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1 hour ago

AWS Direct Connect adds CloudWatch metrics for BGP monitoring AWS Direct Connect now publishes three new Amazon CloudWatch metrics for virtual interfaces (VIFs) that provide visibility into Border Gateway Protocol (BGP) session health and route counts. Network engineers and operations teams managing hybrid cloud connectivity can now monitor BGP sessions natively through CloudWatch without building custom solutions or polling APIs. These metrics solve critical monitoring gaps that previously required custom Lambda functions or on-premises network management tools. VirtualInterfaceBgpStatus reports BGP session state, enabling detection when sessions fail. VirtualInterfaceBgpPrefixesAccepted tracks prefixes from your on-premises network, allowing proactive alarms before reaching prefix limits that would cause BGP sessions to enter idle state. VirtualInterfaceBgpPrefixesAdvertised monitors routes AWS advertises to your network, helping validate configuration changes and detect silent route withdrawals that impact traffic even when BGP sessions remain up. These metrics are available for private, public, and transit virtual interfaces in all commercial AWS Regions. You can integrate them with CloudWatch alarms, dashboards, and Amazon SNS for comprehensive BGP monitoring, reducing mean time to detect network issues and simplifying operations for multi-region and disaster recovery architectures. To learn more about AWS Direct Connect, visit https://aws.amazon.com/directconnect/.

🆕 AWS Direct Connect adds three CloudWatch metrics for BGP monitoring on virtual interfaces, improving session health and route visibility, simplifying network management. Metrics cover session state, prefix tracking, and route advertising. Available globa…

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1 hour ago

AWS Direct Connect adds CloudWatch metrics for BGP monitoring AWS Direct Connect now publishes three new Amazon CloudWatch metrics for virtual interfaces (VIFs) that provide visibility into Border Gateway Protocol (BGP) session health and route counts. Network engineers and operations teams managing hybrid cloud connectivity can now monitor BGP sessions natively through CloudWatch without building custom solutions or polling APIs. These metrics solve critical monitoring gaps that previously required custom Lambda functions or on-premises network management tools. VirtualInterfaceBgpStatus reports BGP session state, enabling detection when sessions fail. VirtualInterfaceBgpPrefixesAccepted tracks prefixes from your on-premises network, allowing proactive alarms before reaching prefix limits that would cause BGP sessions to enter idle state. VirtualInterfaceBgpPrefixesAdvertised monitors routes AWS advertises to your network, helping validate configuration changes and detect silent route withdrawals that impact traffic even when BGP sessions remain up. These metrics are available for private, public, and transit virtual interfaces in all commercial AWS Regions. You can integrate them with CloudWatch alarms, dashboards, and Amazon SNS for comprehensive BGP monitoring, reducing mean time to detect network issues and simplifying operations for multi-region and disaster recovery architectures. To learn more about AWS Direct Connect, visit https://aws.amazon.com/directconnect/.

AWS Direct Connect adds CloudWatch metrics for BGP monitoring

AWS Direct Connect now publishes three new Amazon CloudWatch metrics for virtual interfaces (VIFs) that provide visibility into Border Gateway Protocol (BGP) session health and route counts....

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1 week ago

AWS Weekly Roundup: NVIDIA Nemotron 3 Super on Amazon Bedrock, Nova Forge SDK, Amazon Corretto 26, and more (March 23, 2026) Hello! I’m Daniel Abib, and this is my first AWS Weekly Roundup. I’m a Senior Specialist Solutions Architect at AWS, focused on the generative AI and Amazon Bedrock. With over 28 years of experience in solution architecture, software development, and cloud architecture, I help Startups & Enterprises harness the power of generative AI with Amazon […]

AWS Weekly Roundup: NVIDIA Nemotron 3 Super on Amazon Bedrock, Nova Forge SDK, Amazon Corretto 26, and more (March 23, 2026)

Hello! I’m Daniel Abib,...

#AWS #AmazonBedrockAgentcore #AmazonCloudwatch #AmazonConnect #AmazonCorretto #AmazonNova #AmazonRedshift #AwsLambda #Kiro #News #WeekInReview

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1 week ago

Amazon CloudWatch introduces organization-wide EC2 detailed monitoring enablement Amazon CloudWatch now allows customers to automatically enable Amazon Elastic Compute Cloud (EC2) detailed monitoring across their AWS Organization. Customers can create enablement rules in CloudWatch Ingestion that automatically enable detailed monitoring for both existing and newly launched EC2 instances matching the rule scope, ensuring consistent metrics collection at 1-minute intervals across their EC2 instances. EC2 detailed monitoring enablement rules can be scoped to the whole organization, specific accounts, or specific resources based on resource tags to standardize the configuration across EC2 instances. For example, the central DevOps team can create an enablement rule to automatically turn on detailed monitoring for EC2 instances with specific tags, e.g., env:production, and ensure Auto Scaling policies respond quickly to changes in instance utilization. CloudWatch's auto-enablement capability is available in all AWS commercial regions. Detailed monitoring metrics will be billed according to CloudWatch Pricing. To learn more about org-wide EC2 detailed monitoring enablement, visit the Amazon CloudWatch documentation.

