News For Dev-ops

Move from a locally composed memory-enabled agent to a deployed Foundry Agent Service agent, with keyless Azure infrastructure and an interactive browser sample. In  Native Agent Memory for Microsoft Agent Framework, Powered by Azure Cosmos DB , we introduced  CosmosMemoryContextProvider : a Microsoft Agent Framework context provider that extracts useful information from conversations, stores it in Azure Cosmos DB, and retrieves it before later agent runs. That article used a locally composed Agent Framework agent and  FoundryChatClient . It was a useful way to isolate the memory concepts: one provider, two lifecycle hooks, and a stable user identity across new chat sessions. This post takes the next step. In our featured sample , we will attach the same provider to a prompt agent deployed in Microsoft Foundry Agent Service , provision the complete environment with azd up , and use a small browser app to make the difference between conversation history and long-term memor...

Amazon Redshift , starting with patch P203 , supports concurrency scaling for refreshes of Amazon Kinesis Data Streams (KDS)-connected streaming materialized views (MVs). Amazon Web Services (AWS) Redshift Streaming Ingestion enables low-latency, high-speed data ingestion from Amazon KDS to Amazon Redshift data warehouses. The data lands in a Redshift streaming materialized view, providing fast access to external data, lowering data-access time, and reducing storage costs. Users can configure streaming ingestion for their Amazon Redshift cluster or Redshift Serverless workgroup using SQL commands. Once set up, each streaming materialized-view refresh can ingest hundreds of megabytes of data per second. If you have concurrency scaling enabled, your streaming workloads will now automatically scale by freeing-up your main Amazon Redshift cluster or workgroup to run other higher priority workloads. You can start using this new capability immediately in all AWS regions where Amazon Reds...

GPT-5.6 Terra and Luna are now generally available on Amazon Bedrock in AWS GovCloud (US-West) and AWS GovCloud (US-East), bringing the smartest family of models from OpenAI yet to Bedrock's next-generation inference engine built for high-performance, security and reliability. GPT-5.6 sets a new standard for intelligence and efficiency, allowing you to solve harder problems in less time and with more intelligence per token. The two models span capability tiers from balanced performance (Terra) to fast, cost-efficient inference (Luna). With GPT-5.6, you can build autonomous coding agents, run long-horizon genomics and biology analyses, and perform advanced cybersecurity research. Terra provides GPT-5.5-level performance at half the cost and Luna brings fast, affordable inference at the lowest price point. GPT-5.6 also supports prompt caching with explicit cache breakpoints, so repeated context across agentic workflows is billed at a 90% discount and doesn't compound cost as yo...

Today, OpenAI announced that they are lowering API prices for GPT-5.6 Sol. Following the recent Terra and Luna price reductions, Sol now costs $4 per million input tokens and $20 per million output tokens—20% lower input pricing and 33.3% lower output pricing. This promotional pricing is available at least through November 21, 2026. Whether you're building autonomous coding agents, running complex multi-step analyses, or performing advanced research workflows, the reduced pricing gives you more room to experiment and scale what's already working. GPT-5.6 Sol delivers state-of-the-art results on agentic coding benchmarks, and the lower price point makes it more accessible for sustained, high-volume workloads. For latest Regional availability of GPT-5.6 Sol, check the AWS Regions page. To learn more and view the pricing visit the Amazon Bedrock documentation on GPT-5.6 Sol. Post Updated on August 21, 2026 at 09:11PM

The Amazon Elastic Kubernetes Service (Amazon EKS) Capability for Argo CD now supports custom configuration through a standard argocd-cm ConfigMap in your cluster. This capability gives you a fully managed GitOps continuous delivery experience, and you can now tune it to fit how your teams work. You can define custom health checks for your Custom Resources, customize the Argo CD UI banner content, adjust how the capability watches and compares the resources it manages, and more. You configure these settings the same way you do in upstream Argo CD, and AWS applies them to your managed capability. With this launch, cluster administrators now have more control over how Argo CD reports application health. By default, Argo CD has no built-in health logic for Custom Resources, so an Application can report as healthy while its resources are still provisioning, and sync waves can advance before those resources are ready. With a custom health check, you define this logic yourself. For example...

AWS Local Zone in Las Vegas, Nevada is now generally available. The new AWS Local Zone supports Amazon Elastic Compute Cloud (Amazon EC2) C7i, M7i, R7i, and C8gn instances, Amazon Elastic Block Store (Amazon EBS) volume types gp3, gp2, io1, sc1, and st1, Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS), Application Load Balancer, and AWS Direct Connect. AWS Local Zones are AWS infrastructure deployments that extend core services, such as compute, storage, networking, and other select services, closer to metropolitan areas worldwide. AWS Local Zones help you achieve single-digit millisecond latency for end-user workloads, meet data residency requirements, support AI/ML inference workloads, and accelerate migration and modernization of legacy applications to the cloud, all while maintaining consistent AWS APIs, tools, and services as AWS Regions. AWS Local Zones are available in more than 30 metropolitan areas worldwide. To get started, en...