Category: Amazon CloudWatch

Application performance monitoring (or APM) is the practice of taking key application performance indicators to ensure system availability, improve system performance, and improve the end-user experience. This week we announced Amazon CloudWatch Application Signals, a new set of features built-in to Amazon CloudWatch to help you speed up troubleshooting, reduce application disruptions, and operational costs, […]

Observability describes how well you can understand what is happening in a system, often by instrumenting it to collect metrics, logs, and traces. To achieve operational excellence and meet business objectives, you need to understand how your systems are performing. In order to accomplish this, many customers use Amazon CloudWatch to get real-time monitoring, alerts […]

To support business and internal processes, organizations are increasing their use of conversational interfaces. They offer opportunities for more availability, improved service levels, and reduced costs. As these conversational services become more important, so, does the need to monitor performance and effectiveness of these interfaces with analytics and dashboards. This analysis is used to drive […]

As machine learning (ML) workloads continue to grow in popularity, many customers are looking to run them on Kubernetes with graphics processing unit (GPU) support. Amazon Elastic Compute Cloud (Amazon EC2) instances powered by NVIDIA GPUs deliver the scalable performance needed for fast ML training and cost-effective ML inference. Monitoring GPU utilization gives valuable information for researchers working […]

Amazon CloudWatch Container Insights is a fully managed monitoring and observability service that provides DevOps engineers, developers, SREs, and IT managers with out-of-the-box visibility into their containerized applications and microservice environments. With Amazon CloudWatch Container Insights, you can monitor, isolate, and diagnose issues in your Kubernetes clusters with minimal effort. It delivers infrastructure telemetry like […]

Customers running microservice-based workloads in a serverless environment frequently have issues with troubleshooting incidents as the data they need can be distributed across hundreds or thousands of components. In this blog post, I will demonstrate how you can reduce the mean time to resolution (MTTR, or the average time it takes to repair or mitigate […]

Overview Maintaining and improving end user experience is key and as your business grows, the number of endpoints you need to observe can grow quickly. It can become more challenging and time consuming to build multiple canaries to observe them. This solution is designed to show how you can use a consistent and automated approach […]

Introduction In this blog post, we will share how you can use AWS-native observability tools to measure the current state of your modern serverless applications and how to get started with the minimal effort. We will review tools like Amazon CloudWatch and AWS X-Ray and explore how these services can help you instrument your application […]

Amazon Bedrock is an easy way to build and scale generative AI applications with foundation models (FMs). As a fully managed service, it offers a choice of high-performing FMs from leading AI companies including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon. It also offers a broad set of capabilities needed to build generative […]

Introduction Lambda@Edge is a powerful feature of Amazon CloudFront that allows you to execute serverless code closer to your application users, resulting in improved performance and reduced latency. By distributing Lambda@Edge functions to edge locations worldwide, AWS ensures that the code executes closer to end users, providing faster response times. Moreover, the serverless nature of […]