DevOpsSup - Extended DevOps Approach
Explore DevOpsSup, an extended DevOps approach integrating operations teams. Learn about building, management, and future prospects, with real-world project examples and key takeaways for implementation.
Azure DevOps - Building Private Agents at Scale
Learn to efficiently build and scale private Azure DevOps agents using virtual machine scale sets, optimizing costs and performance for your CI/CD pipelines.
Using Nix to Create Reproducible Golang Development Environments
Learn to create reproducible Golang development environments using Nix. Explore declarative configurations, tools integration, remote setups, and CI/CD implementation for consistent and efficient Go projects.
MLOps: From Jupyter to Production - Conf42 ML 2024
Learn to transition machine learning projects from Jupyter notebooks to production environments, covering MLOps best practices and real-world implementation strategies.
How to Build Cloud-Native Platforms with Kubernetes
Explore cloud-native platform development with Kubernetes, covering key concepts, best practices, and API-driven design. Gain insights into developer experience, testing, and platform team responsibilities.
AI-Augmented DevOps with Platform Engineering
Explore AI-augmented DevOps and platform engineering strategies to optimize workflows, identify bottlenecks, and implement real-world solutions for improved efficiency.
Building a Better Testing Culture
Explore strategies for fostering a robust testing culture, addressing challenges in automated testing, and promoting collaboration for efficient software delivery.
Simplifying Event-Driven Workflows with Argo Events and Argo Workflows
Explore Argo Events and Argo Workflows for building event-driven workflows on Kubernetes. Learn concepts, architecture, and best practices for combining these tools in production environments.
Testing in Apache Solr - Session 3
Explore Solr's testing capabilities, learn to contribute effectively, and master techniques for writing and managing tests in Apache Solr.
Automated Testing and Board Farming - Techniques for Rapid Software Testing
Explore automated testing techniques for rapid software release validation, focusing on current tools, projects, and development directions in response to EU's CRA legislation requirements.
Sustaining Git Performance Under Heavy Workloads - AI-driven Approach
Explore AI-driven strategies for maintaining Git repository performance under heavy workloads, including partial repacking and bitmap regeneration techniques.
Tips and Tricks for Writing Fast and Maintainable Front-End Tests
Discover techniques for crafting efficient, reliable front-end tests that communicate software intent clearly. Learn to write end-to-end and component tests, prevent flaky CI runs, and make tests valuable beyond QA.
Cloud-Native CI/CD in Kubernetes with Tekton
Implement CI/CD pipelines using Tekton, leveraging Kubernetes objects for seamless integration and scalability. Learn from DevOps expert Brent Laster about Tekton's dashboard, CLI, and key features.
Test Automation with GitOps: Benefits and Challenges
Explore GitOps for test automation in CI/CD, reducing setup time and improving efficiency. Learn benefits and challenges through Open Liberty's experience with OpenShift deployments.
Git Workflows for Platform Engineers
Explore advanced Git techniques for platform engineers to integrate operations and security best practices into development projects using GitLab core and CI/CD capabilities.
Exploring the Possibilities of GitHub Actions
Explore GitHub Actions' versatility beyond software workflows. Learn to automate tasks, increase productivity, and streamline processes for efficient and enjoyable development experiences.
How to Automate Machine Learning with GitHub Actions
Automate machine learning workflows using GitHub Actions to speed up development cycles and streamline model deployment.
Fighting Pipeline Debt With Great Expectations
Learn to combat pipeline debt using Great Expectations, an open-source library for data validation, documentation, and profiling in complex data systems.
How to Automate Machine Learning with GitHub Actions
Automate machine learning workflows using GitHub Actions to speed up development cycles and streamline model deployment.
Streamlining Testing in a Large Python Codebase
Optimize Python testing in large codebases using parallel execution, efficient startup, and targeted coverage reporting. Boost development speed and code quality with practical strategies and open-source tools.
Start Strong! Setting Up Python Projects for Success
Découvrez des outils et techniques pour démarrer efficacement vos projets Python, de la configuration à la gestion des dépendances, en passant par les tests et l'intégration continue.