Service-mesh-based architectures provide visibility and control for microservices (a group of loosely coupled services that function together to make an application operate) by providing a consistent way to route and monitor traffic between them
In this post, we’ll explain how to use AWS App Mesh to provide visibility and control for microservices by providing a consistent way to route and monitor traffic between them.
The transaction logs from the archive location can be replayed on the standby database by manually applying the Rollforward command, or by setting up user exit programs.
In this approach, we configure the database parameter LOGARCHMETH1 with Amazon EFS as an archive location for transaction logs using the DISK option.
The low-latency streaming that this architecture provides to web users applies only to those users that are routed to the Azure public MEC that does the video processing and hosts the web app
Today we are announcing two new capabilities for Amazon Virtual Private Cloud (VPC) NAT gateway and Amazon Route 53, allowing your IPv6-only workloads to transparently communicate with IPV4-only services.
This is why we are launching two new capabilities allowing your IPv6 workloads to transparently communicate with IPv4 services: NAT64 (read “six to four”) for the VPC NAT gateway and DNS64 (also “six to four”) for the Amazon Route 53 resolver.
Today, we are announcing a new Amazon Relational Database Service (RDS) Multi-AZ deployment option with up to 2x faster transaction commit latency, automated failovers typically under 35 seconds, and readable standby instances.
When the new Multi-AZ DB cluster deployment option is enabled, RDS configures a primary database and two read replicas in three distinct Availability Zones.
The solution uses the Customizations for Control Tower framework and AWS Service Catalog to provision the DNS resources across a multi-account setup.
Cloud automation is a powerful method for reducing the amount of time and effort your team uses to configure cloud services.
In this blog post, we will show how a cross-account IAM assume role can be used to deploy AWS Lambda Serverless API code into pre-production and production environments.
PaaS is a cloud computing platform designed to enable organizations to deploy, provision and run applications without needing to build out the underlying infrastructure
Like many of the other PaaS options discussed here, Elastic Beanstalk is designed to act as a managed service that frees you from having to build out infrastructure or perform any complex configurations
Right now, the biggest business use cases for edge computing are for Internet of Things (IoT), artificial intelligence (AI) and big data, and other areas like virtual/augmented reality and streaming video optimization.
“Tell us what good looks like” is therefore a common request, with organizations seeking opinionated guidance and reference deployments to establish technical confidence and accelerate moving their mission-critical workloads to the Microsoft Cloud.
Our customers are transforming their digital environments, whether migrating workloads to Azure, building new cloud-native apps, or unlocking new scenarios at the edge.
Our new architecture needed to address the deficiencies while preserving the core goal of our service: update stateful artifacts based on incoming financial events.
We used an Apache Spark application on a long-running Amazon EMR cluster to simultaneously ingest input batch data and perform reduce operations to produce the stateless artifacts and a corresponding index file for the stateful processing to use.
In many ways, monitoring tools are like a patient’s pulse oximeter, and observability platforms are like the patient’s team of doctors that use the blood oxygen information to diagnose broader health issues.