🆕 Amazon CloudWatch now enables organization-wide EC2 detailed monitoring across AWS Orgs, automatically applying it to existing and new instances based on rules, ensuring consistent 1-min metrics collection. Available in all commercial regions; pricing per CloudWatch.

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1 week ago

Amazon CloudWatch introduces organization-wide EC2 detailed monitoring enablement Amazon CloudWatch now allows customers to automatically enable Amazon Elastic Compute Cloud (EC2) detailed monitoring across their AWS Organization. Customers can create enablement rules in CloudWatch Ingestion that automatically enable detailed monitoring for both existing and newly launched EC2 instances matching the rule scope, ensuring consistent metrics collection at 1-minute intervals across their EC2 instances. EC2 detailed monitoring enablement rules can be scoped to the whole organization, specific accounts, or specific resources based on resource tags to standardize the configuration across EC2 instances. For example, the central DevOps team can create an enablement rule to automatically turn on detailed monitoring for EC2 instances with specific tags, e.g., env:production, and ensure Auto Scaling policies respond quickly to changes in instance utilization. CloudWatch's auto-enablement capability is available in all AWS commercial regions. Detailed monitoring metrics will be billed according to https://aws.amazon.com/cloudwatch/pricing/. To learn more about org-wide EC2 detailed monitoring enablement, visit the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/telemetry-config-rules.html

Amazon CloudWatch introduces organization-wide EC2 detailed monitoring enablement

Amazon CloudWatch now allows customers to automatically enable Amazon Elastic Compute Cloud (EC2) detailed monitoring across their AWS Organization. Customers can create enablement rules i...

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2 weeks ago

Amazon CloudWatch Application Signals adds new SLO capabilities Amazon CloudWatch Application Signals now offers three new console based capabilities for Service Level Objectives (SLOs): SLO Recommendations, Service-Level SLOs, and SLO Performance Report. CloudWatch Application Signals helps customers monitor and improve application performance on AWS. It automatically collects data from applications running on services like Amazon EC2, Amazon ECS, and Lambda. Previously, customers had to manually set SLO thresholds without data-driven guidance, often leading to misconfigured targets and alert fatigue. They also lacked visibility into overall service health across operations and had no way to track reliability trends over time or generate calendar periods performance reports. These new capabilities address each of those gaps, making it easier to set data-driven reliability targets, monitor overall service health, and identify reliability trends before they become incidents. SLO Recommendations analyzes 30 days of service metrics (P99 latency and error rates) to suggest appropriate reliability targets. Customers can validate proposed targets before implementation to help reduce the cognitive and operational effort needed for new SLO deployments. Service-Level SLOs provide a holistic view of service reliability across all operations, simplifying alignment between technical monitoring and business objectives. SLO Performance Report provides historical analysis aligned with calendar periods, supporting daily, weekly, and monthly intervals. These capabilities support key use cases including proactive reliability management, SLO threshold optimization, and business reporting aligned with calendar periods. These features are available in all AWS Regions where Amazon CloudWatch Application Signals is available. Pricing is based on the number of inbound and outbound requests to and from applications, plus Service Level Objectives charges, with each SLO generating 2 application signals per service level indicator metric period.

🆕 Amazon CloudWatch Application Signals now offers SLO Recommendations, Service-Level SLOs, and SLO Performance Reports to help set reliable targets, monitor service health, and track trends, simplifying proactive reliability management and SLO optimization across AWS regio…

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2 weeks ago

Amazon CloudWatch Application Signals adds new SLO capabilities Amazon CloudWatch Application Signals now offers three new console based capabilities for Service Level Objectives (SLOs): SLO Recommendations, Service-Level SLOs, and SLO Performance Report. CloudWatch Application Signals helps customers monitor and improve application performance on AWS. It automatically collects data from applications running on services like Amazon EC2, Amazon ECS, and Lambda. Previously, customers had to manually set SLO thresholds without data-driven guidance, often leading to misconfigured targets and alert fatigue. They also lacked visibility into overall service health across operations and had no way to track reliability trends over time or generate calendar periods performance reports. These new capabilities address each of those gaps, making it easier to set data-driven reliability targets, monitor overall service health, and identify reliability trends before they become incidents. https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-ServiceLevelObjectives.html#CloudWatch-ServiceLevelObjectives-Recommendations analyzes 30 days of service metrics (P99 latency and error rates) to suggest appropriate reliability targets. Customers can validate proposed targets before implementation to help reduce the cognitive and operational effort needed for new SLO deployments. Service-Level SLOs provide a holistic view of service reliability across all operations, simplifying alignment between technical monitoring and business objectives. SLO Performance Report provides historical analysis aligned with calendar periods, supporting daily, weekly, and monthly intervals. These capabilities support key use cases including proactive reliability management, SLO threshold optimization, and business reporting aligned with calendar periods. These features are available in all AWS Regions where Amazon CloudWatch Application Signals is available. https://aws.amazon.com/cloudwatch/pricing/ is based on the number of inbound and outbound requests to and from applications, plus Service Level Objectives charges, with each SLO generating 2 application signals per service level indicator metric period.

