With just a few clicks, teams can quickly and easily apply a policy that requires network traffic from branch offices to be routed through a specific network firewall before reaching cloud resources running in an AWS Region. AWS Cloud WAN also integrates with leading SD-WAN, network appliances and independent software vendors to make it easier for customers to connect their on-premises SD-WAN devices to AWS.
David Brown, Vice President of Amazon EC2 at AWS said, “As the edge of the cloud continues to be pushed outward, and more customers move their applications to AWS to become more agile, reduce complexity and save money, they need an easier way to evolve their networks to support a modern, distributed model that allows them to reach their customers and end users globally with high performance.”
Additionally, 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 data’s value.
- Enabling customers to run big data applications and petabyte-scale data analytics faster, Amazon EMR Serverless lets customers specify the framework they want to run and automatically provisions, manages and scales the necessary computation and memory resources as workload demands change.
- Analyzing real-time data streams from IoT devices, website clickstreams, database logs and many other sources, Amazon MSK Serverless provisions, manages and scales clusters automatically, so customers no longer have to worry about capacity planning or unpredictable streaming workloads.
- Collectively processing more than two exabytes of data with Amazon Redshift every day, Amazon Redshift Serverless now makes it even easier to get insights from data quickly without the need to manage data warehouse infrastructure.
Other serverless analytics offerings from AWS include Amazon QuickSight for business intelligence and AWS Glue for data integration.
Swami Sivasubramanian, Vice President of Database, Analytics and Machine Learning at AWS noted, “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 capacity—or incurring excess cost.”