10/19/2026, 12:00:00 AM ~ 10/20/2026, 12:00:00 AM (UTC)
Recent Announcements
Amazon CloudWatch Omni is now available in additional AWS Regions
AWS announces that Amazon CloudWatch Omni is now available in eight additional AWS Regions. CloudWatch Omni is an AI-powered observability experience, organized around your teams and the applications they run, that helps you observe and troubleshoot your applications and agents in one place. It combines the interoperability of OpenTelemetry with the scale and reliability of CloudWatch, and meets you where you work — a standalone web experience with single sign-on (SSO), or a local IDE extension.\nWith CloudWatch Omni, You create spaces in your central accounts to see telemetry across your AWS accounts, Regions, and other clouds, including Azure and GCP. Omni discovers services, maps dependencies, and surfaces golden metrics automatically and you can interact with telemetry through chat, point-and-click, or your own tool via Agent Toolkit for AWS to find signals, build dynamic views, and reach root cause powered by AWS DevOps Agent. A dedicated agent observability experience adds an evaluation-driven workflow for frameworks including LangGraph, CrewAI, OpenAI Agents SDK, Vercel AI SDK, and Strands. With this expansion, CloudWatch Omni is now available in Canada (Central), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (London), and South America (São Paulo), in addition to US East (N. Virginia), US West (Oregon), and Europe (Ireland). To get started, create your Omni space from the CloudWatch console, configure SSO, and sign in. Agent developers can install the free CloudWatch Omni extension for VS Code, Cursor, and Kiro. To learn more, see the Amazon CloudWatch Omni product page and documentation. For pricing, see the CloudWatch Omni pricing page.
EC2 Image Builder now integrates with ASG for faster image builds
EC2 Image Builder now supports using existing instances from an Auto Scaling Group (ASG) for building images, enabling faster builds by eliminating the time spent in launching and bootstrapping new instances and reusing already running EC2 instances.\nWith this feature, you can provide an ASG in your Image Builder infrastructure configuration. Instead of launching a new instance at the build time, Image Builder selects an already-running instance from this ASG, applies your build components, and creates the image. The ASG continuously replenishes the pool as instances are used for builds, ensuring instances are always available for subsequent pipeline runs. This feature is fully opt-in and does not affect existing pipelines. Pipelines without an ASG configured continue to use the default launch path with no behavior change. This feature is available in all AWS Regions at no additional cost. To configure ASG integration in your Image Builder pipelines, see the EC2 Image Builder documentation.
Amazon GuardDuty adds optional threat detection rules for Runtime Monitoring
Amazon GuardDuty now supports optional detection rules for Runtime Monitoring. You can enable more than 50 Runtime Monitoring rules that help detect process, file, and network activity that might be routine in one environment but a sign of compromise in another, such as modifying sudoers files or disabling audit logging.\nThe new rules provide detections for Amazon EC2 instances, Amazon EKS, and Amazon ECS on both EC2 and AWS Fargate, and span 13 finding types mapped to MITRE ATT&CK® tactics including persistence, privilege escalation, execution, defense evasion, discovery, exfiltration, and command and control. This release introduces four new finding types: CommandAndControl:Runtime/SuspiciousCommand, CredentialAccess:Runtime/SensitiveFileRead, Discovery:Runtime/SensitiveFileRead, and Exfiltration:Runtime/SuspiciousCommand. To get started, visit the GuardDuty console. You can enable rules in dry-run mode to evaluate detection efficacy before enabling live detection. Custom Detection Rules for Runtime Monitoring is available in all AWS commercial Regions and the AWS GovCloud (US) Regions. To learn more, see Amazon GuardDuty Custom Detection Rules. To receive programmatic updates on new Amazon GuardDuty features and threat detections, subscribe to the Amazon GuardDuty SNS topic.
Grok 4.7 is now available on Amazon Bedrock in AWS GovCloud (US)
Amazon Bedrock now supports SpaceXAI Grok 4.7, a frontier model built for coding, agentic tasks, and knowledge work in AWS GovCloud (US).\nGrok 4.7 builds on Grok 4.6 with better mixed-document handling, more dependable repo-scale coding with planning and error recovery, and enhanced browser-use agents for form fills and portal navigation. Get started with Grok 4.7 in the Amazon Bedrock console or programmatically through supported Amazon Bedrock APIs. For information about supported AWS Regions, endpoints, APIs, features, inference profiles and pricing, see the Amazon Bedrock documentation. To learn more, read the launch blog post.
AWS Blogs
AWS Japan Blog (Japanese)
- AWS Weekly — 2026/10/12
- Weekly Generative AI with AWS — 2026/10/12 Week
- The AI analysis platform “Dotta,” which completes analysis by “just listening” by Corteg Co., Ltd., has been realized with Amazon Bedrock AgentCore
- Guidance for building an AI-powered studio on AWS
- Announcing the AWS Physical AI Toolchain
- Enhanced network policy functionality in Amazon EKS
- Implementing least-privilege access in Amazon Bedrock
- Practical steps to minimize the risk of access key disclosure with AWS security services
- Amazon Bedrock API Key Protection: Implementation and Management Best Practices
AWS News Blog
AWS Big Data Blog
AWS Database Blog
AWS DevOps & Developer Productivity Blog
- Automate Active Directory joins for Elastic Beanstalk Windows applications
- HERE Technologies and AWS: Accelerating NDS.Live with agentic AI
Artificial Intelligence
- Amazon SageMaker JumpStart: 2026 year-to-date in review
- Pegasus 1.5 from TwelveLabs is now available in Amazon Bedrock
- How Deepgram optimized voice AI at scale with AWS Trainium
- Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM
- Improve TTFT for multi-turn agentic workloads with bi-directional KV transfer in vLLM