Streaming analytics in AWS enables enterprises to process and analyze log data in real time, supporting use cases such as personalized customer experiences, anomaly detection, application troubleshooting, and user behavior analysis. With innovations like cloud computing, organizations are turning to public cloud providers like AWS for next-generation streaming analytics tools that can handle large volumes of log data generated continuously from thousands of sources. Amazon Kinesis is a key component of streaming analytics in AWS, providing serverless streaming data services that allow customers to capture, process, and store data streams in near real-time at any scale. Kinesis Data Streams, Firehose, and Analytics enable customers to collect, transform, and deliver log data to various destinations such as Amazon S3, Amazon Redshift, Amazon OpenSearch Service, Splunk, and others. While streaming analytics offers numerous benefits, it also comes with limitations such as the complexity of building and maintaining data pipelines and the cost of processing, storing, and analyzing data at scale. ChaosSearch can help address these limitations by transforming Amazon S3 into a log analytics data lake, providing multimodal data access, no unnecessary data movement, and no fragile ETL pipelines.