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Discover how observability enhances real-time monitoring of Python applications and LLMs through metrics, traces, and logs using OpenTelemetry for improved performance.
Discover how to seamlessly integrate ChatGPT into your .NET applications with practical implementation techniques and best practices for AI-powered functionality.
Explore a hybrid framework combining Faker.js and AI APIs to generate intelligent test data for e-commerce scenarios, comparing traditional random data with AI-driven realistic user journeys.
Master Bicep DSL for declarative Azure resource management with simplified, reusable infrastructure-as-code and enhanced ARM integration.
Explore Azure Virtual WAN architecture, core components, and connectivity models to simplify large-scale branch, user, and VNet networking in this comprehensive 44-minute session.
Master practical techniques for writing clear, value-driven user stories that bridge business needs with development goals and avoid common pitfalls.
Discover how Postman's Model Context Protocol transforms API testing through natural language interactions, AI automation, and adaptive test generation from OpenAPI specs.
Master production-like load testing for real-time apps using JMeter & k6. Simulate high-throughput WebSocket traffic, model realistic patterns, monitor with InfluxDB/Grafana for scalable systems.
Explore Azure Traffic Manager's DNS-based global traffic distribution to enhance application availability and performance through intelligent routing across regions.
Discover how to implement TensorFlow Java bindings for running ML models and AI predictions in production systems without switching to Python.
Discover how to implement Spring Boot observability using Micrometer and OpenTelemetry to automatically collect metrics and traces for performance insights with minimal setup.
Master Vitest testing framework for Vite projects, covering setup, mocks, snapshots, watch mode, and coverage reports to ensure reliable code quality.
Discover how Deep Java Library empowers Java developers to explore deep learning, use pre-trained models, and integrate AI capabilities into real-world applications.
Master Java performance optimization using JMH, JFR, and VisualVM to handle JVM optimizations, warmup effects, and GC behavior for accurate benchmarking insights.
Explore real-world architectural patterns for building stable, scalable UI and API automation frameworks with robust abstractions and unified layers.
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