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This SDK provides comprehensive Python support for interacting with Azure Event Hubs, a high-throughput streaming platform. It allows developers to build robust data ingestion pipelines, acting as both event producers (sending data) and event consumers (receiving data). Key features include efficient batch processing, partition key management, and reliable checkpointing using Azure Blob Storage for production-grade stream applications.

A comprehensive Python SDK guide for securely managing secrets, cryptographic keys, and certificates within Azure Key Vault. This tool allows developers to implement secure storage, perform cryptographic operations (encryption, decryption, signing, verification), and handle certificate lifecycle management, ensuring sensitive application data is protected across various development environments.

This SDK enables Java developers to build real-time, scalable web applications using Azure Web PubSub. It leverages WebSocket-based messaging to implement critical features such as live chat applications, instant server-to-client push notifications, and real-time data synchronization. Key functionalities include targeted message delivery (to all, groups, or specific users), connection management, and secure client access token generation.

A comprehensive SDK for running Playwright end-to-end tests at scale. It leverages cloud-hosted browsers within the Azure ecosystem, allowing developers to execute reliable, large-scale automated tests. Features include integrated Azure portal reporting, seamless authentication using Microsoft Entra ID, and strong support for CI/CD pipelines.

A comprehensive SDK for running Playwright end-to-end tests at scale. It leverages cloud-hosted browsers within the Azure ecosystem, allowing developers to execute reliable, large-scale automated tests. Features include integrated Azure portal reporting, seamless authentication using Microsoft Entra ID, and strong support for CI/CD pipelines.

This library serves as a low-level exporter for Python applications, enabling the reliable transfer of comprehensive OpenTelemetry telemetry data—including traces, metrics, and logs—to Azure Application Insights. It provides robust configuration options, including connection string setup, Azure AD authentication, custom sampling, and offline storage management, ensuring complete and reliable observability.

This library provides a straightforward, one-line setup for integrating Python applications with Azure Application Insights. It leverages OpenTelemetry for automatic instrumentation across popular frameworks (Flask, Django, FastAPI) and various libraries, enabling comprehensive monitoring of traces, metrics, and logs in a single setup.

A comprehensive guide for building applications that interact with Azure Blob Storage using the Azure SDK for Java. Covers essential patterns including client initialization (via connection string or credentials), uploading/downloading data from files or streams, listing blobs, and managing containers. Ideal for developers building scalable cloud data storage solutions.

This SDK provides a comprehensive Python interface for interacting with Azure Blob Storage, Microsoft's scalable object storage service. It enables users to perform core object storage operations, including uploading, downloading, listing, deleting blobs, managing containers, and setting custom metadata. The library supports both synchronous and asynchronous workflows, making it ideal for building robust data pipelines, data lakes, or cloud-native applications that require reliable, scalable file storage.

This is a comprehensive client library for interacting with Azure Blob Storage, Microsoft's scalable object storage solution for the cloud. It allows developers to perform core operations in Rust, such as uploading, downloading, listing, creating, and managing blobs and containers. Ideal for building cloud-native applications that require persistent, scalable data storage.

This SDK provides a full set of tools for interacting with Azure Blob Storage using JavaScript or TypeScript. It enables developers to perform essential object storage operations, including uploading, downloading, listing, creating, and managing both blobs and containers. Supports various authentication methods like DefaultAzureCredential and Connection Strings, making it ideal for building robust, cloud-native applications.

This SDK provides comprehensive Python support for Azure Data Lake Storage Gen2. It enables developers to interact with hierarchical file systems, performing essential big data operations such as creating, listing, uploading, downloading, and managing metadata for files and directories. Ideal for building data analytics pipelines and cloud-based data processing workflows.