AWS Certified Associate Changed Data-Engineer-Associate Questions

Athena workgroups are a way to isolate query execution and query history among users, teams, and applications that share the same AWS account. By creating a workgroup for each use case, the company can control the access and actions on the workgroup resource using resource-level IAM permissions or identity-based IAM policies. The company can also use tags to organize and identify the workgroups, and use them as conditions in the IAM policies to grant or deny permissions to the workgroup. This solution meets the requirements of separating query processes and access to query history among users, teams, and applications that are in the same AWS account. References:

Athena Workgroups

IAM policies for accessing workgroups

Workgroup example policies

Problem Analysis:

The company needs near real-time replication of MySQL updates to Amazon Redshift.

Minimal development effort is required for this solution.

Key Considerations:

AWSDMSprovides afull load + CDC (Change Data Capture)mode for continuous replication of database changes.

DMS integrates natively with both MySQL and Redshift, simplifying setup.

Solution Analysis:

Option A: AWS Glue Job

Glue is batch-oriented and does not support near real-time replication.

Option B: DMS with Full Load + CDC

Efficiently handles initial database load and continuous updates.

Requires minimal setup and operational overhead.

Option C: AppFlow SDK

AppFlow is not designed for database replication. Custom connectors increase development effort.

Option D: DataSync

DataSync is for file synchronization and not suitable for database updates.

Final Recommendation:

UseAWS DMSinfull load + CDCmode for continuous replication.

Problem Analysis:

The company usesDynamoDBfor gaming data storage and needs to ingest data intoAmazon OpenSearch Serviceinnear real time.

Data updates must propagate quickly to OpenSearch for analytics or search purposes.

Key Considerations:

DynamoDB Streamsprovide near-real-time capture of table changes (inserts, updates, and deletes).

Integration withAWS Lambdaallows seamless processing of these changes.

OpenSearch offers APIs for indexing and updating documents, which Lambda can invoke.

Solution Analysis:

Option A: Step Functions with Periodic Export

Not suitable for near-real-time updates; introduces significant latency.

Operationally complex to manage periodic exports and S3 data ingestion.

Option B: AWS Glue Job

AWS Glue is designed for ETL workloads but lacks real-time processing capabilities.

Option C: DynamoDB Streams + Lambda

DynamoDB Streams capture changes in near real time.

Lambda can process these streams and use the OpenSearch API to update the index.

This approach provides low latency and seamless integration with minimal operational overhead.

Option D: Custom OpenSearch Plugin

Writing a custom plugin adds complexity and is unnecessary with existing AWS integrations.

Implementation Steps:

EnableDynamoDB Streamsfor the relevant DynamoDB tables.

Create aLambda functionto process stream records:

Parse insert, update, and delete events.

Use OpenSearch APIs to index or update documents based on the event type.

Set up a trigger to invoke the Lambda function whenever there are changes in the DynamoDB Stream.

Monitor and log errors for debugging and operational health.

The AWS Transfer Family server's security policy can be updated to enforceTLS 1.2or higher, ensuring compliance with company policy for encrypted data transfers.

AWS Transfer Family Security Policy:

AWS Transfer Family supports setting aminimum TLS versionthrough its security policy configuration. This ensures that only connections using TLS 1.2 or above are allowed.