Amazon CloudWatch Application Signals adds new SLO capabilities

Amazon CloudWatch Application Signals now offers three new console based capabilities for Service Level Objectives (SLOs): SLO Recommendations, Service-Level SLOs, and SLO Performance Report. CloudWatch App...

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3 weeks ago

Amazon CloudWatch Logs announces increased query concurrency and API limits Amazon CloudWatch Logs customers can now run up to 100 concurrent queries per account and execute 10 StartQuery and GetQueryResults API calls per second per account/per-region, using the Logs Insights Query Language (Logs Insights QL). These limit increases enable customers to support more users and execute more concurrent queries. With concurrency increasing from 30 to 100, more users can simultaneously run queries and leverage dashboards using Logs Insights QL. Customers using StartQuery and GetQueryResults APIs for Logs Insights QL benefit from higher limits without being throttled, enabling them to execute more queries and view results faster. The limit increases for Logs Insights queries is available in US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), Canada (Calgary), South America (São Paulo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Milan), Europe (Zurich), Europe (Spain), Africa (Cape Town), Middle East(Tel Aviv), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Melbourne), Asia Pacific (Tokyo), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Hong Kong), Asia Pacific (Jakarta), Asia Pacific (Bangkok), Asia Pacific (Malaysia), Asia Pacific (Auckland), Asia Pacific (Taipei), and Mexico (Querétaro). For more information, visit the Amazon CloudWatch Logs https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/AnalyzingLogData.html.

Amazon CloudWatch Logs announces increased query concurrency and API limits

Amazon CloudWatch Logs customers can now run up to 100 concurrent queries per account and execute 10 StartQuery and GetQueryResults API calls per second per account/per-reg...

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3 weeks ago

Amazon CloudWatch Logs announces increased query concurrency and API limits Amazon CloudWatch Logs customers can now run up to 100 concurrent queries per account and execute 10 StartQuery and GetQueryResults API calls per second per account/per-region, using the Logs Insights Query Language (Logs Insights QL). These limit increases enable customers to support more users and execute more concurrent queries. With concurrency increasing from 30 to 100, more users can simultaneously run queries and leverage dashboards using Logs Insights QL. Customers using StartQuery and GetQueryResults APIs for Logs Insights QL benefit from higher limits without being throttled, enabling them to execute more queries and view results faster. The limit increases for Logs Insights queries is available in US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), Canada (Calgary), South America (São Paulo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Milan), Europe (Zurich), Europe (Spain), Africa (Cape Town), Middle East(Tel Aviv), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Melbourne), Asia Pacific (Tokyo), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Hong Kong), Asia Pacific (Jakarta), Asia Pacific (Bangkok), Asia Pacific (Malaysia), Asia Pacific (Auckland), Asia Pacific (Taipei), and Mexico (Querétaro). For more information, visit the Amazon CloudWatch Logs documentation.

🆕 Amazon CloudWatch Logs boosts query concurrency to 100 per account and API calls to 10/sec, enabling more users to run queries and view results faster across 26 regions. For details, see Amazon CloudWatch Logs documentation.

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4 weeks ago

Application Performance Monitoring Enabled by Default in CloudWatch Observability EKS Add-on Today, Amazon CloudWatch Observability EKS add-on version 5.0.0 automatically enables CloudWatch Application Signals — Amazon's application performance monitoring (APM) capability — for all new installations and upgrades, eliminating the previous manual opt-in step. Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service that simplifies running containerized applications at scale. The CloudWatch Observability add-on for EKS extends native Kubernetes observability by integrating Enhanced Container Insights, Container Logs, and now Application Signals directly into your clusters. The Observability add-on automatically instruments your services to collect traces, metrics, and logs for a unified, application-centric view. For DevOps engineers, platform teams, and developers who needed application-level visibility into their EKS-hosted services — such as service latency, error rates, and request traces — this change closes that gap by making those capabilities available out of the box, so teams can focus on building and operating applications rather than configuring observability tooling.azon EKS. With Application Signals now enabled by default, customers immediately benefit from automatic service instrumentation — no manual configuration or Kubernetes workload annotations required — along with pre-built dashboards that surface application performance metrics and a rich troubleshooting experience that goes beyond infrastructure-level data to help teams quickly identify and resolve issues. For example, a platform team managing a microservices application on EKS can now detect latency spikes or error rate increases at the service level without any additional setup, accelerating root cause analysis during incidents. This feature is available in all commercial AWS regions where Amazon CloudWatch Application Signals is available; to get started, you can refer to the Amazon CloudWatch Application Signals documentation and upgrade to version 5.0.0 of the add-on.

