System Requirements | Medplum

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Medplum publishes an official agent installer for Microsoft Windows.

To install on a Windows Host, remote into the host and download the agent executable to the host filesystem. Double click on the MSI to start and go through the install screen, inputting the 4 pieces of information from the previous step into the screen.

The agent executable for Windows is built with each release, and can be be downloaded from the releases page.

Operating System (OS)

• Minimum OS: Microsoft Windows 8.1 or Windows Server 2012 R2
• Recommended OS: Microsoft Windows 11 or Windows Server 2022

Random Access Memory (RAM)

• Minimum RAM: 512 MB - Adequate for small-scale applications with minimal processing demands.
• Recommended RAM: 2 GB or more - Advisable for applications that manage extensive in-memory operations, exhibit high levels of user concurrency, or execute multiple background processes.

Central Processing Unit (CPU)

• Minimum CPU: 1 GHz or faster processor, 64-bit (x64) architecture. Single-core CPUs are capable of running Node.js; however, performance may be limited under intensive workloads.
• Recommended CPU: Multi-core processor (2 cores or more). Node.js inherently operates on a single thread, but it can leverage multi-core systems using the cluster module, facilitating concurrent processing and enhancing throughput.

Disk Storage

• Minimum Disk Space: 100-200 MB - Sufficient for the Node.js runtime environment and a basic application footprint.
• Recommended Disk Space: 1 GB or greater - Recommended to accommodate application dependencies, log files, user data, and temporary files. Solid State Drives (SSDs) are preferable for improved read/write performance, which is particularly beneficial when the application frequently accesses the disk.

Note: These specifications represent a baseline that should ensure the functional operation of a standard Node.js application. Actual requirements may vary based on specific application characteristics and workload conditions. We recommend conducting performance evaluations to fine-tune these recommendations to match the application's production environment and anticipated usage patterns.