
Explore DevSecOps beyond pipelines, covering key concepts, application security, and practical strategies for integrating security into the development lifecycle.

Explore AWS IoT for smart robot development. Learn about data-driven optimization, edge ML, remote control, simulation, and interoperability. Discover real-world applications and CI/CD pipelines for robotics.

Learn to run Robot Framework tests in Jenkins for continuous integration, covering setup, job creation, and execution of automated tests.

Discover a CI/CD-driven approach to automated metadata management in data lakes, focusing on balancing development speed, governance, and schema evolution for rapidly growing organizations.

Explore automated test monitoring and reporting for Databricks Runtime using Delta, analyzing results from various sources to track quality and efficiently report failures to owners.

Explore multi-table transactions using LakeFS and Delta Lake for collaborative data lake management, enabling CI/CD deployment and simplified multi-table pipelines in cloud storage systems.

Exploring next-gen tools for Apache Spark development, focusing on productivity, code standardization, metadata, lineage, and CI/CD agility to overcome limitations of traditional ETL tools.

Learn to automate and deploy Jupyter notebooks using GitHub Actions, enhancing your MLOps workflow and streamlining the process of productionizing data science projects.

Explore BuildKit's modern OCI image builder toolkit, enhancing Docker builds with improved performance, remote caching, and multi-platform support for streamlined application development and CI workflows.

Comprehensive MLOps project implementation covering data ingestion, validation, transformation, model training, and deployment on AWS EC2 using MLflow and GitHub Actions.

Explore the latest WSL improvements and best practices for creating a powerful Linux environment on Windows, including AI enhancements, GitHub Actions, and VS Code Remote integration.

Learn how to apply CI/CD practices to machine learning pipelines, enhancing model development from data exploration to deployment for better, faster results in MLOps.

Explore ML Ops challenges and solutions using AWS services. Learn to bridge the gap between data science and deployment with a "model factory" architecture for effective CI/CD in machine learning.

Automate data pipelines using Python and GitHub Actions. Learn to create ETL scripts, set up repositories, configure workflows, and implement ML applications for efficient data processing.

Develop an end-to-end data analytics pipeline, from exploratory analysis to model deployment. Learn pipeline orchestration, distributed training, automation, and monitoring for scalable machine learning projects.

Empower data consumers to create their own products with minimal training. Learn best practices, community building, SQL literacy promotion, and guard rail establishment for self-service analytics.

Explore the implementation challenges and solutions for integrating Host Managed SMR drives in software-defined storage, covering sequential write constraints, ZoneFS utilization, and data alignment considerations.

Master deploying self-hosted GitHub Action runners on Kubernetes using Terraform, with practical demonstrations for cloud and local environments while maintaining security and cost efficiency.

Discover how Mozilla integrates Test Driven Security into DevOps pipelines, accelerating security issue detection and mitigation while maintaining rapid innovation for Firefox services.

Automate security reviews in CI/CD pipelines using AWS Step Functions. Learn to deploy serverless systems for integrating security tools like static analysis and container scanning into developer workflows.

Explore Visual Studio 2019's new features with Scott Hanselman: improved Git workflows, automated CI/CD to Azure using GitHub Actions, and .NET Core debugging on Linux.