Amazon CloudWatch Synthetics multi-browser support is now available in the AWS GovCloud (US-East, US-West) Regions. This expansion enables customers in these two regions to test and monitor their web applications using both Chrome and Firefox browsers. With this launch, you can run the same canary script across Chrome and Firefox when using Playwright-based canaries or Puppeteer-based canaries. CloudWatch Synthetics automatically collects browser-specific performance metrics, success rates, and visual monitoring results while maintaining an aggregate view of overall application health. This helps development and operations teams quickly identify and resolve browser compatibility issues that could affect application reliability. To learn more about configuring multi-browser canaries, see the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries.html in the Amazon CloudWatch Synthetics User Guide. 

Amazon CloudWatch agent now supports the collection of detailed performance metrics for NVMe local volumes on Amazon EC2 instances. These metrics give you insights into behavior and performance characteristics of your NVMe local storage. The CloudWatch agent can now be configured to collect and send detailed NVMe metrics to CloudWatch, providing deeper visibility into storage performance. The new metrics include comprehensive performance indicators such as queue depths, I/O sizes, and device utilization. These metrics are similar to the detailed performance statistics available for EBS volumes, providing a consistent monitoring experience across both storage types. You can create CloudWatch dashboards, set alarms, and analyze trends for your NVMe-based instance store volumes. Detailed performance statistics for Amazon EC2 instance store volumes via Amazon CloudWatch agent are available for all local NVMe volumes attached to Nitro-based EC2 instances in all AWS Commercial and AWS GovCloud (US) Regions. See the Amazon CloudWatch pricing page for CloudWatch pricing details. To get started with detailed performance statistics for Amazon EC2 instance store volumes in CloudWatch, see Collect Amazon EC2 instance store volume NVMe driver metrics in the Amazon CloudWatch User Guide. To learn more about detailed performance statistics for Amazon EC2 instance store volumes, see Amazon EC2 instance store volumes in the Amazon EC2 User Guide.

Amazon CloudWatch agent now supports the collection of detailed performance metrics for NVMe local volumes on Amazon EC2 instances. These metrics give you insights into behavior and performance characteristics of your NVMe local storage. The CloudWatch agent can now be configured to collect and send detailed NVMe metrics to CloudWatch, providing deeper visibility into storage performance. The new metrics include comprehensive performance indicators such as queue depths, I/O sizes, and device utilization. These metrics are similar to the https://docs.aws.amazon.com/ebs/latest/userguide/nvme-detailed-performance-stats.html, providing a consistent monitoring experience across both storage types. You can create CloudWatch dashboards, set alarms, and analyze trends for your NVMe-based instance store volumes. Detailed performance statistics for Amazon EC2 instance store volumes via Amazon CloudWatch agent are available for all local NVMe volumes attached to Nitro-based EC2 instances in all AWS Commercial and AWS GovCloud (US) Regions. See the https://aws.amazon.com/cloudwatch/pricing/ for CloudWatch pricing details. To get started with detailed performance statistics for Amazon EC2 instance store volumes in CloudWatch, see https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Container-Insights-metrics-instance-store-Collect.html in the Amazon CloudWatch User Guide. To learn more about detailed performance statistics for Amazon EC2 instance store volumes, see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/nvme-detailed-performance-stats.html in the Amazon EC2 User Guide.

Today, Amazon announced two new Amazon CloudWatch metrics that provide insight into when your application exceeds the I/O performance limits for your EC2 instance with attached EBS volumes. These two metrics, Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check, monitor if the driven IOPS or throughput is exceeding the maximum EBS IOPS or throughput that your instance can support. With these two new metrics at the instance level, you can quickly identify and respond to application performance issues stemming from exceeding the EBS-Optimized limits of your instance. These metrics will return a value of 0 (performance not exceeded) or a 1 (performance exceeded) when your workload is exceeding the EBS-Optimized IOPS or throughput limit of the EC2 instance. With Amazon CloudWatch, you can use these new metrics to create customized dashboards and set alarms that notify you or automatically perform actions based on these metrics, such as moving to a larger instance size or a different instance type that supports higher EBS-Optimized limits. The Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check metrics are available by default at a 1-minute frequency at no additional charges, for all Nitro-based Amazon EC2 instances with EBS volumes attached. You can access these metrics via the EC2 console, CLI, or CloudWatch API in all Commercial AWS Regions, including the AWS GovCloud (US) Regions and China Regions. To learn more about these CloudWatch metrics, please visit the EC2 CloudWatch Metrics documentation.

