
Explore hands-on tracing and APM for Java applications. Learn implementation, benefits, and OpenTracing concepts using Elastic APM and Jaeger agents.

Explore observability beyond logs, metrics, and traces. Learn holistic system monitoring approaches, creating richer events aligned with business needs, and adding value through comprehensive system understanding.

Explore Kubernetes autoscaling and high availability strategies, including scheduling, load balancing, and HA implementation in large-scale clusters.

Explore JVM calibration on Kubernetes, from OS processes to K8s parameters. Gain insights into effective resource management and performance monitoring for optimized application deployment.

Explore Everything-as-Code and GitOps practices for effective collaboration. Learn to design systems for quick GitOps implementation, focusing on infrastructure, observability, and permissions automation.

Explore DataOps principles and practices for data & analytics, comparing similarities and differences with DevOps in software engineering to enhance agility and business value.

Deploy Azure data solutions securely using Infrastructure as Code. Learn maintenance techniques, see a live demo, and access downloadable code for a quick start.

Modernize your data estate with SQL Server containers in Kubernetes. Learn to build a hybrid data estate for flexible deployment options.

Deploy OpenShift on Nutanix stack: Learn benefits, solutions, and interactions. Experts showcase deployment process, prerequisites, scaling, storage configuration, and database deployment.

Explore Red Hat's AI portfolio: from simple chatbots to full-scale MLOps applications for enterprise. Learn about Podman AI Lab, RHEL AI, and OpenShift AI for building and deploying AI solutions.

Explore Podman Desktop's features for managing containers and Kubernetes locally, streamlining development and testing of containerized applications.

Explore computer vision use cases on OpenShift, from data collection and annotation to model training and deployment, with practical demonstrations on cars and trains detection.

Master Kubernetes for data engineering: set up, deploy dashboard, run Apache Airflow with Helm charts. Learn kubectl, manage clusters, and optimize workflows for scalable data processing.

Implement CI/CD for modern data engineering using Azure and Terraform. Automate infrastructure, storage, and data factory deployment with hands-on guidance and practical examples.

Discover modern DevOps practices for on-demand, compliant data delivery in application development and analytics, addressing data sprawl and regulatory challenges in the Microsoft ecosystem.

Tackle challenges in obtaining quality data for test, QA, and CI practices to improve efficiency and reduce failed releases while ensuring compliance.

Explore strategies for migrating customers and internal teams to Kubernetes, focusing on best practices and real-world experiences.

Explore data-driven secure DevOps practices to enhance software delivery speed and quality while maintaining robust security measures.

Explore effective strategies for identifying operational problems through metric analysis, enhancing system monitoring and troubleshooting capabilities.

Explore Kubernetes automation: compare Operators and Helm Charts for efficient cluster management and application deployment strategies.

Explore common IT issues: DNS, TLS, and configuration problems. Learn troubleshooting techniques and best practices for resolving these persistent challenges in software development.