🆕 Amazon CloudWatch EKS add-on v5.0.0 now defaults to Application Signals, offering automatic performance monitoring for new EKS setups, pre-built dashboards, and quick issue resolution in all commercial AWS regions.

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4 weeks ago

Application Performance Monitoring Enabled by Default in CloudWatch Observability EKS Add-on Today, Amazon CloudWatch Observability EKS add-on version 5.0.0 automatically enables CloudWatch Application Signals — Amazon's application performance monitoring (APM) capability — for all new installations and upgrades, eliminating the previous manual opt-in step. Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service that simplifies running containerized applications at scale. The CloudWatch Observability add-on for EKS extends native Kubernetes observability by integrating Enhanced Container Insights, Container Logs, and now Application Signals directly into your clusters. The Observability add-on automatically instruments your services to collect traces, metrics, and logs for a unified, application-centric view. For DevOps engineers, platform teams, and developers who needed application-level visibility into their EKS-hosted services — such as service latency, error rates, and request traces — this change closes that gap by making those capabilities available out of the box, so teams can focus on building and operating applications rather than configuring observability tooling.azon EKS. With Application Signals now enabled by default, customers immediately benefit from automatic service instrumentation — no manual configuration or Kubernetes workload annotations required — along with pre-built dashboards that surface application performance metrics and a rich troubleshooting experience that goes beyond infrastructure-level data to help teams quickly identify and resolve issues. For example, a platform team managing a microservices application on EKS can now detect latency spikes or error rate increases at the service level without any additional setup, accelerating root cause analysis during incidents. This feature is available in all commercial AWS regions where Amazon CloudWatch Application Signals is available; to get started, you can refer to the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/install-CloudWatch-Observability-EKS-addon.html#Container-Insights-setup-EKS-appsignalsconfiguration and upgrade to version 5.0.0 of the add-on.

Application Performance Monitoring Enabled by Default in CloudWatch Observability EKS Add-on

Today, Amazon CloudWatch Observability EKS add-on version 5.0.0 automatically enables CloudWatch Application Signals — Amazon's application performance monitoring (APM) capabi...

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1 month ago

Amazon CloudWatch logs centralization rules now support customizable destination log group structure Amazon CloudWatch now supports customizing destination log group names when creating CloudWatch log centralization rules. Organizations managing logs across multiple accounts can now use attributes to organize centralized logs into meaningful hierarchies — by account ID, region, organizational unit, or other AWS Organizations metadata — that match how their organization operates and what their compliance requirements demand. You can define a destination log group name structure using attributes that CloudWatch Logs automatically replaces with actual values when logs are copied. For example, using the pattern ${source.accountId}/${source.region}/${source.logGroup} creates destination log groups like 123456789012/us-east-1/cloudtrail/managementevent, making it easy to identify which account and region logs originated from. You can use attributes, including source account ID, region, log group name, organization ID, organizational unit ID, root ID, and the full organizational path. Customizable destination log group names are available in all centralization rules supported regions. Customers can use centralization rules to centralize one copy of logs for free (ingestion). Additional copies are charged at $0.05/GB of logs centralized (the backup region feature is considered an additional copy). Storage charges apply. To learn more, visit the CloudWatch Logs Centralization documentation.

🆕 Amazon CloudWatch lets you name log groups for better organization, aiding compliance and management. Available everywhere, free for one copy, $0.05/GB for more.

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1 month ago

Amazon CloudWatch logs centralization rules now support customizable destination log group structure Amazon CloudWatch now supports customizing destination log group names when creating CloudWatch log centralization rules. Organizations managing logs across multiple accounts can now use attributes to organize centralized logs into meaningful hierarchies — by account ID, region, organizational unit, or other AWS Organizations metadata — that match how their organization operates and what their compliance requirements demand. You can define a destination log group name structure using attributes that CloudWatch Logs automatically replaces with actual values when logs are copied. For example, using the pattern ${source.accountId}/${source.region}/${source.logGroup} creates destination log groups like 123456789012/us-east-1/cloudtrail/managementevent, making it easy to identify which account and region logs originated from. You can use attributes, including source account ID, region, log group name, organization ID, organizational unit ID, root ID, and the full organizational path. Customizable destination log group names are available in all https://builder.aws.com/build/capabilities/explore. Customers can use centralization rules to centralize one copy of logs for free (ingestion). Additional copies are charged at $0.05/GB of logs centralized (the backup region feature is considered an additional copy). Storage charges apply. To learn more, visit the https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CloudWatchLogs_Centralization.html.

Amazon CloudWatch logs centralization rules now support customizable destination log group structure

Amazon CloudWatch now supports customizing destination log group names when creating CloudWatch log centralization rules. Organizations managing logs across multiple acc...

