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IAM user

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Identity and access management

Cloud financial management

Product lifecycle management

Application portfolio management

Business innovation management

Increase the EC2 instance size during peak traffic. Write feedback data to Amazon Simple Notification Service (Amazon SNS). Subscribe the RDS database endpoint to the SNS topic.

Write feedback data to an Amazon Simple Queue Service (Amazon SQS) queue. Use EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SQS queue and process submissions into the database.

Write feedback data to Amazon Simple Notification Service (Amazon SNS). Subscribe the RDS database endpoint to the SNS topic. Use EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SNS topic.

Write feedback data to an Amazon Simple Queue Service (Amazon SQS) queue when the EC2 instance reaches CPU threshold limits. Use scheduled scaling of EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SQS queue and process submissions into the database.

Use the AWS Step Functions Map state in Inline mode to process each item sequentially within a single execution.

Use the AWS Step Functions Map state in Distributed mode to process each item in a separate execution for maximum scalability.

Use AWS Glue to dynamically scale Apache Spark workers for parallel data processing.

Use multiple AWS Lambda functions invoked concurrently via Amazon S3 event notifications.

Create an S3 access point for each department in the central account hosting the bucket. Restrict each access point to the respective VPC. Update the bucket policy to enforce access via access points.

Create an interface VPC endpoint for S3 in each department's VPC. Attach an endpoint policy allowing access to the S3 access point. Associate the endpoint with the VPC's security groups.

Establish a gateway endpoint for S3 in each department's VPC. Configure the endpoint policy to permit access to the S3 access point. Update the route tables to direct traffic through the gateway endpoint.

Deploy an S3 access point in each department's AWS account and link it to the central S3 bucket. Restrict each access point to the department's VPC. Modify the bucket policy to require access through these access points.

Create a gateway endpoint in the central account's VPC. Attach an endpoint policy allowing access to the S3 bucket. Update the route tables to route traffic via the gateway.

Deploy Amazon ElastiCache for Memcached to cache database queries.

Implement Amazon ElastiCache for Redis to reduce read latency.

Use RDS Proxy to manage database connections.

Migrate the database to Amazon Aurora MySQL.

Create an Amazon Aurora Replica.

Configure an RDS for MySQL read replica.

Contact AWS Support to request a provisioned throughput increase.

Use the AWS SDK to execute the write operations.

Analyze the application and reduce the number of write operations.

Retry the operation with exponential backoff.

Create a global secondary index (GSI) with category as the partition key and subcategory as the sort key.

Create a local secondary index (LSI) with category as the partition key and subcategory as the sort key.

Recreate the table. Add userID as the partition key and timestamp as the sort key. During table creation, add a local secondary index (LSI) with category as the partition key and subcategory as the sort key.

Update the queries to use Scan operations with category as the partition key and subcategory as the sort key.