
Explore GitOps principles for ML in production. Learn to apply GitOps to deployment, onboarding, monitoring, and model lifecycle stages for enhanced traceability and productivity.

Discover best practices for building effective ML platforms. Learn key components, justification strategies, and how ML infrastructure differs from software infrastructure.

Master Dagger for streamlined CI/CD workflows. Hands-on tutorial covers architecture, practical applications, and community collaboration. Transform software automation with this powerful cross-language scripting engine.

Explore the transformative impact of Backstage developer portal on software development workflows, collaboration, and productivity. Gain insights into real-world scenarios and best practices for leveraging this open-source framework.

Explore composite Site Reliability Guardians for monitoring application health across multiple services. Learn to leverage SLOs and Dynatrace's tools for effective service-level and application-level health validation.

Explore SciML's infrastructure practices in Julia, covering documentation, testing, error handling, and benchmarking. Gain insights into scalable and reproducible numerical ecosystems for Julia developers.

Explore streamlined machine learning workflows in Julia, integrating package development principles and MLflow for robust, reproducible, and scalable model creation and management.

Explore Anyscale's Governance Suite for AI platforms, addressing security, controls, and productivity challenges in the era of Generative AI. Gain insights into sustainable AI practices for modern enterprises.

Unlock efficient distributed ML pipelines with Ray Train. Explore solutions for setup, integration, debugging, fault tolerance, and data processing challenges in scalable machine learning workflows.

Explore GitHub Actions for documentation automation, from basic concepts to practical implementation, benefits, and potential drawbacks in this comprehensive technical presentation.

Explore the comprehensive approach to platform engineering beyond Backstage, integrating frontend and backend components for a robust Internal Developer Platform. Learn effective strategies and see a live demo.

Explore the concept of 'shift left' in security, its impact on developers, and the effectiveness of this approach for development teams.

Gain insights into AI debugging strategies, from practical tips to handling complex models. Learn about data privacy, continuous monitoring, and effective techniques for junior engineers in ML systems.

Explore best practices for securing Kubernetes clusters, covering control plane, node-level, application, and network security strategies. Gain insights into real-world incidents and essential tools for robust K8s protection.

Explore how AI revolutionizes incident management for SRE teams, enhancing triage, communication, and analysis. Learn to leverage AI for faster investigations and improved post-mortems in this insightful conference talk.

Explore AIOps implementation in AWS for predictive maintenance, covering CloudWatch capabilities, data lake approaches, and DevOps Guru for enhanced cloud operations and incident management.

Explore how cloud technologies and Java revolutionize incident management, from microservices to serverless computing, enhancing real-time monitoring, automated responses, and data-driven insights for faster resolution.

Discover strategies for robust monitoring systems, from redundancy and isolation to health checks and cloud services. Learn to effectively monitor your monitoring for enhanced reliability and performance.

Explore the transformative impact of AI-driven automation on software development, focusing on code review and quality assurance. Gain insights into benefits, real-world applications, challenges, and future trends in intelligent automation.

Dive into SLSA compliance for supply chain security using CNCF tools. Explore GitHub Actions, Cosign, Kyverno, in-toto, and Kubescape to secure software from build to runtime in Kubernetes ecosystems.

Dive into Infrastructure as Code on AWS, exploring best practices, patterns, and solutions for treating infrastructure deployment like software delivery. Learn to scale and manage cloud resources effectively.