Adam Selipsky, chief executive officer (CEO) of Amazon Web Services (AWS) kicked off day two of AWS re:Invent 2022 with a keynote speech that unveiled a plethora of integrations and innovations to AWS’s broad cloud offerings.
Speaking at The Venetian in Las Vegas, Selipsky began by highlighting AWS’ sustainability goals, reiterating the company’s commitment to power operations with 100 per cent renewable energy by 2025, and announced that AWS is aiming to be water positive by 2030. The company will reuse and recycle water used in direct operations and will report annually on its water use efficiency (WUE).
“We’re building sustainability into everything we do. And that includes working with you. We’re determined to be inventive, and relentless, as we work to make the cloud the cleanest, and the most energy efficient way to run all of your infrastructure and your businesses.” said Selipsky.
Cloud uptake and data management also shared centre stage in Selipsky’s keynote as he stressed the cost effectiveness, speed, efficiency, and flexibility of cloud services during unpredictable times, and highlighted innovation among partners adopting cloud.
Likening “the vast realm of data” to space, Selipsky said, “Just as the vastness and complexity of space means you can’t explore it with just one technology, the same is true for data.” Having the right tools to manage this scale and variety of data, integrations to combine data spread across different places, as well as governance and insights over that data are key.
Here are the tools and integrations announced during Selipsky’s keynote:
OpenSearch Serverless – This option allows businesses to run search and analytic workloads without having to configure or scale OpenSearch clusters, delivering fast data ingestion and query responses for even the most demanding and unpredictable workloads. With OpenSearch Serverless, businesses only pay for the resources consumed.
Integrations – The process of combining data across different places or ETL (extract transform load) is a “painful” one, Selipsky explained. AWS’ integrations, including Aurora/Redshift (available in preview) and Redshift/Apache Spark (generally available) announced on Tuesday, seek “to make it easier to do analytics and machine learning without having to deal with the ETL muck”. Or better, to create a “Zero ETL Future”.
Governance – AWS seeks to make it easy for the right people to access and share data when they need it, and balance control and access to ensure data is secure but not locked. Selipsky hence announced Amazon Data Zone (coming soon), designed to help catalog, discover, share and govern data across an organization. Users can also use it to collaborate with others to drive insights for their businesses.
Insights – To explore and analyze data, Selipsky announced ML-powered forecasting, available today, allowing a business user to forecast a metric, taking into account seasonality, anomalies, and outliers to aim to form the best forecast. With ‘why’ questions in queue, users can also dig down and understand past events and trends that impacted the forecast.
Security – A new capability – container run time threat detection – was added to GuardDuty, Amazon’s threat detection service that monitors AWS workloads for malicious activity and delivers findings for remediation. GuardDuty can “now detect threats from software running inside your container by monitoring operating system level behavior in the container itself.” said Selipsky.
Security data analytics – Selipsky announced the preview of Amazon Security Lake, to allow security teams to automatically access, collect and analyze periodic security data.
Chips – Following the launch of the third generation of AWS’s Graviton processors, designed to deliver end to end performance and energy efficiency, businesses have been able to achieve better price performance, Selipsky stated. AWS has now announced, in preview, Inf2 instances for EC2, designed to deliver the highest performance for machine learning training and other extreme workloads.
High performance computing – HPC is used to tackle massive workloads, such as those for drug discovery and energy utilization, which usually require large scale computation. For HPC workloads that require the modeling of complex structures, like wind turbines, concrete buildings and industrial equipment, AWS announced EC2 HPC 6id instances, designed to deliver “leading price performance for data and memory intensive HPC workloads, with higher memory bandwidth per core, faster local SSD storage, and enhanced networking with elastic fabric adapter,” boasted Selipsky.
- AWS Simspace Weaver – designed to run large scale space simulations
- Amazon Connect – A contact center in the cloud, including forecasting, planning and scheduling capabilities, contact agent performance management capabilities, and a user interface guiding agents to access all customer interactions for faster issue resolution.
- AWS Supply Chain – A new cloud application designed to improve supply chain visibility through actionable insights that help customers mitigate supply chain risks and reduce costs.
- AWS Clean Rooms – A new service allowing companies and their partners to collaborate and analyze shared data sets without exposing underlying raw data.
- Amazon Omics – A new service to store, query and analyze insights from genomic and other omics (the study of molecular data), which is often challenging to process and instrumental to scientific discovery. Amazon Omics is designed to support such large scale analysis involving large populations.
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