managing-aws-dynamodb-deep

name	managing-aws-dynamodb-deep
description	Use when working with Aws Dynamodb Deep — aWS DynamoDB deep-dive management covering table configurations, capacity analysis, GSI/LSI health, auto-scaling policies, streams, backups, contributor insights, and TTL settings. Use when performing deep analysis of DynamoDB tables, optimizing capacity and throughput, debugging throttling, or auditing table configurations beyond basic inventory.
connection_type	aws
preload	false

AWS DynamoDB Deep-Dive Skill

Deep analysis of DynamoDB tables, capacity planning, index health, and operational metrics.

MANDATORY: Discovery-First Pattern

Always list tables and get basic descriptions before deep-diving.

Phase 1: Discovery

#!/bin/bash
export AWS_PAGER=""

echo "=== DynamoDB Tables ==="
TABLES=$(aws dynamodb list-tables --output text --query 'TableNames[]')
echo "$TABLES" | tr '\t' '\n'

echo ""
echo "=== Table Summary ==="
for table in $TABLES; do
  aws dynamodb describe-table --table-name "$table" --output text \
    --query "Table.[TableName,TableStatus,BillingModeSummary.BillingMode,ItemCount,TableSizeBytes,GlobalSecondaryIndexes[].IndexName|join(',',@)]" &
done
wait

echo ""
echo "=== Auto-Scaling Targets ==="
aws application-autoscaling describe-scalable-targets --service-namespace dynamodb --output text \
  --query 'ScalableTargets[].[ResourceId,ScalableDimension,MinCapacity,MaxCapacity]' 2>/dev/null | head -20

Phase 2: Analysis

#!/bin/bash
export AWS_PAGER=""

END_TIME=$(date -u +"%Y-%m-%dT%H:%M:%S")
START_TIME=$(date -u -d "7 days ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-7d +"%Y-%m-%dT%H:%M:%S")

echo "=== Throttle Events (7d) ==="
for table in $(aws dynamodb list-tables --output text --query 'TableNames[]'); do
  {
    read_throttle=$(aws cloudwatch get-metric-statistics --namespace AWS/DynamoDB --metric-name ReadThrottleEvents \
      --dimensions Name=TableName,Value="$table" \
      --start-time "$START_TIME" --end-time "$END_TIME" --period 604800 --statistics Sum \
      --output text --query 'Datapoints[0].Sum')
    write_throttle=$(aws cloudwatch get-metric-statistics --namespace AWS/DynamoDB --metric-name WriteThrottleEvents \
      --dimensions Name=TableName,Value="$table" \
      --start-time "$START_TIME" --end-time "$END_TIME" --period 604800 --statistics Sum \
      --output text --query 'Datapoints[0].Sum')
    printf "%s\tReadThrottles:%s\tWriteThrottles:%s\n" "$table" "${read_throttle:-0}" "${write_throttle:-0}"
  } &
done
wait

echo ""
echo "=== Consumed vs Provisioned Capacity ==="
 table  $(aws dynamodb list-tables --output text --query ); 
  {
    consumed_read=$(aws cloudwatch get-metric-statistics --namespace AWS/DynamoDB --metric-name ConsumedReadCapacityUnits \
      --dimensions Name=TableName,Value= \
      --start-time  --end-time  --period 604800 --statistics Average \
      --output text --query )
    consumed_write=$(aws cloudwatch get-metric-statistics --namespace AWS/DynamoDB --metric-name ConsumedWriteCapacityUnits \
      --dimensions Name=TableName,Value= \
      --start-time  --end-time  --period 604800 --statistics Average \
      --output text --query )
        
  } &



 
 
 table  $(aws dynamodb list-tables --output text --query ); 
  aws dynamodb describe-table --table-name  --output text \
    --query  2>/dev/null &



 
 
 table  $(aws dynamodb list-tables --output text --query ); 
  {
    stream=$(aws dynamodb describe-table --table-name  --output text \
      --query )
    ttl=$(aws dynamodb describe-time-to-live --table-name  --output text \
      --query )
        
  } &



 
 
aws dynamodb list-backups --output text \
  --query  |  -10

 
 
 table  $(aws dynamodb list-tables --output text --query ); 
  aws dynamodb describe-contributor-insights --table-name  --output text \
    --query  2>/dev/null &

Output Format

• Target ≤50 lines per output
• Use --output text --query for all commands
• Tab-delimited fields: TableName, Metric, Value
• Aggregate capacity metrics as averages over the period
• Never dump full table items -- show metadata and metrics only

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

• Billing mode: PAY_PER_REQUEST vs PROVISIONED -- capacity metrics differ significantly
• GSI throttling: GSIs have independent capacity -- throttled GSIs can cause table-level write throttling
• Hot partitions: Use Contributor Insights to identify hot partition keys
• On-demand scaling: On-demand tables can throttle if traffic exceeds 2x previous peak within 30 minutes
• Auto-scaling delay: Auto-scaling reacts to CloudWatch alarms with ~5 minute delay -- not instant
• Item size: Max 400KB per item -- check AverageItemSize from table description
• Stream retention: DynamoDB Streams retain data for 24 hours only -- process events promptly
• Backup types: AWS_BACKUP (managed by AWS Backup), SYSTEM (continuous backups), USER (on-demand)