Skill UI

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

This guide provides comprehensive examples for developing real-time chat applications using the Azure Communication Services Chat SDK in Java. It covers essential features including creating chat threads, sending diverse message types (text, HTML), listing message history, managing participants, and handling advanced functionalities like read receipts, message updates, and participant management. Ideal for building robust, enterprise-grade messaging systems.

A comprehensive SDK providing robust authentication credentials for Python applications interacting with Azure services. It simplifies secure access by supporting multiple credential types, including Managed Identity, Service Principal, and Azure CLI. Features like DefaultAzureCredential allow seamless authentication across local environments, CI/CD pipelines, and various Azure cloud deployments.

A comprehensive SDK providing robust authentication credentials for Python applications interacting with Azure services. It simplifies secure access by supporting multiple credential types, including Managed Identity, Service Principal, and Azure CLI. Features like DefaultAzureCredential allow seamless authentication across local environments, CI/CD pipelines, and various Azure cloud deployments.

This is the Azure Resource Manager SDK for .NET, designed to streamline the deployment and management of Weights & Biases (W&B) ML experiment tracking instances directly through Azure Marketplace. It allows developers to programmatically create, configure, and manage W&B environments, including setting up marketplace details, managing admin users, configuring Single Sign-On (SSO), and ensuring robust ML observability within an Azure ecosystem. Ideal for MLOps pipelines.

This is the Azure Resource Manager SDK for .NET, designed to streamline the deployment and management of Weights & Biases (W&B) ML experiment tracking instances directly through Azure Marketplace. It allows developers to programmatically create, configure, and manage W&B environments, including setting up marketplace details, managing admin users, configuring Single Sign-On (SSO), and ensuring robust ML observability within an Azure ecosystem. Ideal for MLOps 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.

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 SDK provides comprehensive support for automatically instrumenting Node.js applications to collect observability data. It integrates distributed tracing, metrics, and logs using the OpenTelemetry standard, allowing seamless data export and monitoring within Azure Monitor. It supports various resource types and connection methods.

This SDK provides the management plane interface for provisioning and administering Azure SQL resources (servers, databases, firewalls, etc.) using C# and .NET. It allows developers to automate the deployment lifecycle of SQL infrastructure entirely through code, integrating seamlessly with the Azure Resource Manager.

This comprehensive guide covers the entire MLOps lifecycle, specializing in building robust, scalable, and production-grade Machine Learning systems. Expertise includes orchestrating complex ML pipelines using Kubeflow, Airflow, Prefect, and cloud-native services (AWS SageMaker, Azure ML, GCP Vertex AI). It covers experiment tracking (MLflow, W&B), model versioning, model registries, infrastructure as code (Terraform), and container deployment using Kubernetes. Ideal for engineers tasked with moving ML models from research to reliable, managed production environments.

This skill facilitates the configuration and management of Single Sign-On (SSO) for Windsurf enterprise deployments. It supports industry-standard protocols like SAML 2.0 and OIDC/OAuth 2.0, allowing seamless identity integration with major providers such as Okta, Azure AD, and Google Workspace. Essential for administrators implementing centralized, secure enterprise authentication.