
Learn to transition machine learning projects from Jupyter notebooks to production environments, covering MLOps best practices and real-world implementation strategies.

Explore cloud-native development challenges, platform engineering solutions, and developer portals. Learn about Red Hat Developer Hub and security best practices for empowering developer experiences.

Explore a secure, scalable AWS serverless solution using Bedrock for generative AI tasks. Learn architecture, deployment, cost estimation, and advanced features for efficient platform engineering.

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.

Explore strategies for building highly available applications, from microservices and load balancing to global disaster recovery, enhancing system resilience and reliability.

Explore building a serverless GenAI platform, from architecture to adoption strategies, and learn its impact on various industries.

Explore AWS observability using Datadog, covering challenges, fundamentals, implementation as code, and advanced techniques for effective platform engineering and monitoring.

Explore team topologies in platform engineering, covering key principles, team dynamics, real-world examples, and strategies for building effective platforms as products.

Explore AI-augmented DevOps and platform engineering strategies to optimize workflows, identify bottlenecks, and implement real-world solutions for improved efficiency.

Explore effective cloud governance strategies with experts, covering cost-efficiency, performance, and security. Gain practical insights for implementing robust cloud management across your organization.

Explore DevOps strategies for user retention, focusing on customer data, collaboration, and product improvements to drive business impact and stay competitive.

Explore strategies for fostering a robust testing culture, addressing challenges in automated testing, and promoting collaboration for efficient software delivery.

Discover effective techniques to assess candidates' soft skills and technical abilities, ensuring the right fit for your engineering team and company culture.

Explore strategies for prioritizing code quality in engineering teams, focusing on communication, incentives, and practical techniques for busy developers.

Discover strategies to identify and prevent burnout in engineering teams, fostering a healthy work environment for optimal performance and well-being.

Explore effective strategies for mentoring and developing early-career engineers, including onboarding, coaching, and creating structured career paths for rapid growth and success.

Discover strategies for successful technology migrations, preserving engineering velocity, and maintaining team autonomy through real-world lessons and experiences.

Explore principles of vibrant cities applied to codebases, enhancing software team dynamics and productivity through innovative urban planning concepts.

Discover effective observability practices and microservice architecture patterns for organizational success in distributed systems.

Explore localization strategies for global car markets with code examples, modularization techniques, and insights on team collaboration.

Explore a revolutionary approach to software architecture decisions, emphasizing collaborative practices and dismantling traditional hierarchies.