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The Ready methodology of the Cloud Adoption Framework for Azure can guide you through preparing your environment for cloud adoption. During the readiness phase, you can use an Azure landing zone. A landing zone is a technical accelerator that provides the basic building block for any cloud adoption environment. A landing zone can automate the configuration of your Azure environment, aligning with best practice guidance from the Cloud Adoption Framework. While preparing for high-performance computing (HPC), you might encounter environment configurations that depend on your industry use case and requirements.
As you prepare your environment for sustained cloud adoption, you can use an Azure landing zone conceptual architecture that represents a target end state. For HPC, there are multiple conceptual architecture references that are based on the three industries that the Cloud Adoption Framework currently addresses:
Consider these architecture references as you develop a long-term vision for your landing zone. These references provide a starting point. Based on your organization's business requirements and the needs of your end users, you might need to modify them.
The decisions that you make during strategic impact assessment and technical planning influence the landing zone configuration that you choose for your HPC deployments on Azure. We recommend that you consider the following questions:
As you can see from these questions, the deployment model varies depending on your business, industry, and application usage.
Azure Batch and Azure CycleCloud are both Azure provided 1st party service while Azure HPC OnDemand Platform (AzHOP) is an automation built on top of Azure Cycle Cloud which delivers an end-to-end deployment mechanism for a complete HPC cluster solution in Azure.
Feature | Azure Batch | Azure CycleCloud |
---|---|---|
Scheduler | Batch APIs and tools are available. You can also use cloud-native command-line scripts in the Azure portal. | You can use standard HPC schedulers such as SLURM, OpenPBS, PBSPro, LSF, Grid Engine, and HTCondor. Or you can extend Azure CycleCloud autoscaling plugins to work with your own scheduler. |
Compute resources | Software as a service (SaaS) nodes – platform as a service (PaaS). | PaaS software – PaaS. |
Monitoring tools | Azure Monitor. | Azure Monitor and Grafana. |
Customization | You can use custom image pools, third-party images, or Batch API access. | You can use the comprehensive RESTful API to customize and extend functionality, deploy your own scheduler, and support existing workload managers. |
Integration | Azure Synapse Analytics pipelines, Azure Data Factory, and the Azure CLI. | A built-in CLI for Windows and Linux. |
User type | Developers. | Classic HPC administrators and users. |
Work type | Batches and workflows. | Tightly coupled workflows that use Message Passing Interface (MPI). |
Windows support | Provided. | Depends on the scheduler choice. |
Azure CycleCloud and Azure Batch are powerful tools for HPC tasks on Azure, but they're designed for different use cases.
Azure CycleCloud is an enterprise-friendly tool for orchestrating and managing HPC environments on Azure. It's targeted at HPC administrators and users who want to deploy an HPC environment with a specific scheduler in mind. Azure CycleCloud provides powerful tooling to construct complete HPC environments on Azure, including Network File Sharing (NFS) servers, parallel file systems, sign-in hosts, license servers, and directory services. It's useful for organizations that have operated HPC environments for a while and have accumulated years of expertise and in-house tooling around a specific scheduler.
In contrast, Batch is mostly aimed at developers and teams who build a capability into their own product or service. Batch includes its own scheduler and is designed to run large-scale parallel jobs efficiently without cluster or job scheduler software. Batch is useful when you don't need to manage a workload scheduler.
In summary, use Azure CycleCloud when you want to deploy an HPC environment with a specific scheduler in mind and need a complete HPC environment. Use Batch when you develop a product or service that requires large-scale parallel processing and you don't want to manage a workload scheduler.
Events
May 19, 6 PM - May 23, 12 AM
Calling all developers, creators, and AI innovators to join us in Seattle @Microsoft Build May 19-22.
Register today