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1 month ago

AWS Outposts racks now support additional Amazon CloudWatch metrics in AWS GovCloud (US) Regions AWS Outposts racks now support VifConnectionStatus and VifBgpSessionState Amazon CloudWatch metrics in AWS GovCloud (US) Regions. These metrics provide visibility into the connectivity status of your Outposts racks' Local Gateway (LGW) and Service Link Virtual Interfaces (VIFs) with your on-premises devices. These metrics provide you with the ability to monitor Outposts VIF connectivity status directly within the CloudWatch console, without having to rely on external networking tools or coordination with other teams. You can use these metrics to set alarms, troubleshoot connectivity issues, and ensure your Outposts racks are properly integrated with your on-premises infrastructure. The VifConnectionStatus metric indicates whether an Outposts VIF is successfully connected, configured, and ready to forward traffic. A value of "1" means that the VIF is operational, while "0" means that it is not ready. The VifBgpSessionState metric shows the current state of the BGP session between the Outposts VIF and the on-premises device, with values ranging from 1 (IDLE) to 6 (ESTABLISHED). The VifConnectionStatus and VifBgpSessionState metrics are now available for all Outposts VIFs in AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions where Outposts racks are available. To get started, read this blog post and access the metrics in the CloudWatch console. To learn more, check out the CloudWatch metrics for Outposts documentation for first-generation Outposts racks.

🆕 AWS Outposts racks now support VifConnectionStatus and VifBgpSessionState metrics in AWS GovCloud (US), providing better visibility for Local Gateway and Service Link Virtual Interfaces, allowing direct monitoring in CloudWatch.

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1 month ago

AWS Outposts racks now support additional Amazon CloudWatch metrics in AWS GovCloud (US) Regions AWS Outposts racks now support VifConnectionStatus and VifBgpSessionState Amazon CloudWatch metrics in AWS GovCloud (US) Regions. These metrics provide visibility into the connectivity status of your Outposts racks' Local Gateway (LGW) and Service Link Virtual Interfaces (VIFs) with your on-premises devices. These metrics provide you with the ability to monitor Outposts VIF connectivity status directly within the CloudWatch console, without having to rely on external networking tools or coordination with other teams. You can use these metrics to set alarms, troubleshoot connectivity issues, and ensure your Outposts racks are properly integrated with your on-premises infrastructure. The VifConnectionStatus metric indicates whether an Outposts VIF is successfully connected, configured, and ready to forward traffic. A value of "1" means that the VIF is operational, while "0" means that it is not ready. The VifBgpSessionState metric shows the current state of the BGP session between the Outposts VIF and the on-premises device, with values ranging from 1 (IDLE) to 6 (ESTABLISHED). The VifConnectionStatus and VifBgpSessionState metrics are now available for all Outposts VIFs in AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions where Outposts racks are available. To get started, read this https://aws.amazon.com/blogs/compute/improving-network-observability-with-new-aws-outposts-racks-network-metrics/and access the metrics in the CloudWatch console. To learn more, check out the CloudWatch metrics for https://docs.aws.amazon.com/outposts/latest/userguide/outposts-cloudwatch-metrics.html#metrics-vif for first-generation Outposts racks.

AWS Outposts racks now support additional Amazon CloudWatch metrics in AWS GovCloud (US) Regions

AWS Outposts racks now support VifConnectionStatus and VifBgpSessionState Amazon CloudWatch metrics in AWS GovCloud (US) Regions. These metrics provide visibili...

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1 month ago

AWS Weekly Roundup: Amazon EC2 G7e instances, Amazon Corretto updates, and more (January 26, 2026) Hey! It’s my first post for 2026, and I’m writing to you while watching our driveway getting dug out. I hope wherever you are you are safe and warm and your data is still flowing! This week brings exciting news for customers running GPU-intensive workloads, with the launch of our newest graphics and AI inference […]

AWS Weekly Roundup: Amazon EC2 G7e instances, Amazon Corretto updates, and more (January 26, 2026)

Hey! It’s my first post for 2026, and I’m writing to you while watching o...

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1 month ago

AWS Observability now available as a Kiro power Today, AWS announces AWS Observability as a Kiro power, enabling developers and operators to investigate infrastructure and application health issues faster with AI agent-assisted workflows in Kiro. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to accelerate specialized software development and deployment use cases. The AWS Observability power packages four specialized MCP servers with targeted observability guidance: the CloudWatch MCP server for observability data; the Application Signals MCP server for application performance monitoring; the CloudTrail MCP server for security analysis and compliance; and the AWS Documentation MCP server for contextual reference access. This unified platform gives Kiro agents instant context for comprehensive workflows including alarm response, anomaly detection, distributed tracing, SLO compliance monitoring, and security investigation. Additionally, the power includes automated gap analysis that helps you identify and fix missing instrumentation. With the AWS Observability power, developers can now accelerate troubleshooting their distributed applications and infrastructure in minutes, directly in their IDE. The power addresses two critical needs: reducing mean time to resolution (MTTR) for active incidents and proactively improving your observability stack. For faster incident response, when investigating an active alarm, the power dynamically loads relevant guidance and operational signals so AI agents receive only the context needed for the specific troubleshooting task at hand. For stack improvement, the automated gap analysis examines your code to identify missing instrumentation patterns—such as unlogged errors, missing correlation IDs, or absent distributed tracing—and provides actionable recommendations. The power includes eight comprehensive steering guides covering incident response, alerting, performance monitoring, security auditing, and gap analysis. The AWS Observability power is available for one-click installation within Kiro IDE and Kiro powers webpage in all AWS Regions, with each underlying MCP server functional based on regional support of the corresponding AWS service. To learn more about AWS observability MCP servers, visit our documentation.

