Learn how to mock external HTTP APIs in ASP.NET Core integration tests by replacing HttpMessageHandler for typed HttpClient instances in WebApplicationFactory.
Learn how to propagate CancellationToken through ASP.NET Core endpoints, services, EF Core queries, and HttpClient calls to stop unnecessary work when requests are aborted.
Learn how to stream large JSON responses in ASP.NET Core with IAsyncEnumerable, System.Text.Json, and cancellation-aware Entity Framework Core queries.
Learn the differences between ASP.NET Core output caching and response caching, including HTTP cache rules, server-side policies, middleware setup, and when to use each.
Learn how Databricks Apps uses workspace-level Python and npm repositories, letting administrators manage package sources while developers declare app dependencies.
Learn how BigQuery incremental transfers for PostgreSQL and ServiceNow use watermark columns and write modes to load new and updated records efficiently.
Learn how Google Cloud Storage Object Enrichments uses pretrained AI models to add searchable metadata to images and PDFs, and how to configure and use the results.
Learn how to use Gemini 4 Argon with BigQuery generative AI functions for SQL-based text analysis, summarization, and structured information extraction.
Learn how to publish an ASP.NET Core Minimal API with Native AOT, validate the executable, and assess compatibility limits around reflection and dynamic runtime features.
Learn how Microsoft’s NuGet author-signing certificate rotation affects trusted-signer policies and package verification, and how to update certificate allowlists safely.
Explains Microsoft's Go security updates, including an Ed25519 validation issue in the macOS cryptography backend, and shows how teams can identify affected toolchains and update safely.
Python 3.10 has reached end of life. Learn how to inventory affected environments, check dependency compatibility, choose a supported version, and plan a controlled upgrade.
Learn how Google Cloud AppLifecycle Manager Feature Flags separate deployment from release using targeted rollouts, centralized flag management, and OpenFeature evaluation.
Learn how Google AI Studio connects Cloud Run, Firebase, and Cloud SQL to support AI-assisted full-stack application development, authentication, data storage, and deployment.
AI agents are moving beyond short conversations. Developers are building agents that inspect codebases, execute tools, run tests, investigate failures, and complete workflows that may take hours to finish. However, running an agent in production introduces a different set of engineering challenges.
Learn how to test Apigee API proxies locally using routing, transformation, error-handling, and mock-backend tests before validating them in Google Cloud.
Learn how to assess and validate EKS workloads for migration to GKE, including identity, networking, storage, ingress, and cloud-specific dependencies.
Learn how Azure Functions agent bindings let Python apps run event-driven AI agent workflows with tool calling, security boundaries, and business-rule enforcement.
Learn how Azure Functions managed connectors and bindings simplify enterprise service integration, including authentication, configuration, and managed identity considerations.
Learn how MSTest UI testing can automate UWP and WinUI 3 desktop workflows, use stable automation identifiers, and avoid flaky tests with condition-based waiting.
Learn how WinDbg's MCP support can let AI agents investigate crash dumps through structured debugger tools and provide evidence-based natural-language debugging assistance.
Learn how to use the AWS SDK for Java SdkWarmUp API to reduce first-request latency by initializing SDK and HTTP client paths during application startup.
Learn how to reduce first-request latency in Java services by initializing and reusing AWS SDK clients, managing connections, and measuring cold-start overhead.
Learn how to route AWS DevOps Agent events through EventBridge and Lambda to create Jira issues, with guidance on authentication, event filtering, retries, and duplicate handling.
Learn how SageMaker HyperPod Spaces integrate with SageMaker Studio to run JupyterLab and Code Editor directly on HyperPod EKS clusters for ML development.
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