Category: Best Practices

A resilient auto scaling policy requires metrics that correlate with application utilization, which may not be tied to system resources. Traditionally, auto scaling policies track system resource such as CPU utilization. These metrics are easily available, but they only work when resource consumption correlates with worker capacity. Factors such as high variance in request processing time, mixed instance types, or natural changes in application behavior over time can break this assumption.

This post is part 3 of the three-part series ‘Enabling high availability of Amazon EC2 instances on AWS Outposts servers’. We provide you with code samples and considerations for implementing custom logic to automate Amazon Elastic Compute Cloud (EC2) relaunch on Outposts servers. This post focuses on guidance for using Outposts servers with third party storage for boot […]

Amazon Elastic Kubernetes Service (Amazon EKS) on AWS Outposts brings the power of managed Kubernetes to your on-premises infrastructure. Use Amazon EKS on Outposts rack to create hybrid cloud deployments that maintain consistent AWS experiences across environments. As organizations increasingly adopt edge computing and hybrid architectures, storage optimization and performance tuning become critical for successful workload deployment.

Organizations running critical workloads on Amazon Elastic Compute Cloud (Amazon EC2) reserve compute capacity using On-Demand Capacity Reservations (ODCR) to have availability when needed. However, reserved capacity can intermittently sit idle during off-peak periods, between deployments, or when workloads scale down. This unused capacity represents a missed opportunity for cost optimization and resource efficiency across the organization.

Amazon Web Services (AWS) provides many mechanisms to optimize the price performance of workloads running on Amazon Elastic Compute Cloud (Amazon EC2), and the selection of the optimal infrastructure to run on can be one of the most impactful levers. When we started building the AWS Graviton processor, our goal was to optimize AWS Graviton […]

Event-driven applications often need to process data in real-time. When you use AWS Lambda to process records from Apache Kafka topics, you frequently encounter two typical requirements: you need to process very high volumes of records in close to real-time, and you want your consumers to have the ability to scale rapidly to handle traffic spikes. Achieving both necessitates understanding how Lambda consumes Kafka streams, where the potential bottlenecks are, and how to optimize configurations for high throughput and best performance.

You can use AWS Step Functions to orchestrate complex business problems. However, as workflows grow and evolve, you can find yourself grappling with monolithic state machines that become increasingly difficult to maintain and update. In this post, we show you strategies for decomposing large Step Functions workflows into modular, maintainable components.

Amazon EC2 offers AMD-based instances built on multiple generations of AMD EPYC processors. This post focuses on optimization strategies for the 3rd and 4th generation families, which provide enhanced capabilities for compute and memory-intensive workloads.

Delightful developer experience is an important part of building serverless applications efficiently, whether you’re creating an automation script or developing a complex enterprise application. While AWS Lambda has transformed modern application development in the cloud with its serverless computing model, developers spend significant time working in their local environments. They rely on familiar IDEs, debugging […]

When expanding your Graviton deployment across multiple AWS Regions, careful planning helps you navigate considerations around regional instance type availability and capacity optimization. This post shows how to implement advanced configuration strategies for Graviton-enabled EC2 Auto Scaling groups across multiple Regions, helping you maximize instance availability, reduce costs, and maintain consistent application performance even in AWS Regions with limited Graviton instance type availability.