An AWS security best practice from The 5 Pillars of the AWS Well-Architected Framework is to ensure that data is protected both in transit and at rest. One option is to use SSL/TLS to encrypt data in transit, and use cryptographic keys to encrypt data at rest.
In the most recent season of BigQuery Spotlight , we discussed key concepts like the BigQuery Resource hierarchy , query processing , and the reservation model . This blog focuses on extending those concepts to operationalize workload management for various scenarios.
High Performance Computing (HPC), also called “Big Compute”, uses a large number of CPU or GPU-based computers to solve complex mathematical tasks. Many industries use HPC to solve some of their most difficult problems.
In today’s blog post, we’re diving a little deeper into the security foundations guide to highlight several best practices for security practitioners and platform teams to use with setting-up, configuring, deploying, and operating a security-centric infrastructure for their organization.
This blog post was co-authored by Amir Dahan, Senior Program Manager, Anupam Vij, Principal Program Manager, Skye Zhu, Data and Applied Scientist 2, and Syed Pasha, Principal Network Engineer, Azure Networking. In our 2020 retrospective , we highlighted shifts in the active cyberthreat landscape.
This blog post was co-written by Sudhir Amin, Sr. Solution Architect, AWS, and David Bermingham, Senior Technical Evangelist, SIOS Technology, Inc. To ensure high availability (HA) of Microsoft SQL Server in Amazon Elastic Compute Cloud (Amazon EC2), there are two options: Always On Failover Cluster Instance (FCI) and Always On availability groups .
The term big compute describes large-scale workloads that require a large number of cores, often numbering in the hundreds or thousands. Scenarios include image rendering, fluid dynamics, financial risk modeling, oil exploration, drug design, and engineering stress analysis, among others.
As organizations align their business with sustainable practices, it is important to review every functional area. If you’re building, deploying, and maintaining an IT stack, improving its environmental impact requires informed decision making.
This example workload shows how, using Azure platform as a service (PaaS) services, one can migrate a z/OS mainframe OLTP application to a secure, scalable, and highly available system in the cloud. Such a migration helps businesses in finance, health, insurance, and retail to minimize application delivery timelines, and it helps reduce the costs of running the applications.
In this blog post, we demonstrate how to build an automated and scalable data pipeline for autonomous driving. This solution was built with the goal of accelerating the process of analyzing recorded footage and training a model to improve the experience of autonomous driving.
This solution guide shows you how to deploy a hybrid app that spans both Azure and Azure Stack Hub and uses a single on-premises data source. By using a hybrid cloud solution, you can combine the compliance benefits of a private cloud with the scalability of the public cloud.
Many organizations face the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems.In this re:Invent session, we explored an architecture to solve this problem using Amazon EMR, Amazon S3, Amazon SageMaker Ground Truth, and more.
With IoT devices scaling up rapidly, real-time data integration and data processing has become a major challenge. This is why customers often choose Message Queuing Telemetry Transport (MQTT) for message ingestion, and Apache Kafka to build a real-time streaming data pipeline.
Sam (sysadmin) and Erin (developer) work at “Mindful Containers” , an imaginary company that sells sleeping pods for mindful breaks. One day, Sam calls Erin because her application has crashed during deployment, but it worked just fine on her workstation.