🆕 AWS Observability is a Kiro power for quicker issue investigation via AI workflows. It has four MCP servers for observability, performance, security, and docs. Easily installable in Kiro IDE, it cuts MTTR and boosts observability.

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1 month ago

AWS Observability now available as a Kiro power Today, AWS announces AWS Observability as a Kiro power, enabling developers and operators to investigate infrastructure and application health issues faster with AI agent-assisted workflows in Kiro. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to accelerate specialized software development and deployment use cases. The AWS Observability power packages four specialized MCP servers with targeted observability guidance: the CloudWatch MCP server for observability data; the Application Signals MCP server for application performance monitoring; the CloudTrail MCP server for security analysis and compliance; and the AWS Documentation MCP server for contextual reference access. This unified platform gives Kiro agents instant context for comprehensive workflows including alarm response, anomaly detection, distributed tracing, SLO compliance monitoring, and security investigation. Additionally, the power includes automated gap analysis that helps you identify and fix missing instrumentation. With the AWS Observability power, developers can now accelerate troubleshooting their distributed applications and infrastructure in minutes, directly in their IDE. The power addresses two critical needs: reducing mean time to resolution (MTTR) for active incidents and proactively improving your observability stack. For faster incident response, when investigating an active alarm, the power dynamically loads relevant guidance and operational signals so AI agents receive only the context needed for the specific troubleshooting task at hand. For stack improvement, the automated gap analysis examines your code to identify missing instrumentation patterns—such as unlogged errors, missing correlation IDs, or absent distributed tracing—and provides actionable recommendations. The power includes eight comprehensive steering guides covering incident response, alerting, performance monitoring, security auditing, and gap analysis. The AWS Observability power is available for https://kiro.dev/launch/powers/aws-observability within https://kiro.dev/powers/#how-do-i-install-powers and https://kiro.dev/powers/ in all AWS Regions, with each underlying MCP server functional based on regional support of the corresponding AWS service. To learn more about AWS observability MCP servers, visit our https://awslabs.github.io/mcp/.

AWS Observability now available as a Kiro power

Today, AWS announces AWS Observability as a Kiro power, enabling developers and operators to investigate infrastructure and application health issues faster with AI agent-assisted workflows in Kiro. Kiro Pow...

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1 month ago

Deep Dive on Loop Filter as Metric Filter in Amazon CloudWatch “ I have checked the documents of AWS for deep dive on loop filter as metric filter in amazon...

✍️ New blog post by GargeeBhatnagar

Deep Dive on Loop Filter as Metric Filter in Amazon CloudWatch

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1 month ago

AWS CloudWatch Alarm Mute Rules eliminate alert fatigue Amazon CloudWatch now supports Alarm Mute Rules, enabling customers to temporarily mute alarm notifications during planned deployments, maintenance windows, and off-hours without compromising monitoring visibility. This new capability helps eliminate alert fatigue while maintaining complete situational awareness across their infrastructure. Alarm Mute Rules transform operational workflows by allowing teams to create one-time or recurring rules that silence notifications for up to 100 individual alarms around deployment calendars, scheduled maintenance activities, or predictable off-hours periods when non-critical alerts become disruptive. Customers can configure actions for OK, ALARM, and INSUFFICIENT_DATA states, and when mute rules expire, any previously muted actions are automatically triggered as long as the alarm remains in the same state it was in when the actions were muted, ensuring critical issues are never overlooked while preventing unnecessary alert fatigue. This eliminates the operational risk of forgotten script-based workarounds and reduces alert noise during planned activities, enabling engineering teams to focus on core business initiatives rather than managing notification fatigue. CloudWatch Alarm Mute Rules is available today in all AWS Regions supporting alarm-level muting. To get started, see https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/alarm-mute-rules.html. You can create mute rules through the https://console.aws.amazon.com/cloudwatch/.

AWS CloudWatch Alarm Mute Rules eliminate alert fatigue

Amazon CloudWatch now supports Alarm Mute Rules, enabling customers to temporarily mute alarm notifications during planned deployments, maintenance windows, and off-hours without compromising monitoring visibility....

