A company has a web application that is hosted on AWS. The application is behind an Amazon CloudFront distribution. A developer needs a dashboard to monitor error rates and anomalies of the CloudFront distribution as frequently as possible.
Which combination of steps should the developer take to meet these requirements? (Choose two.)
To effectively monitor error rates and anomalies of a CloudFront distribution in real-time, enabling real-time logs and creating a data stream in Amazon Kinesis Data Streams is essential. This setup allows for immediate data collection and processing. Additionally, sending the logs from the data stream to Amazon OpenSearch Service using an AWS Lambda function and then creating dashboards in OpenSearch Dashboards ensures that the developer can visualize and analyze the data quickly and accurately. This combination provides both real-time log monitoring and powerful analytic capabilities necessary for detecting anomalies and calculating error rates.
real-time logs + Kinesis Data Streams
https://docs.aws.amazon.com/opensearch-service/latest/developerguide/integrations.html#integrations-kinesis You can use OpenSearch Ingestion to directly load streaming data into your Amazon OpenSearch Service domain, without needing to use third-party solutions. You can load streaming data from Kinesis Data Streams to OpenSearch Service. New data that arrives in the data stream triggers an event notification to Lambda, which then runs your custom code to perform the indexing. Once the Lambda function is configured with Kinesis DataStreams, you can use OpenSearch Dashboards to create visualizations.