HPC Cluster Management with Slurm on Azure CycleCloud

High-performance computing (HPC) in the cloud requires robust orchestration to handle complex, resource-intensive workloads efficiently. This text-based course guides you through the process of utilizing the Slurm job scheduler within Azure CycleCloud to run scale-out applications. You will transition from understanding basic HPC concepts to confidently managing cluster resources, configuring partition queues, and optimizing node autoscaling. You will learn how to align cloud infrastructure with computational demands while keeping resource usage efficient. What you will learn: - Understand the foundational concepts of HPC clustering, job scheduling, and cloud orchestration. - Configure Slurm partitions, nodes, and queues to match diverse workload requirements. - Deploy scalable cluster configurations within Azure CycleCloud using best-practice templates. - Manage job submissions, priority rules, and execution policies for optimal throughput. - Implement dynamic autoscaling strategies to automatically adjust compute nodes based on active queue demands. - Troubleshoot common cluster initialization, network, and scheduling issues through structured diagnostics. The course begins with essential HPC and scheduling terminology before guiding you through step-by-step text explanations of cluster configuration and job execution. You will read real-world scenarios and analyze configuration files to build practical cluster management skills. This course is designed for system administrators, cloud engineers, and researchers new to cloud-based HPC. No prior experience with Slurm or CycleCloud is required, though a basic familiarity with Linux command-line concepts is helpful. Start reading today to build and scale your first high-performance computing cluster in the cloud.