analyzing-dynamodb

name	analyzing-dynamodb
description	Use when working with Dynamodb — amazon DynamoDB table analysis, capacity mode evaluation, GSI/LSI usage, item access patterns, and cost optimization.
connection_type	aws
preload	false

DynamoDB Analysis Skill

Analyze and optimize DynamoDB tables with safe, read-only operations.

MANDATORY: Two-Phase Execution

You MUST follow this two-phase pattern. Skipping Phase 1 causes hallucinated table names and attribute errors.

Phase 1: Discovery (ALWAYS run first)

#!/bin/bash

# 1. List all tables in the region
aws dynamodb list-tables --output json | jq -r '.TableNames[]'

# 2. Describe target table (schema, capacity, indexes)
aws dynamodb describe-table --table-name "$TABLE_NAME" --output json | jq '{
  TableName: .Table.TableName,
  Status: .Table.TableStatus,
  ItemCount: .Table.ItemCount,
  TableSizeBytes: .Table.TableSizeBytes,
  BillingMode: .Table.BillingModeSummary.BillingMode,
  KeySchema: .Table.KeySchema,
  AttributeDefinitions: .Table.AttributeDefinitions,
  GSICount: (.Table.GlobalSecondaryIndexes | length // 0),
  LSICount: (.Table.LocalSecondaryIndexes | length // 0)
}'

# 3. Sample items to understand actual attribute names
aws dynamodb scan --table-name "$TABLE_NAME" --max-items 5 --output json | jq '.Items[0]'

Phase 1 outputs:

• List of tables in the account/region
• Table schema with key attributes and billing mode
• Sample items to understand actual attribute names

Phase 2: Analysis (only after Phase 1)

Only reference tables, attributes, and indexes confirmed in Phase 1.

Shell Script Patterns

Helper Function

#!/bin/bash

# Core DynamoDB helper — always use this
ddb_cmd() {
    aws dynamodb "$@" --output json
}

# Describe table helper
ddb_describe() {
    local table="$1"
    ddb_cmd describe-table --table-name "$table"
}

# CloudWatch metric helper for DynamoDB
ddb_metric() {
    local table="$1" metric="$2" stat="${3:-Sum}" period="${4:-300}"
    aws cloudwatch get-metric-statistics \
        --namespace AWS/DynamoDB \
        --metric-name "$metric" \
        --dimensions Name=TableName,Value="$table" \
        --start-time "$(date -u -v-1H +%Y-%m-%dT%H:%M:%S 2>/dev/null || date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%S)" \
        --end-time "$(date -u +%Y-%m-%dT%H:%M:%S)" \
        --period "$period" \
        --statistics "$stat" \
        --output json
}

Anti-Hallucination Rules

• NEVER reference a table name without confirming it exists via list-tables
• NEVER reference attribute names without seeing them in describe-table or a sample scan
• NEVER assume GSI/LSI names — always get them from describe-table
• NEVER guess capacity units — always read from table description or CloudWatch metrics
• NEVER assume billing mode — confirm on-demand vs provisioned from table description

Safety Rules

• READ-ONLY ONLY: Use only describe-table, list-tables, scan (with --max-items), query, get-item
• FORBIDDEN: create-table, delete-table, update-table, put-item, delete-item, batch-write-item without explicit user request
• ALWAYS add --max-items to scan operations — tables can have billions of items
• NEVER run full table scans on production without --max-items
• Use --select COUNT when you only need item counts, not full items

Common Operations

Table Health Overview

#!/bin/bash
echo "=== DynamoDB Tables ==="
TABLES=$(aws dynamodb list-tables --output json | jq -r '.TableNames[]')

for TABLE in $TABLES; do
    INFO=$(ddb_describe "$TABLE" | jq -r '.Table | "\(.TableName)\t\(.TableStatus)\t\(.ItemCount) items\t\((.TableSizeBytes/1024/1024)|round)MB\t\(.BillingModeSummary.BillingMode // "PROVISIONED")"')
    echo "$INFO"
done

echo ""
echo "=== Table Details: $TABLE_NAME ==="
ddb_describe "$TABLE_NAME" | jq '.Table | {
    KeySchema,
    AttributeDefinitions,
    BillingMode: .BillingModeSummary.BillingMode,
    ProvisionedThroughput: (if .BillingModeSummary.BillingMode == "PAY_PER_REQUEST" then "On-Demand" else .ProvisionedThroughput end),
    ItemCount,
    TableSizeMB: ((.TableSizeBytes/1024/1024)|round)
}'

