AWS Cloud Operations Blog
Category: Amazon CloudWatch
How Cigna Implemented a Multi-Region Centralized Alerting System on AWS
This post is co-written with Nicolas Trettel, Cloud Engineering Senior Advisor at Cigna. Monitoring applications and alerting on issues is crucial for building resilient systems. Amazon CloudWatch is a service that monitors applications, responds to performance changes, optimizes resource use, and provides insights into operational health. By collecting data across AWS resources, CloudWatch gives visibility […]
Support for Amazon CloudWatch Evidently ending soon
After careful consideration, we have made the decision to discontinue CloudWatch Evidently, effective 10/17/2025. Active customers will be able to use the service as normal until 10/17/2025, when support for the service will end. During this period, we will continue to provide critical security patches, but will no longer support any limit increase requests. On […]
Analyzing your custom metrics spend contributors in Amazon CloudWatch
With an ever-growing volume of custom metrics in Amazon CloudWatch, customers often find it difficult to understand and manage their spend on this service. One of the most common questions they have is how to identify which metrics contribute the most to their spend in CloudWatch. This blog post introduces a solution that lets you […]
Enhanced dashboard, latency suggestions in Amazon CloudWatch Internet Monitor
Amazon CloudWatch Internet Monitor provides near-continuous internet measurements for your internet traffic, including availability and performance metrics, tailored to your specific workload footprint on AWS. With Internet Monitor, you can get insights into average internet performance metrics over time, as well as get alerts for issues (health events). You’re notified about events that impact your end […]
Managing access to AWS accounts from Microsoft Teams and Slack at scale using AWS Organizations and AWS Chatbot
Customers use chat collaboration applications like Microsoft Teams and Slack to collaborate and manage their AWS applications. AWS Chatbot is a ChatOps service that enables customers to monitor, troubleshoot issues, and manage AWS applications from chat channels. AWS Chatbot provides autonomy and customizability to DevOps teams operating their AWS environments on the go from chat […]
Ten features for efficiently managing your AWS applications from Microsoft Teams and Slack using AWS Chatbot
Ten features in AWS Chatbot to help you understand your application health and resolve issues faster from chat channels.
How Amazon CloudWatch Logs Data Protection can help detect and protect sensitive log data
Customer applications running on Amazon Web Services (AWS) often require handling sensitive data such as personally identifiable information (PII) or protected health information (PHI). As a result, sensitive log data can be intentionally or unintentionally logged as part of an application’s observability data. While comprehensive logging is important for application troubleshooting, monitoring and forensics, any […]
Using Generative AI to Gain Insights into CloudWatch Logs
Have you ever been investigating a problem and opened up a log file and thought “I have no idea what I am looking at. If only I could get a summary of the data.” Observability and log data play an important role in maintaining operational excellence and ensuring the reliability of your applications and services. […]
AWS named as a Challenger in the 2024 Gartner Magic Quadrant for Observability Platforms
AWS has been named as a Challenger in the 2024 Gartner Magic Quadrant for Observability Platforms, previously known as Gartner Application Performance Monitoring (APM) and Observability Magic Quadrant. This report assesses vendors based on their Ability to Execute and Completeness of Vision. Compared to the previous year, AWS has moved up higher on the Ability […]
Improve Amazon Bedrock Observability with Amazon CloudWatch AppSignals
With the pace of innovation with Generative AI applications, there is increasing demand for more granular observability into applications using Large Language Models (LLMs). Specifically, customers want visibility into: Prompt metrics like token usage, costs, and model IDs for individual transactions and operations, apart from service-level aggregations. Output quality factors including potential toxicity, harm, truncation […]