News For Dev-ops

Amazon SageMaker Studio now supports direct integration from Hugging Face, letting you go from discovering a model to working with it inside a fully configured Studio environment in a single click. Select any supported model on Hugging Face and choose "Customize on SageMaker AI" or "Deploy on SageMaker AI" to land directly on the corresponding workflow page with the model pre-loaded and ready to use. Previously, getting from model discovery to a working environment required navigating the AWS Console to find SageMaker AI, configuring an environment, setting up IAM permissions for serverless model customization, and in many cases requesting GPU quota increases through Service Quotas before running a first job. Now, new customers complete a standard AWS sign-up and receive a SageMaker Studio environment created in seconds with pre-configured permissions for serverless model customization jobs including fine-tuning with custom reward functions for reinforcement learn...

Starting today, AWS CodePipeline is now available in Asia Pacific (New Zealand) Region (ap-southeast-6). AWS CodePipeline is a continuous delivery service that enables you to model, visualize, and automate the steps required to release your software. With CodePipeline, you model the full release process for building your code, deploying to pre-production environments, testing your application and releasing it to production. CodePipeline then builds, tests, and deploys your application according to the defined workflow every time there is a code change. You can integrate partner tools and your own custom tools into any stage of the release process to form an end-to-end continuous delivery solution. CodePipeline integrates natively with other AWS services (such as CodeBuild, CodeDeploy, and CloudFormation) and supports third-party integrations, such as GitHub or with your own custom plugin, offering a comprehensive solution for orchestrating end-to-end CI/CD pipelines. By integrating m...

Once you create a container, its partition key is fixed at creation, and you can’t change it in place. However, if your original key starts causing problems like cross-partition queries or hot partitions , you need to consider your options for changing it. This post explains the mechanics of changing a partition key, and the tradeoffs between the options. First, think about the intent of your change: Re-partition the data. You want your items (and future writes ) to live under a different key. This means moving to a new container and there are three ways, from least to most effort:  Change partition key  feature, container copy jobs , or a do-it-yourself migration. Query by a different key without moving. Your writes are fine where they are, and you only have read patterns that fan out across partitions. A Global Secondary Index adds a separate, read-only, automatically-synchronized container with a different partition key and its own data model, a projection of your ite...

A new model drops with lower per-token pricing and better benchmarks. You switch. A week later someone asks why the agent is burning 12x more tokens on the same task while producing worse output. We ran 150 agent tasks across 15 scenarios on two models, Claude Sonnet 4.6 and Claude Sonnet 5, using GitHub Copilot Chat in VS Code on Windows. The scenarios covered two types of work: architecture and design tasks grounded in Microsoft Learn documentation, and SharePoint Framework project upgrades. Sonnet 5 is the newer model with 33% lower per-token pricing across every token category. The assumption we wanted to test: newer and cheaper means better. What we found was more complicated. Cheaper tokens, higher bills Sonnet 5 is cheaper per token across the board. Here's how the rate cards compare: Sonnet 4.6 Sonnet 5 Input (per 1M tokens) $3.00 $2.00 Cached input $0.30 $0.20 Output $15.00 $10.00 In such a comparison, Sonnet 5 win...

Thank you for your interest in the new Azure SDKs! We release new features, improvements, and bug fixes every month. Subscribe to our Azure SDK Blog RSS Feed to get notified when a new release is available. You can find links to packages, code, and docs on our Azure SDK Releases page . Release highlights Azure AI Transcription reaches general availability for Python The Python azure-ai-transcription (1.0.0) client library is now generally available. This is the first stable release of the library, giving Python developers a supported client for working with Azure AI's transcription service. Microsoft Planetary Computer Pro client library reaches general availability for Python The Python azure-planetarycomputer (1.0.0) client library is now generally available. Alongside the first stable release, this version adds new response models, including AssetStatisticsResponse , ClassMapLegendResponse , and QueryableDefinitionsResponse , and the queryable and class-map-legend operati...

When I presented my study of a crash caused by a thread executing from an unloaded third-party DLL , someone asked how I concluded that CcNamespace.dll was the ringleader of the family of related DLLs. The list of recently-unloaded DLLs is recorded in a circular history.¹ So when you see a bunch of DLLs listed in a row, they were unloaded one after the other.² 00007ff9`6d7c0000 00007ff9`6d80a000 FabrikamContextMenu.dll 00007ff9`115e0000 00007ff9`1172f000 LitWareSync.dll 00007ff9`643d0000 00007ff9`64681000 CcNamespace.dll 00000000`55440000 00000000`5550b000 LibDB_CloudNs_3.dll 00000000`55860000 00000000`55998000 LibNet_CloudNs_3.dll 00000000`557f0000 00000000`5585b000 LibJson_CloudNs_3.dll 00000000`55510000 00000000`557e7000 LibUtils_CloudNs_3.dll 00000000`561a0000 00000000`56238000 MSVCP100.dll 00000000`56240000 00000000`56312000 MSVCR100.dll 00007ff9`85130000 00007ff9`85167000 EhStorShell.dll 00007ff9`3cac0000 00007ff9`3cb61000 wpdshext.dll 00007ff9`78a00000 ...