GSI/LSI Analysis

#!/bin/bash
TABLE_NAME="$1"

echo "=== Global Secondary Indexes ==="
ddb_describe "$TABLE_NAME" | jq -r '.Table.GlobalSecondaryIndexes[]? | "\(.IndexName)\t\(.IndexStatus)\t\(.ItemCount) items\t\(.KeySchema | map(.AttributeName + "=" + .KeyType) | join(","))\tProjection=\(.Projection.ProjectionType)"'

echo ""
echo "=== Local Secondary Indexes ==="
ddb_describe "$TABLE_NAME" | jq -r '.Table.LocalSecondaryIndexes[]? | "\(.IndexName)\t\(.KeySchema | map(.AttributeName + "=" + .KeyType) | join(","))\tProjection=\(.Projection.ProjectionType)"'

echo ""
echo "=== GSI Capacity Utilization ==="
ddb_describe "$TABLE_NAME" | jq -r '.Table.GlobalSecondaryIndexes[]? | select(.ProvisionedThroughput) | "\(.IndexName)\tRCU=\(.ProvisionedThroughput.ReadCapacityUnits)\tWCU=\(.ProvisionedThroughput.WriteCapacityUnits)"'

Capacity & Throttling Analysis

#!/bin/bash
TABLE_NAME="$1"

echo "=== Consumed Read Capacity ==="
ddb_metric "$TABLE_NAME" "ConsumedReadCapacityUnits" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | "\(.Timestamp)\t\(.Sum)"'

echo ""
echo "=== Consumed Write Capacity ==="
ddb_metric "$TABLE_NAME" "ConsumedWriteCapacityUnits" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | "\(.Timestamp)\t\(.Sum)"'

echo ""
echo "=== Throttled Requests (last 1h) ==="
for METRIC in ReadThrottleEvents WriteThrottleEvents; do
    echo "--- $METRIC ---"
    ddb_metric "$TABLE_NAME" "$METRIC" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | select(.Sum > 0) | "\(.Timestamp)\t\(.Sum)"'
done

Access Pattern Analysis

#!/bin/bash
TABLE_NAME="$1"

echo "=== Successful Request Latency ==="
ddb_metric "$TABLE_NAME" "SuccessfulRequestLatency" "Average" 60 | jq -r '.Datapoints | sort_by(.Timestamp) | .[-5:][] | "\(.Timestamp)\t\(.Average)ms"'

echo ""
echo "=== System Errors ==="
ddb_metric "$TABLE_NAME" "SystemErrors" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | select(.Sum > 0) | "\(.Timestamp)\t\(.Sum)"'

echo ""
echo "=== User Errors ==="
ddb_metric "$TABLE_NAME" "UserErrors" "Sum" 300 | jq -r '.Datapoints | sort_by(.Timestamp) | .[] | select(.Sum > 0) | "\(.Timestamp)\t\(.Sum)"'

Cost Estimation

#!/bin/bash
TABLE_NAME="$1"

echo "=== Table Size & Item Count ==="
ddb_describe "$TABLE_NAME" | jq '.Table | {
    TableSizeGB: ((.TableSizeBytes/1024/1024/1024)*100|round/100),
    ItemCount: .ItemCount,
    BillingMode: .BillingModeSummary.BillingMode,
    StorageCostEstimate: "\(((.TableSizeBytes/1024/1024/1024)*0.25)*100|round/100) USD/month (at $0.25/GB)"
}'

echo ""
echo "=== GSI Storage Overhead ==="
ddb_describe "$TABLE_NAME" | jq '[.Table.GlobalSecondaryIndexes[]? | {IndexName, SizeGB: ((.IndexSizeBytes/1024/1024/1024)*100|round/100)}]'

Output Format

Present results as a structured report:

Analyzing Dynamodb 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.

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

• Scan vs Query: Scans read every item — always prefer Query with key conditions for production analysis
• Eventually consistent reads: Default reads are eventually consistent; specify --consistent-read only when needed
• GSI eventual consistency: GSI data is always eventually consistent — do not rely on immediate GSI updates
• Capacity calculation: 1 RCU = 1 strongly consistent read/s (4KB) or 2 eventually consistent reads/s; 1 WCU = 1 write/s (1KB)
• Hot partitions: Adaptive capacity helps but does not eliminate hot key issues — check partition key distribution
• Item size limit: 400KB per item — check for items approaching this limit
• --max-items vs --limit: --max-items limits CLI output (client-side); --limit limits DynamoDB scan (server-side and costs less RCU)