Today, Amazon announced two new Amazon CloudWatch metrics that provide insight into when your application exceeds the I/O performance limits for your EC2 instance with attached EBS volumes. These two metrics, Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check, monitor if the driven IOPS or throughput is exceeding the maximum EBS IOPS or throughput that your instance can support. With these two new metrics at the instance level, you can quickly identify and respond to application performance issues stemming from exceeding the https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-optimized.html. These metrics will return a value of 0 (performance not exceeded) or a 1 (performance exceeded) when your workload is exceeding the EBS-Optimized IOPS or throughput limit of the EC2 instance. With Amazon CloudWatch, you can use these new metrics to create customized dashboards and set alarms that notify you or automatically perform actions based on these metrics, such as moving to a larger instance size or a different instance type that supports higher EBS-Optimized limits. The Instance EBS IOPS Exceeded Check and Instance EBS Throughput Exceeded Check metrics are available by default at a 1-minute frequency at no additional charges, for all Nitro-based Amazon EC2 instances with EBS volumes attached. You can access these metrics via the EC2 console, CLI, or CloudWatch API in all Commercial AWS Regions, including the AWS GovCloud (US) Regions and China Regions. To learn more about these CloudWatch metrics, please visit the https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/viewing_metrics_with_cloudwatch.html#ebs-metrics-nitro.

Amazon CloudWatch Database Insights expands the availability of its on-demand analysis experience to the RDS for SQL Server database engine. CloudWatch Database Insights is a monitoring and diagnostics solution that helps database administrators and developers optimize database performance by providing comprehensive visibility into database metrics, query analysis, and resource utilization patterns. This feature leverages machine learning models to help identify performance bottlenecks during the selected time period, and gives advice on what to do next. Previously, database administrators had to manually analyze performance data, correlate metrics, and investigate root cause. This process is time-consuming and requires deep database expertise. With this launch, you can now analyze database performance monitoring data for any time period with automated intelligence. The feature automatically compares your selected time period against normal baseline performance, identifies anomalies, and provides specific remediation advice. Through intuitive visualizations and clear explanations, you can quickly identify performance issues and receive step-by-step guidance for resolution. This automated analysis and recommendation system reduces mean-time-to-diagnosis from hours to minutes. You can get started with this feature by enabling the Advanced mode of CloudWatch Database Insights on your RDS for SQL Server databases using the RDS service console, AWS APIs, the AWS SDK, or AWS CloudFormation. Please refer to https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.Engines.html and https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/USER_PerfInsights.Overview.Engines.html#USER_PerfInsights.Overview.PIfeatureEngnRegSupport for information regarding the availability of Database Insights across different regions, engines and instance classes. 

Amazon CloudWatch now helps you monitor large-scale distributed applications by automatically discovering and organizing services into groups based on configurations and their relationships. SREs and DevOps teams can identify critical dependencies and blast radius impacts to remediate issues faster. You get an always-on, out-of-the-box catalog and map that visualizes services and dependencies across AWS accounts and regions, organizing them into logical groups that align with how customers think about their systems—without manual configurations. You can also apply dynamic grouping based on how you organize applications—by teams, business units, criticality tiers, or other attributes. With this new application performance monitoring (APM) capability, customers can quickly visualize which applications and dependencies to focus on while troubleshooting their distributed applications. For example, SRE and DevOps teams can now accelerate root cause analysis and reduce mean-time-to-resolution (MTTR) through high-level operational signals such as SLOs, health indicators, changes, and top observations. The application map integrates with a contextual troubleshooting drawer that surfaces relevant metrics and actionable insights to accelerate triage. When deeper investigation is needed, teams can pivot to an application-specific dashboard tailored for troubleshooting. The map, drawer, and dashboard dynamically update as new services are discovered or as customers adjust how their environments are grouped—ensuring the view is always accurate and aligned with how teams operate. This new capability is now available in all AWS commercial regions where Application Signals have launched , at no additional cost. To learn more, please visit https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/ServiceMap.html

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Last week, Anthropic’s Claude Sonnet 4.5—the world’s best coding model according to SWE-Bench – became available in Amazon Q command line interface (CLI) and Kiro. I’m excited about this for two reasons: First, a few weeks ago I spent 4 intensive days with a global customer delivering an AI-assisted development workshop, where I experienced firsthand […]

