8/28/2026, 12:00:00 AM ~ 8/31/2026, 12:00:00 AM (UTC)
Recent Announcements
Amazon EC2 C8gn instances are now available in AWS Europe (Paris) region
Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C8gn instances, powered by the latest-generation AWS Graviton4 processors, are available in the AWS Europe (Paris) region. The C8gn instances provide up to 30% better compute performance than Graviton3-based Amazon EC2 C7gn instances. Amazon EC2 C8gn instances feature the latest 6th generation AWS Nitro Cards, and offer up to 600 Gbps network bandwidth, the highest network bandwidth among network optimized EC2 instances. \n Take advantage of the enhanced networking capabilities of C8gn to scale performance and throughput, while optimizing the cost of running network-intensive workloads such as network virtual appliances, data analytics, CPU-based artificial intelligence and machine learning (AI/ML) inference.
For increased scalability, C8gn instances offer instance sizes up to 48xlarge, up to 384 GiB of memory, and up to 120 Gbps of bandwidth to Amazon Elastic Block Store (EBS). C8gn instances support Elastic Fabric Adapter (EFA) networking on the 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes, which enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters.
C8gn instances are available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon, N.California), Europe (Frankfurt, Stockholm, Ireland, London, Spain, Zurich, Milan, Paris), Asia Pacific (Singapore, Malaysia, Sydney, Thailand, Mumbai, Seoul, Melbourne, Jakarta, Hyderabad, Tokyo, Hong Kong), Middle East (UAE), Africa (Cape Town), Canada West (Calgary, Central), South America (Sao Paulo), AWS GovCloud (US-East, US-West). To learn more, see Amazon C8gn Instances. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.
Amazon Bedrock AgentCore Memory now supports fine-grained access control
Amazon Bedrock AgentCore Memory now supports fine-grained access control (FGAC), enabling you to enforce per-user and per-tenant memory isolation through AgentCore Gateway without building custom authorization logic.\n
With FGAC, you can front your Memory resource with an AgentCore Gateway configured for OAuth (JWT) authentication and attach Cedar policies that restrict access based on the authenticated caller’s identity. You can enforce that each user only accesses their own actor’s data, restrict memory records to namespaces derived from the user’s token claims, and allow or deny specific Memory operations per caller. This lets you move access control enforcement from application code to the infrastructure layer using cryptographic proof of identity. FGAC for Memory is built on the AgentCore Memory connector, a managed gateway connector that wires a gateway target to the Memory data plane and exposes 12 Memory operations as Cedar actions with their request attributes available for policy conditions.
To get started, see Fine-grained access control for Memory in the Amazon Bedrock AgentCore Developer Guide.
Amazon Bedrock AgentCore Memory now supports flexible namespace variables
Amazon Bedrock AgentCore Memory now lets developers define flexible namespace variables to scope long-term memories along any application-specific dimension - such as organization, tenant, team, or environment - without creating duplicate strategies or overloading built-in variables. This gives multi-tenant and complex-hierarchy applications fine-grained control over how memories are organized, isolated, and accessed.\n Define keys on the memory resource, reference them in a strategy’s namespace template, and supply values at runtime through the CreateEvent API. The service substitutes them into namespace templates during long-term memory extraction. Up to five keys can be defined per memory resource, each referenceable across multiple strategies. Flexible namespace variables are available today in all AWS Regions where Amazon Bedrock AgentCore Memory is generally available, at no additional cost. To get started, see Specify long-term memory organization with namespaces in the Amazon Bedrock AgentCore Developer Guide.
AWS Transform now in scope for FedRAMP Class C
AWS Transform is now in scope for FedRAMP Class C (formerly Moderate baseline) in the US East (Ohio) Region. You can now use AWS Transform to build applications and run workloads that are subject to FedRAMP Class C compliance requirements.\n The Federal Risk and Authorization Management Program (FedRAMP) is a US government-wide program that delivers a standard approach to the security assessment, authorization, and continuous monitoring for cloud products and services. AWS Transform is an agentic migration and modernization service designed to compress enterprise timelines from years to months — handling everything from large-scale infrastructure migrations to continuous tech debt reduction, without the manual handoffs and lost context that commonly stall these programs.
To learn more about FedRAMP, visit the AWS services in scope page. To learn more about AWS Transform, visit the webpage and documentation.
Amazon EC2 P6-B300 instances are now available in additional AWS Regions
Starting today, Amazon Elastic Cloud Compute (Amazon EC2) P6-B300 instances are available in Asia Pacific (Hyderabad) and South America (Sao Paulo) Regions. P6-B300 instances provide 8xNVIDIA Blackwell Ultra GPUs with 2.1 TB high bandwidth GPU memory, 6.4 Tbps EFA networking, 300 Gbps dedicated ENA throughput, and 4 TB of system memory.\n P6-B300 instances deliver 2x networking bandwidth, 1.5x GPU memory size, and 1.5x GPU TFLOPS (at FP4, without sparsity) compared to P6-B200 instances, making them well suited to train and deploy large trillion-parameter foundation models (FMs) and large language models (LLMs) with sophisticated techniques. The higher networking and larger memory deliver faster training times and more token throughput for AI workloads.
