundant:isZoneRedundant}, enableAutomaticFailover:enableAutomaticFailover}"

Output Format

Present results as a structured report:

Azure Cosmos Db 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

ShortcutCounterWhy
"I'll skip discovery and check known resources"Always run Phase 1 discovery firstResource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"Follow the full discovery → analysis flowQuick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"Audit configuration explicitlyDefaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"Always check relevant metrics when availableAPI/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 errorAssumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

  1. Database vs container throughput: Throughput can be provisioned at database level (shared) or container level (dedicated). Check both.
  2. Autoscale misread: autoscaleMaximumThroughput is the max -- actual consumption may be much lower. Always check NormalizedRUConsumption metric.
  3. Partition hot spots: High NormalizedRUConsumption on a single partition range indicates a hot partition. Check partition key design.
  4. Consistency tradeoffs: Strong consistency doubles RU cost for reads in multi-region setups. Session is the default and usually sufficient.
  5. Serverless vs provisioned: Serverless accounts do not have throughput settings. Check capacityMode in account properties.

리뷰

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