How to fix ThrottlingException: Rate exceeded in DynamoDB

// AWS SDK v3 for JavaScript automatically handles retries
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';

const client = new DynamoDBClient({
  region: 'us-east-1',
  maxAttempts: 10, // Default is 3, increase for high-throughput applications
});

// For custom retry logic:
const delay = (retryCount) => {
  const baseDelay = 50; // 50ms
  const maxDelay = 5000; // 5 seconds
  const delay = Math.min(maxDelay, baseDelay * Math.pow(2, retryCount));
  const jitter = delay * 0.1 * Math.random(); // Add 10% jitter
  return delay + jitter;
};

# Check current provisioned capacity
aws dynamodb describe-table --table-name YourTableName

# Update provisioned capacity
aws dynamodb update-table \
  --table-name YourTableName \
  --provisioned-throughput \
    'ReadCapacityUnits=100,WriteCapacityUnits=50'

# For global secondary indexes
aws dynamodb update-table \
  --table-name YourTableName \
  --global-secondary-index-updates \
    '[{
      "Update": {
        "IndexName": "YourIndexName",
        "ProvisionedThroughput": {
          "ReadCapacityUnits": 50,
          "WriteCapacityUnits": 25
        }
      }
    }]'

# Register scalable target
aws application-autoscaling register-scalable-target \
  --service-namespace dynamodb \
  --resource-id "table/YourTableName" \
  --scalable-dimension "dynamodb:table:ReadCapacityUnits" \
  --min-capacity 5 \
  --max-capacity 1000

# Create scaling policy for read capacity
aws application-autoscaling put-scaling-policy \
  --service-namespace dynamodb \
  --resource-id "table/YourTableName" \
  --scalable-dimension "dynamodb:table:ReadCapacityUnits" \
  --policy-name "ReadScalingPolicy" \
  --policy-type "TargetTrackingScaling" \
  --target-tracking-scaling-policy-configuration \
    '{
      "TargetValue": 70.0,
      "PredefinedMetricSpecification": {
        "PredefinedMetricType": "DynamoDBReadCapacityUtilization"
      },
      "ScaleOutCooldown": 60,
      "ScaleInCooldown": 300
    }'

// Example: Add random suffix to partition key
function getPartitionKey(userId) {
  const suffix = Math.floor(Math.random() * 10); // 0-9
  return `user-${userId}-${suffix}`;
}

// Example: Use composite key with timestamp
function getTimeBasedKey(entityId) {
  const hour = new Date().getHours();
  return `${entityId}-${hour}`;
}

// Example: Use write sharding for high-velocity data
function getShardedKey(streamId) {
  const shardId = streamId % 100; // Distribute across 100 shards
  return `stream-${shardId}`;
}

// Process BatchWriteItem with retry logic
async function batchWriteWithRetry(items, tableName) {
  let unprocessedItems = { [tableName]: items };

  while (Object.keys(unprocessedItems[tableName] || {}).length > 0) {
    const response = await dynamodb.batchWriteItem({
      RequestItems: unprocessedItems
    }).promise();

    unprocessedItems = response.UnprocessedItems || {};

    if (Object.keys(unprocessedItems).length > 0) {
      // Exponential backoff with jitter
      const delay = Math.min(5000, 50 * Math.pow(2, retryCount));
      await new Promise(resolve => setTimeout(resolve, delay));
    }
  }
}

// For transactions, use ClientRequestToken for idempotency
const transactionParams = {
  TransactItems: [
    { Put: { TableName: 'Table1', Item: item1 } },
    { Update: { TableName: 'Table2', Key: key2, UpdateExpression: 'SET #count = #count + :inc' } }
  ],
  ClientRequestToken: 'unique-transaction-id-' + Date.now()
};

# Switch table to on-demand mode
aws dynamodb update-table \
  --table-name YourTableName \
  --billing-mode PAY_PER_REQUEST

# Check current billing mode
aws dynamodb describe-table --table-name YourTableName \
  --query 'Table.BillingModeSummary.BillingMode'