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1 month ago

Amazon CloudWatch Application Signals now supports integration with Kiro powers Today, AWS announces Amazon CloudWatch Application Signals integration with Kiro powers, enabling developers and operators to investigate application health issues faster with AI agent-assisted workflows in Kiro. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to accelerate specialized software development and deployment use cases. Kiro power for Amazon CloudWatch Application Signals packages the Application Signals MCP server with targeted observability guidance, giving the Kiro agent instant context for service health monitoring, SLO compliance, and investigation workflows. With Kiro power for Application Signals, developers can now accelerate troubleshooting their distributed applications in minutes instead of spending hours, directly in their IDE. For example, developers triaging an SLO or isolating an impacted service or operation, the Kiro power will dynamically load the relevant guidance and operational signals, so AI agents receive only the context needed for the specific task at hand. Amazon CloudWatch Application Signals Kiro power Kiro power is available within https://kiro.dev/powers/#how-do-i-install-powers and https://kiro.dev/powers/ for https://kiro.dev/launch/powers/cloudwatch-application-signals/ in all AWS Regions. To learn more about Application signals MCP server, visit our https://awslabs.github.io/mcp/servers/cloudwatch-applicationsignals-mcp-server. Amazon CloudWatch Application Signals helps you monitor and improve application performance on AWS by automatically collecting application telemetry and enabling you to track application health, performance, and service relationships. To get started, see the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Application-Monitoring-Sections.html?utm_source=chatgpt.com.

Amazon CloudWatch Application Signals now supports integration with Kiro powers

Today, AWS announces Amazon CloudWatch Application Signals integration with Kiro powers, enabling developers and operators to investigate application health issues faster with AI agent-assis...

#AWS #AmazonCloudwatch

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1 month ago

Amazon CloudWatch Application Signals now supports integration with Kiro powers Today, AWS announces Amazon CloudWatch Application Signals integration with Kiro powers, enabling developers and operators to investigate application health issues faster with AI agent-assisted workflows in Kiro. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and hooks validated by Kiro partners to accelerate specialized software development and deployment use cases. Kiro power for Amazon CloudWatch Application Signals packages the Application Signals MCP server with targeted observability guidance, giving the Kiro agent instant context for service health monitoring, SLO compliance, and investigation workflows. With Kiro power for Application Signals, developers can now accelerate troubleshooting their distributed applications in minutes instead of spending hours, directly in their IDE. For example, developers triaging an SLO or isolating an impacted service or operation, the Kiro power will dynamically load the relevant guidance and operational signals, so AI agents receive only the context needed for the specific task at hand. Amazon CloudWatch Application Signals Kiro power Kiro power is available within Kiro IDE and Kiro powers webpage for one-click installation in all AWS Regions. To learn more about Application signals MCP server, visit our documentation. Amazon CloudWatch Application Signals helps you monitor and improve application performance on AWS by automatically collecting application telemetry and enabling you to track application health, performance, and service relationships. To get started, see the Amazon CloudWatch Application Signals documentation.

🆕 AWS CloudWatch Application Signals now integrates with Kiro powers, offering AI-assisted workflows for faster issue investigation, enabling developers to troubleshoot distributed apps in minutes instead of hours, available for one-click installation in all AWS Regions.

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1 month ago

Amazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 Tables New capabilities help optimize application performance, analyze unlimited prefixes, and simplify metrics analysis through S3 Tables integration.

Amazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 Tables

New capabilities help optimize appli...

#AWS #AmazonAthena #AmazonCloudwatch #AmazonEmr #AmazonQuickSight #AmazonRedshift #AmazonS3Tables #AmazonSimpleStorageService(S3) #Analytics #Storage

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1 month ago

Amazon CloudWatch introduces unified data management and analytics for operations, security, and compliance Reduce data management complexity and costs with automatic normalization across sources, native analytics integration, and built-in support for industry-standard formats like OCSF and Apache Iceberg.

Amazon CloudWatch introduces unified data management and analytics for operations, security, and compliance

Reduce data management complexity and costs with automatic normalization across sources, native analytics integration, and ...

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2 months ago

Amazon ECS now publishes container health status as a CloudWatch metric https://aws.amazon.com/ecs/ (Amazon ECS) now publishes container health status as a new metric in CloudWatch Container Insights with enhanced observability. Customers can now track the operational health of their containers through a dedicated CloudWatch metric and create alarms to respond proactively to unhealthy containers. When customers configure a container health check in the container definition of an ECS task definition, Container Insights now publishes the UnHealthyContainerHealthStatus metric in the ECS/ContainerInsights namespace. The metric reports 0 for HEALTHY and 1 for UNHEALTHY. Container health state information is also available in embedded metric format (EMF) logs, providing additional context while health checks are being evaluated during the UNKNOWN state. The metric is available across cluster, service, task, and container-level dimensions, enabling customers to monitor health at their preferred level of granularity. Customers can create CloudWatch alarms on the metric to receive notifications when containers become unhealthy, allowing teams to take immediate action and maintain application reliability. To get started, enable Container Insights with enhanced observability on your ECS cluster and configure a container health check in your task definition to start collecting the metric in CloudWatch. Container health metric is available in all AWS Regions where Amazon ECS Container Insights is supported. For more information, see the https://docs.aws.amazon.com/AmazonECS/latest/developerguide/healthcheck.html and the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Container-Insights-enhanced-observability-metrics-ECS.html.