AWS Toolkit for Visual Studio Code now includes Amazon CloudWatch Logs Live Tail, an interactive log streaming and analytics capability which provides real-time visibility into your logs, making it easier to develop and troubleshoot your serverless applications. The Toolkit for VS Code is an open-source extension for the Visual Studio Code (VS Code) editor. This extension makes it easier for developers to develop, debug locally, and deploy serverless applications that use AWS. This new integration brings the power of Live Tail directly into the VS Code Command Palette. CloudWatch log events can now be streamed in the VS Code Editor as they are ingested in real-time. You can search, filter, and highlight log events of interest, to aid and accelerate troubleshooting, investigations, and root cause analysis. Amazon CloudWatch Logs Live Tail for AWS Toolkit for Visual Studio Code is available in all AWS Commercial regions. To learn more, please visit the documentation. For pricing details, check Amazon CloudWatch Pricing.

To be honest, I’m still recovering from the AWS Summit in New York, doing my best to level up on launches like Amazon Bedrock AgentCore (Preview) and Amazon Simple Storage Service (S3) Vectors. There’s a lot of new stuff to learn! Meanwhile, it’s been an exciting week for AWS builders focused on reliability and observability. […]

Today, CloudWatch Synthetics, which allows monitoring of customer workflows on websites through periodically running custom code scripts, announces two new features: canary safe updates and automatic retries for failing canaries. The former allows you to test updates for your existing canaries before applying changes and the latter enables canaries to automatically attempt additional retries when a scheduled run fails, helping to differentiate between genuine and intermittent failures. Canary safe updates helps minimize potential monitoring disruptions caused by erroneous updates. By doing a dry run you can verify canary compatibility with newly released runtimes, or with any configuration or code changes. It minimizes potential monitoring gaps by maintaining continuous monitoring during update processes and mitigates risk to end user experience in the process of keeping canaries up-to-date. The automatic retries feature helps in reducing false alarms. When enabled, it provides more reliable monitoring results by distinguishing between persistent issues and intermittent failures preventing unnecessary disruption. Users can analyze temporary failures using the canary runs graph, which employs color-coded points to represent scheduled runs and their retries. You can start using these features by accessing CloudWatch Synthetics through the AWS Management Console, AWS CLI, or CloudFormation. Dry runs for safe canary updates and automatic retries are are priced the same as regular canary runs and are available in all commercial AWS Regions. To learn more about https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/performing-safe-canary-upgrades.html and automatic retries visit the linked Amazon CloudWatch Synthetics documentation. Or get started with Synthetics monitoring by visiting the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries.html.

CloudWatch Database Insights announces support of databases hosted on Amazon Relational Database Service (RDS). Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health. Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights. You can get started with Database Insights by enabling it on your RDS databases using the RDS service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. Database Insights is available in all public AWS Regions and applies a new vCPU-based pricing – see pricing page for details. For further information, visit the Database Insights documentation.

Gain deep visibility into AWS Lambda performance with CloudWatch Application Signals, eliminating manual monitoring complexities and improving serverless app health.

AWS announces the general availability of Amazon CloudWatch Database Insights with support for Amazon Aurora PostgreSQL and Amazon Aurora MySQL. Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health. Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights. You can get started with Database Insights by enabling it on your Aurora clusters using the Aurora service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. Database Insights is available in all public AWS Regions and applies a new vCPU-based pricing – see pricing page for details. For further information, visit the Database Insights documentation.

Amazon CloudWatch Database Insights now collects the query execution plans of top SQL queries running on Aurora PostgreSQL instances, and stores them over time. This feature helps you identify if a change in the query execution plan is the cause of performance degradation or a stalled query. Execution plan capture for Aurora PostgreSQL is available exclusively in the Advanced mode of CloudWatch Database Insights. A query execution plan is a sequence of steps that database engines use to retrieve or modify data in a relational database management system (RDBMS). The RDBMS query optimizers may not always choose the most optimal execution plan from a set of alternative ways to execute a given query. Hence, database users sometimes need to manually examine and tune the plans to improve performance. This feature allows you to visualize multiple plans of a SQL query and compare them. It can help you determine if a change in performance of a SQL query is due to a different query execution plan within minutes. You can get started with this feature by enabling Database Insights Advanced mode on your Aurora PostgreSQL clusters using the RDS service console, AWS APIs, or the AWS SDK. CloudWatch Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. CloudWatch Database Insights is available in https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ and offers vCPU-based pricing – see the https://aws.amazon.com/cloudwatch/pricing/ for details. For further information, visit thehttps://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Database-Insights.html

Amazon Q Developer can now help you investigate and remediate operational issues quickly from anywhere in the AWS Management Console, accelerating the troubleshooting process for operators of all experience levels.