P6-B300 instances are now available in p6-b300.48xlarge size in the following AWS Regions: US West (Oregon), AWS GovCloud (US-East), US East (N. Virginia), Asia Pacific (Hyderabad, Seoul), and South America (Sao Paulo). To learn more about P6-B300 instances, visit Amazon EC2 P6 instances.
Amazon CloudWatch agent adds support for journald logs
AWS announces support for collecting systemd journal (journald) logs with the Amazon CloudWatch agent. You can now configure the CloudWatch agent to read log entries directly from the systemd journal on Linux instances and send them to Amazon CloudWatch Logs, without first writing those logs to files on disk.\n Many modern Linux distributions, including Amazon Linux 2023, use systemd journal as the primary logging system and no longer write traditional text log files such as /var/log/messages by default. Previously, collecting these logs with the CloudWatch agent required additional configuration to export the journal to files on disk. With this launch, the CloudWatch agent reads journald entries natively, preserving the structured metadata that journald captures, such as the systemd unit, priority, and process information. You can filter log entries using systemd units, journal priority levels, and journal field matches, and you can apply regular expression filters before logs are published to CloudWatch Logs. This helps you reduce noise and control log volume and costs.
Support for journald in the CloudWatch agent is available in all AWS Commercial Regions and GovCloud(US) regions. Standard Amazon CloudWatch Logs pricing applies for ingested logs. For more information, see Amazon CloudWatch Pricing page.
To get started, update to the latest version of the CloudWatch agent and add a journald section to your agent configuration file. To learn more, see Manually create or edit the CloudWatch agent configuration file in the Amazon CloudWatch User Guide.
Amazon Aurora MySQL 3.13 (compatible with MySQL 8.0.45) is generally available
Starting today, Amazon Aurora MySQL-Compatible Edition 3 (compatible with MySQL 8.0) supports MySQL 8.0.45, which includes community MySQL fixes and Aurora-specific improvements. For detailed information on this release, refer to Aurora MySQL 3 and MySQL 8.0.45 release notes.\n You can upgrade your databases during scheduled maintenance windows using automatic minor version upgrades. To simplify operations at scale, enable automatic minor version upgrades and use the AWS Organizations Upgrade Rollout Policy to orchestrate upgrades across your clusters in phases. You can perform minor version upgrades in-place or via snapshot restore. This release is supported in all AWS Regions where Aurora MySQL is available. Amazon Aurora is designed for high performance and availability at global scale with full MySQL compatibility. It provides scale-to-zero serverless compute, Aurora Global Database for multi-Region resilience, Aurora I/O-Optimized for improved price performance on I/O-intensive workloads, and built-in security and continuous backups. To get started, take a look at Aurora’s getting started page.
SpaceXAI Grok 4.6 now available on Amazon Bedrock in AWS GovCloud (US)
Amazon Bedrock in AWS GovCloud (US) now supports SpaceXAI Grok 4.6, a frontier model built for coding, agentic tasks, and knowledge work. Grok 4.6 is SpaceXAI’s latest flagship model, built for long-running agents and ambitious interactive and visual work. It offers 500k context window and configurable reasoning efforts (low, medium, high, xhigh).\n
The model runs on the bedrock-runtime endpoint with support for the Responses, Chat Completions, and Converse APIs, and customers can access Grok 4.6 at scale with cross-Region inference routing requests across both AWS GovCloud (US) Regions. Grok 4.6 is also avialable via the bedrock-mantle endpoint in AWS GovCloud (US-East).
To get started, review the model card for Grok 4.6 in the Amazon Bedrock User Guide.
AWS Blogs
AWS Japan Blog (Japanese)
- Disaster recovery and multi-site networking with Amazon EVS and NSX Federation
- To 120,000 people in 2 weeks — NEC realized a secure enterprise-wide AI environment with Claude Desktop on Amazon Bedrock
- Streamline access to tabular data sets stored in Amazon S3 Tables with DuckDB
- Reach insights faster with Amazon SageMaker Unified Studio notebooks
- Analyze Application Load Balancer Logs with Amazon CloudWatch Logs
- Are AI coding agents really getting better?
- Implementing Amazon Bedrock’s Fine-Grained Cost Allocation
- Part 2: Amazon Bedrock Cost Allocation Using Amazon Athena and CUDOS
- Continuous Profit Business Realized with AI Tools - Turning Development Capabilities into Assets — AWS Local Executive Roadshow Sapporo Edition (#8 /8) Event Report
- Key points for introducing generative AI learned from practical companies ~ turning sleeping data into corporate value ~ — AWS Local Executive Roadshow Sapporo Edition (#7 /8) Event Report
AWS Japan Startup Blog (Japanese)
- 3 days of “energy” gathering in Kyoto | Japan’s largest startup conference [IVS2026]
- AI, Governance, and Multiple Products — Case Session for 3 Notable Startups [AWS Summit Japan 2026]
- A place to meet the latest technology “beyond” | Startup Zone & Physical AI Area [AWS Summit Japan 2026]
AWS Big Data Blog
AWS DevOps & Developer Productivity Blog
Artificial Intelligence
- Batch write and discover records in Amazon SageMaker Feature Store
- How Decathlon runs demand forecasting at scale with Chronos-2
- Spreading the load: How Salesforce met Multi-AZ HA with SageMaker Inference Components