Amazon ECS now publishes container health status as a CloudWatch metric

https://aws.amazon.com/ecs/ (Amazon ECS) now publishes container health status as a new metric in CloudWatch Container Insights with enhanced observability. Cus...

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2 months ago

Amazon ECS now publishes container health status as a CloudWatch metric Amazon Elastic Container Service (Amazon ECS) now publishes container health status as a new metric in CloudWatch Container Insights with enhanced observability. Customers can now track the operational health of their containers through a dedicated CloudWatch metric and create alarms to respond proactively to unhealthy containers. When customers configure a container health check in the container definition of an ECS task definition, Container Insights now publishes the UnHealthyContainerHealthStatus metric in the ECS/ContainerInsights namespace. The metric reports 0 for HEALTHY and 1 for UNHEALTHY. Container health state information is also available in embedded metric format (EMF) logs, providing additional context while health checks are being evaluated during the UNKNOWN state. The metric is available across cluster, service, task, and container-level dimensions, enabling customers to monitor health at their preferred level of granularity. Customers can create CloudWatch alarms on the metric to receive notifications when containers become unhealthy, allowing teams to take immediate action and maintain application reliability. To get started, enable Container Insights with enhanced observability on your ECS cluster and configure a container health check in your task definition to start collecting the metric in CloudWatch. Container health metric is available in all AWS Regions where Amazon ECS Container Insights is supported. For more information, see the Amazon ECS container health checks documentation and the CloudWatch Container Insights documentation.

🆕 Amazon ECS now offers container health metrics in CloudWatch for better observability, triggering alarms for unhealthy containers. Set up health checks in task definitions to start collecting metrics. Available in all ECS Container In…

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2 months ago

AWS Weekly Roundup: Amazon EC2 G7e instances, Amazon Corretto updates, and more (January 26, 2026) Hey! It’s my first post for 2026, and I’m writing to you while watching our driveway getting dug out. I hope wherever you are you are safe and warm and your data is still flowing! This week brings exciting news for customers running GPU-intensive workloads, with the launch of our newest graphics and AI inference […]

AWS Weekly Roundup: Amazon EC2 G7e instances, Amazon Corretto updates, and more (January 26, 2026)

Hey! It’s my first post for 2026, and I’m writing to you w...

#AWS #AmazonCloudwatch #AmazonConnect #AmazonCorretto #AmazonEc2 #AmazonElasticContainerRegistry #News #Uncategorized #WeekInReview

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AWS News(Unofficial)

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2 months ago

Amazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 Tables New capabilities help optimize application performance, analyze unlimited prefixes, and simplify metrics analysis through S3 Tables integration.

Amazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 Tables

New capabilities help optimize appli...

#AWS #AmazonAthena #AmazonCloudwatch #AmazonEmr #AmazonQuickSight #AmazonRedshift #AmazonS3Tables #AmazonSimpleStorageService(S3) #Analytics #Storage

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AWS News(Unofficial)

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2 months ago

Amazon CloudWatch introduces unified data management and analytics for operations, security, and compliance Reduce data management complexity and costs with automatic normalization across sources, native analytics integration, and built-in support for industry-standard formats like OCSF and Apache Iceberg.

Amazon CloudWatch introduces unified data management and analytics for operations, security, and compliance

Reduce data management complexity and costs with automatic normalization across sources, native analytics integration, and ...

#AWS #AmazonCloudwatch #Events #Launch #ManagementTools #News

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3 months ago

AWS launches simplified import of CloudTrail Lake data in Amazon CloudWatch Today, AWS launches simplified import of CloudTrail Lake data in Amazon CloudWatch, a data management and analytics service that allows you to unify operational, security, and compliance data across your AWS environment and third-party sources. With this launch, you can now import your historical CloudTrail Lake data into CloudWatch with a few steps enabling you to easily consolidate operational, security, and compliance data in one place. In CloudWatch, you simply specify the CloudTrail Lake event data store (EDS), and the date range to initiate import of your CloudTrail data. Simplified import of CloudTrail Lake data is supported via the AWS console, CLI, and SDK. While simplified import of CloudTrail Lake data is available at no additional cost, you incur CloudWatch fees based on custom logs pricing. To learn more about simplified import of CloudTrail Lake data and supported AWS regions, visit the https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/telemetry-config-cloudwatch.html

AWS launches simplified import of CloudTrail Lake data in Amazon CloudWatch

Today, AWS launches simplified import of CloudTrail Lake data in Amazon CloudWatch, a data management and analytics service that allows you to unify operational, security, and compliance data ac...

#AWS #AmazonCloudwatch

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