Amazon CloudWatch now lets customers evaluate metrics data for an extended duration of up to 7 days, a 7x increase from the previous limit of 24 hours. This enhancement empowers customers to monitor the health of longer-running or infrequent processes, such as daily data loading jobs or day-over-day performance trends, offering deeper insights into their resources and applications. Customers now have the flexibility to leverage CloudWatch alarms for use cases like near-real-time metric tracking as well as for monitoring patterns that span multiple days. Amazon CloudWatch alarming on multi-day data is now available in all AWS Regions including the AWS GovCloud (US) Regions. To alarm on multiple days of data, create or update an alarm using the CloudWatch console or Command Line Interface (CLI), specify a period of at least 3,600 (1 hour) and the number of datapoints that you want to compare against the threshold. For more information, visit the CloudWatch alarms documentation section.

Amazon CloudFront announces enhancements to its standard access logging capabilities, providing customers with new log configuration and delivery options. Customers can now deliver CloudFront access logs directly to two new destinations: Amazon CloudWatch Logs and Amazon Data Firehose. Customers can select from an expanded list of log output formats, including JSON and Apache Parquet (for logs delivered to S3). Additionally, they can directly enable automatic partitioning of logs delivered to S3, select specific log fields, and set the order in which they are included in the logs. Until today, customers had to write custom logic to partition logs, convert log formats, or deliver logs to CloudWatch Logs or Data Firehose. The new logging capabilities provide native log configurations, eliminating the need for custom log processing. For example, customers can now directly enable features like Apache Parquet format for CloudFront logs delivered to S3 to improve query performance when using services like Amazon Athena and AWS Glue. Additionally, customers enabling access log delivery to CloudWatch Logs will receive 750 bytes of logs free for each CloudFront request. Standard access log delivery to Amazon S3 remains free. Please refer to the 'Additional Features' section of the CloudFront pricing page for more details. Customers can now enable CloudFront standard logs to S3, CloudWatch Logs and Data Firehose through the CloudFront console or APIs. CloudFormation support will be coming soon. For detailed information about the new access log features, please refer to the Amazon CloudFront Developer Guide.

Amazon CloudWatch Database Insights now provides lock contention diagnostics for Aurora PostgreSQL instances. This feature helps you identify the root cause behind both ongoing and historical lock contention issues within minutes. The lock contention diagnostics feature is available exclusively in the Advanced mode of CloudWatch Database Insights. With this launch, you can visualize a locking condition in the Database Insights console, which shows the relationship between blocking and waiting sessions. The visualization helps you quickly identify the dominating sessions, queries, or objects causing lock contention. Additionally, this feature persists historical locking data for 15 months, allowing you to analyze and investigate historical locking conditions. You no longer need to manually run custom queries or rely on application logs to diagnose lock contention issues, streamlining the troubleshooting process. You can get started with this feature by enabling the Advanced mode of CloudWatch Database Insights on your Aurora PostgreSQL clusters using the Aurora service console, AWS APIs, or the AWS SDK. CloudWatch Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. CloudWatch Database Insights is available in all public AWS Regions and offers vCPU-based pricing – see the pricing page for details. For further information, visit the Database Insights documentation.

CloudWatch Application Signals, an application performance monitoring (APM) tool that simplifies health and performance monitoring for applications now supports the ability to monitor your applications' services and Service Level Objectives (SLOs) across multiple source accounts from one monitoring account. Centralized application observability across accounts in a region provides single-pane-of-glass tracking, health maintenance, and resource optimization. Customers can use Amazon CloudWatch Observability Access Manager (OAM) to create and manage links between source accounts and monitoring accounts. Using the Application Signals Console in their monitoring account, customers can now view all services and SLOs to analyze and track broad patterns across multiple accounts. They can also set SLOs in the monitoring account. The multi account monitoring feature balances centralized monitoring with access restrictions required by their teams. Cross Account support for Application Signals is available in all https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Application-Monitoring-Sections.html is generally available. See https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Unified-Cross-Account.html to learn more. Customers can now opt in to the new bundled pricing for Application Signals. For pricing, see https://aws.amazon.com/cloudwatch/pricing/.

