As Amazon Web Services Inc. moves further into 2022, the cloud giant is showing a clear focus on data services and serverless computing.
The company’s groundwork in both areas was unveiled in late November when it made a series of announcements during the annual re:Invent conference in Las Vegas. AWS followed this up today with general availability releases and a few new offerings announced during its Summit San Francisco event.
The latest news also demonstrates that AWS does not show any signs of slowing the pace when it comes to the release of new features for the cloud.
“In 2021 alone we added 3,084 significant services and features,” Swami Sivasubramanian (pictured), vice president for database, analytics and machine learning at AWS, said during his Summit keynote address. “Our focus at AWS is in enabling every application in the cloud. We are actually just getting started.”
Interactive data processing
Enabling every application requires a focus on being able to deliver access to the data needed to power microservices. AWS has been focused on providing tools for data integration, exploration and distributed processing.
General availability for AWS Glue Interactive Sessions was announced today as a way for data analysts and engineers to process information interactively using the Jupyter-based notebook or an integrated development environment of choice. The company also unveiled general availability of Glue Autoscaling, and a new feature called Glue Sensitive Data Detection to identify sensitive data types.
In addition to enhancements for AWS Glue, the company is also continuing to pursue a set of initiatives for making it easier to query data stores. Amazon QuickSight was launched in 2016 as a business intelligence tool for exploring data using natural language. QuickSight Q was added last year as a machine learning-powered capability to receive accurate answers and relevant visualizations.
AWS also announced a preview of QuickSight 1-Click Public Embedding that allows users to embed dashboards into public applications without the need for additional coding. “Developers want to bring analytics into every app they use,” Sivasubramanian said. “But this has been slowed by the need to move to another tool.”
AWS is also focused on bolstering its serverless portfolio. Observers in the serverless community sat up and took notice in November when the cloud giant announced that four of its cloud-based analytics platforms would be made available as serverless services.
Amazon Kinesis, EMR, Redshift and MSK were added to the serverless portfolio in what was viewed among some analysts as growing bridge between serverless and containers.
In addition, AWS announced the general availability of Amazon Aurora Serverless v2. This enhanced version of Aurora, a fully managed relational database engine compatible with MySQL and PostgreSQL, is designed to offer reduced latency for scaling up or down. It also appeals to developers who would prefer not to worry about database provisioning.
“Aurora continues to be the fastest-growing AWS service,” Sivasubramanian noted. “We wanted customers of all sizes to experience the benefits of serverless.”
AWS customers will now also be able to experience serverless through general availability of an improvement to SageMaker, the company’s machine learning platform. AWS announced SageMaker Serverless Inference, which Sivasubramanian positioned as a pay-as-you go service for machine learning model deployment. Users will be offered options such as Real Time Inference for workloads and Batch Transform for handling large batch datasets.
Sivasubramanian’s keynote at the AWS Summit came less than a month after he made news himself. The AWS executive was recently appointed by the U.S. Department of Commerce to the National AI Advisory Committee, chartered to advise the White House on a wide range of issues related to artificial intelligence. In addition to AWS, the Advisory Committee also includes representatives from Salesforce Inc., Microsoft Corp., Google LLC, and IBM Corp.