📋 Tender Overview
Amazon Web Services Inc. AWS an Amazon.com Inc. company announced the general availability of three new serverless analytics offerings that make it even easier for customers to analyze vast amounts of data without having to configure scale or manage the underlying infrastructure. Todays announcements include new serverless offerings for Amazon EMR to enable customers to run analytics applications using open-source big data frameworks Apache Spark and Hive without having to manage the underlying infrastructure Amazon Managed Streaming for Apache Kafka Amazon MSK to simplify real-time data ingestion and streaming and Amazon Redshift to allow customers to run high-performance data warehousing and analytics workloads on petabytes of data without having to manage clusters. Along with other serverless analytics offerings from AWS such as Amazon QuickSight for business intelligence and AWS Glue for data integration the new offerings announced today make it significantly easier and more cost-effective for customers to modernize their infrastructure and analyze vast amounts of data without worrying about capacity planning or incurring excess costs by over-provisioning for peak demand. There are no upfront commitments or additional costs to use Amazon EMR Serverless Amazon MSK Serverless and Amazon Redshift Serverless and customers only pay for the precise capacity needed for their analytics workloads.By offering the most serverless options for data analytics in the cloudincluding options for data warehousing big data processing real-time data analysis data integration interactive dashboards and visualizations and morewe are making it even easier for customers to maximize the value of their data to drive innovation improve customer experiences and make better decisions faster said Swami Sivasubramanian vice president of Database Analytics and Machine Learning at AWS. With these new serverless options customers can run even the most variable and intermittent analytics workloads and expand the use of analytics throughout their organizations without worrying about provisioning or scaling capacityor incurring excess cost.AWS customers choose from a wide variety of purpose-built analytics services to derive maximum value from their organizations data including Amazon EMR for processing vast amounts of unstructured data using open-source big data frameworks like Apache Spark and Hive Amazon MSK for ingesting real-time data streams and Amazon Redshift for data warehousing. While many customers appreciate the fine-grained control these services offer a subset of customers with highly variable or intermittent workloads would prefer to have AWS manage the underlying infrastructure by automatically adding or subtracting resources based on application demand. To remove the complexity of scaling and managing infrastructure AWS introduced the concept of serverless event-driven computing in 2014. Many customers have since adopted serverless technologies on AWSincluding Amazon Kinesis Data Streams for real-time data streaming AWS Glue for data integration and Amazon QuickSight for interactive dashboards and visualizationsto take advantage of benefits like automatic provisioning on-demand scaling and pay-for-use pricing. With the new serverless offerings for Amazon EMR Amazon MSK and Amazon Redshift AWS offers the broadest set of serverless analytics capabilities in the cloud making it even easier for customers to lower costs expand analytics to more users and maximize their datas value.Serverless big data analytics with Amazon EMR Serverless Tens of thousands of customers use Amazon EMR to run open-source frameworks like Apache Spark and Hive for large-scale distributed data processing jobs interactive SQL queries and machine learning applications. Amazon EMR supports the most big data frameworks in the cloud enabling customers to run big data applications and petabyte-scale data analytics faster and at less than half the cost of on-premises solutions. With Amazon EMR Serverless customers can simply specify the framework they want to run and Amazon EMR Serverless automatically provisions manages and scales the necessary compute and memory resources as workload demands change. Customers can get started with Amazon EMR Serverless by simply selecting an open-source framework and submitting their jobs using the Amazon EMR application programming interface API the AWS Command Line Interface AWS CLI or an integrated development environment IDE with Amazon EMR Studio. Amazon EMR Serverless is generally available today to customers running Amazon EMR in US East N. Virginia US West Oregon Asia Pacific Tokyo and Europe Ireland with availability in additional AWS Regions coming soon. Serverless data streaming with Amazon MSK Serverless Todays organizations are increasingly adopting Apache Kafka to capture and analyze real-time data streams from Internet of Things IoT devices website clickstreams database logs and many other sources where dynamic data is continuously generated. With this new serverless option Amazon MSK Serverless now provisions manages and scales clusters automatically so customers no longer have to worry about capacity planning or unpredictable streaming workloads. To take advantage of Amazon MSK Serverless customers simply create a cluster in the Amazon MSK console set up a private and secure Apache Kafka endpoint and use new or existing Apache Kafka clients to stream data.