Today, CloudWatch RUM, a real-time monitoring service that visualizes and analyzes user interactions with web applications, announces support for Interaction to Next Paint (INP) web vital monitoring. This crucial metric would help customers measure the latency of a page's response to user interactions, offering insights into the end-user experience of their web application. INP is a metric that assesses a page's overall responsiveness to user interactions by observing the latency of all click, tap, and keyboard interactions that occur throughout the lifespan of a user's visit to a page. The final INP value is the longest interaction observed, ignoring outliers. This new metric joins the existing set of core web vitals tracked by CloudWatch RUM. The time series graph for INP allows customers to instantly assess whether page responsiveness is positive, tolerable, or frustrating based on a percentile aggregate of the metric. Furthermore, customers can click on specific data points to access a list of correlated INP events, leading them directly to affected user sessions for in-depth analysis of issues and their impact on user experience. Users can start capturing INP by upgrading the aws-rum-web to v1.23.0 at minimum, which is now available via NPM and CDN. The new INP metric is available in all AWS Regions where CloudWatch RUM is available at no additional cost to customers. To learn how to configure the the CloudWatch RUM web client visit this documentation or get started using the user guide.

Amazon CloudWatch now helps you monitor large-scale distributed applications by automatically discovering and organizing services into groups based on configurations and their relationships. SREs and DevOps teams can identify critical dependencies and blast radius impacts to remediate issues faster. You get an always-on, out-of-the-box catalog and map that visualizes services and dependencies across AWS accounts and regions, organizing them into logical groups that align with how customers think about their systems—without manual configurations. You can also apply dynamic grouping based on how you organize applications—by teams, business units, criticality tiers, or other attributes. With this new application performance monitoring (APM) capability, customers can quickly visualize which applications and dependencies to focus on while troubleshooting their distributed applications. For example, SRE and DevOps teams can now accelerate root cause analysis and reduce mean-time-to-resolution (MTTR) through high-level operational signals such as SLOs, health indicators, changes, and top observations. The application map integrates with a contextual troubleshooting drawer that surfaces relevant metrics and actionable insights to accelerate triage. When deeper investigation is needed, teams can pivot to an application-specific dashboard tailored for troubleshooting. The map, drawer, and dashboard dynamically update as new services are discovered or as customers adjust how their environments are grouped—ensuring the view is always accurate and aligned with how teams operate. This new capability is now available in all AWS commercial regions where Application Signals have launched , at no additional cost. To learn more, please visit CloudWatch Application Signals documentation.

Today, AWS announces general availability support for 10 new Amazon CloudWatch metrics in AWS End User Messaging for the SMS and MMS channel. AWS End User Messaging provides developers with a scalable and cost-effective messaging infrastructure without compromising the safety, security, or results of their communications. You can now use CloudWatch metrics to monitor SMS and MMS message performance. The new metrics allow you to track the number of messages sent and delivered, messages feedback rates such as one-time passcodes conversions, and track messages blocked by SMS protect. Customers can use CloudWatch Metrics Insights to graph and identify trends in real time and monitor those trends directly in the AWS End User Messaging console or in Amazon CloudWatch. To learn more, visit the AWS End User Messaging SMS https://docs.aws.amazon.com/sms-voice/latest/userguide/what-is-service.html  

AWS announces VPC endpoints for Amazon CloudWatch Observability Access Manager (OAM). CloudWatch OAM enables you to programmatically manage cross-account observability settings within a region. The new VPC endpoints enhance your security posture by keeping traffic between your VPC and CloudWatch OAM within the AWS network, eliminating the need to traverse the public internet. You can use Observability Access Manager to create and manage links between source accounts and monitoring accounts, enabling you to monitor and troubleshoot applications that span multiple accounts within a Region. With the new VPC endpoints, you can establish secure, private, and reliable connections between your VPC and CloudWatch Observability Access Manager. This allows you to maintain private connectivity while managing cross-account observability links and sinks, even from VPCs without internet access. This feature supports both IPv4 and IPv6 addressing, and you can use AWS PrivateLink's built-in security controls—like security groups and VPC endpoint policies—to help secure access to your observability resources. CloudWatch Observability Access Manager VPC endpoints are now available in all commercial AWS regions, the AWS GovCloud (US) Regions, and the China Regions. To start using VPC endpoints for CloudWatch Observability Access Manager, refer to CloudWatch OAM endpoints for a list of supported Regional endpoints. To learn more about AWS PrivateLink, see accessing AWS services through AWS PrivateLink.