Tag: SysAdmin

AWS Network Firewall now supports expanded Managed Rules from AWS Marketplace partners, with new rule group optimizations through partners to include up to 10 million domain name indicators and up to 1 million IP addresses in their managed rule groups. Infoblox is expanding domain name indicators to protect your workloads from critical and high-risk domains. Lumen is introducing new rule groups to stop command and control attacks. ThreatSTOP is adding managed rules for Office of Foreign Assets Control (OFAC) sanctions and expanding global compliance protections with new European Union, Japan, and United Nations sanction coverage. These enhancements give you access to richer, more comprehensive threat intelligence directly within AWS Network Firewall, reducing the operational burden of managing threat feeds and enabling faster, more accurate protection against emerging threats. Whether you need to block malicious domains at scale, defend against command and control infrastru

Amazon SageMaker AI now supports serverless model customization for Qwen3.5, enabling you to fine-tune Qwen3.5 4B, 9B, and 27B parameter models using supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). Qwen3.5 is a popular open-weight model family from Alibaba Cloud. Before this launch, you could deploy these base models on SageMaker AI and now, you can also adapt them to your specific domains and workflows.  Model customization enables you to tailor foundation models with your proprietary data so they more accurately reflect your domain knowledge, terminology, and quality standards. Rather than building models from scratch, fine-tuning lets you start from a capable base model and specialize it for your use cases, whether that's improving accuracy on domain-specific tasks, aligning outputs with your organization's tone, or improving performance on new tasks using your labeled data. With serverless customization, SageMaker AI handles all infrastructure

AWS Secrets Manager now supports managed external secrets for MongoDB Atlas and Confluent Cloud. AWS Secrets Manager now supports managed external secrets for MongoDB Atlas and Confluent Cloud, enabling you to centrally manage and automatically rotate secrets for these third-party services directly from AWS Secrets Manager — without building or maintaining custom Lambda rotation functions. The MongoDB Atlas integration supports two secret types: database user secrets (username-password authentication via SCRAM) and service account secrets (OAuth client ID and secret). The Confluent Cloud integration supports API key rotation for service accounts, with support for both cluster-scoped and cloud resource management keys. All integrations include automatic rotation enabled by default, eliminating hardcoded secrets and reducing the operational overhead of managing secrets across multiple platforms. With managed external secrets, secret rotation is fully managed

Today, Amazon Bedrock AgentCore introduces new features to help developers go from an idea to working agent prototype faster and manage the full agent lifecycle from a single platform: a managed harness (in preview), the AgentCore CLI, and AgentCore skills for coding assistants. The managed harness (preview) lets developers define an agent by specifying a model, system prompt, and tools, then run it immediately with no orchestration code required. The harness manages the full agent loop: reasoning, tool selection, action execution, and response streaming. Each session gets its own microVM with filesystem and shell access. The harness is model agnostic with the ability to switch models mid-session. Any configuration set at create time can be overridden per invocation, so developers experiment without redeploying. When developers need full control, they can export the harness orchestration in Strands-based code. Filesystem persistence (preview) externalizes the local session s

Today, AWS announced that you can now receive notifications through the AWS Health Dashboard when Amazon EC2 for SQL Server cannot detect a valid SQL Server High Availability (HA) status. This enhancement is particularly valuable for customers who register EC2 SQL HA clusters through AWS Console or CloudFormation automation to reduce license included costs. You can receive this notification through multiple channels, including AWS Health, Amazon EventBridge events, and email. These notifications will guide you to respond quickly, helping avoid unexpect

On April 22, 2026 Amazon announced quarterly security and critical updates for Amazon Corretto Long-Term Supported (LTS) and Feature Release (FR) versions of OpenJDK. Corretto 26.0.1, 25.0.3, 21.0.11, 17.0.19, 11.0.31, and 8u492 are now available for download. Amazon Corretto is a no-cost, multi-platform, production-ready distribution of OpenJDK. This is the last Corretto 8 release to include JavaFX binaries. JavaFX binaries will no longer be included starting from the next quarterly update in July 2026. You can learn more about the migration recommendations at Corretto 8 GitHub. Visit Corretto home page to download Corretto 26, Corretto 25, Corretto 21, Corretto 17, Corretto 11, or Corretto 8. You can also get the updates on your Linux system by configuring a

Amazon OpenSearch Service now supports rollback for service software updates, giving you greater control when managing updates to your Amazon OpenSearch Service domains. Previously, once a software update was applied, there was no self-service option to revert it to a previous version if you encountered an unexpected issue. Software update rollback uses a blue/green deployment. You can initiate a rollback within 15 days of a service software update being applied, using the new RollbackServiceSoftwareUpdate API, the AWS CLI, or the Amazon OpenSearch Service console. Rollback option for service software updates is now available in all AWS Regions where Amazon OpenSearch Service is available. To learn more about the software updates and rollback option, refer to the Amazon OpenSearch Service documentatio

Amazon SageMaker AI now supports inference recommendations, a new capability that eliminates manual optimization and benchmarking to deliver optimal inference performance. By delivering validated, optimal deployment configurations with performance metrics, SageMaker AI accelerates the path to production and keeps your model developers focused on building accurate models, not managing infrastructure. Customers bring their own generative AI models, define expected traffic patterns, and specify a performance goal (optimize for cost, minimize latency, or maximize throughput). SageMaker AI then analyzes the model's architecture and applies optimizations aligned to that goal across multiple instance types, benchmarking each configuration on real GPU infrastructure using NVIDIA AIPerf. By evaluating multiple instance types, customers can select the most price-performant option for their workload. The result is deployment-ready configurations with validated metrics including time t

Amazon SageMaker now supports multi-region replication from IAM Identity Center (IdC), enabling you to deploy SageMaker Unified Studio domains in different regions from your IdC instance. This new capability empowers enterprise customers, particularly those in regulated industries like financial services and healthcare, to maintain compliance while leveraging centralized workforce identity management. As an Amazon SageMaker Unified Studio administrator, you can deploy SageMaker domains closer to your workforce based on data residency needs while maintaining seamless single sign-on (SSO) access. Organizations can address use cases such as maintaining IdC in one region while processing sensitive data in compliance-required regions, supporting global operations with centralized identity management, and meeting data sovereignty requirements without compromising SSO capabilities. To get started see the

Today, AWS announced the availability of Qwen3-Coder-Next, Qwen3-30B-A3B, Qwen3-30B-A3B-Thinking-2507, Qwen3-Coder-30B-A3B-Instruct, and Qwen3.5-4B in Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These five models from Qwen bring specialized capabilities spanning agentic coding, efficient reasoning, extended thinking, and multimodal understanding, enabling customers to build sophisticated AI applications across diverse use cases on AWS infrastructure. These models address different enterprise AI challenges with specialized capabilities: Qwen3-Coder-Next excels at long-horizon reasoning, complex tool use, and recovery from execution failures, making it ideal for powering coding agents in CLI/IDE platforms. Qwen3-30B-A3B uniquely supports seamless switching between thinking and non-thinking modes, making it well suited for general-purpose assistant tasks like multilingual dialogue,