Use Amazon Kinesis Data Streams to ingest the events and process them with AWS Lambda, index the results in Amazon OpenSearch Service for search and analytics, and create dashboards with Amazon Managed Grafana is correct because it pairs a managed, low latency ingest service with serverless processing and a search engine and it supports seconds‑level freshness with minimal operational overhead.

Amazon Kinesis Data Streams provides high throughput and low end to end latency so it can handle 300,000 events per minute and meet a 10 second freshness target and AWS Lambda scales processing without managing servers so you can perform record transformation and enrichment in near real time. Amazon OpenSearch Service is built for near real time indexing and full text search and it supports aggregations and analytics for interactive queries. Amazon Managed Grafana integrates with OpenSearch and provides rich, managed dashboards so stakeholders can view searchable, seconds fresh dashboards with low operational burden.

Use Amazon EC2 instances to ingest and process the event stream into Amazon S3 for storage, then use AWS Glue to catalog the data and Amazon Athena for querying, and visualize with Amazon QuickSight is not ideal because EC2 increases operational overhead and storing to S3 with Athena is a query on read pattern that is best for batch or microbatch workloads and it will struggle to deliver sub 10 second searchable dashboards.

Use Amazon MSK (Managed Streaming for Apache Kafka) for ingestion, land the data in Amazon Redshift for analysis, run external queries with Redshift Spectrum, and build visuals in Amazon QuickSight can handle high volume streaming but Redshift and Spectrum are designed for analytics over larger, batched or microbatched datasets and Redshift is not a search engine so it will not provide low latency, full text search and the same interactive search experience as OpenSearch.

Use Amazon EMR to handle stream processing, store records in Amazon DynamoDB, query with DynamoDB, and create dashboards in Amazon CloudWatch is a poor match because EMR adds operational complexity, DynamoDB is a key value and document database that is not optimized for full text search and complex aggregations, and CloudWatch dashboards are metric oriented and do not provide the same searchable, analytics focused dashboards as a Grafana plus OpenSearch combination.

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