Help us improve your experience.

Let us know what you think.

Do you have time for a two-minute survey?

 
 

Recommended Apstra Server VM Resources

The required VM resources for an Apstra server may be greater than the recommendations below. Requirements are based on the size of the network (blueprint), the number of off-box agents, and the number of Intent-Based Analytics (IBA) probes. If one VM is insufficient for your needs, you can increase resources by clustering several VMs (Platform / Apstra Cluster). For more information about Apstra Server Clustering, see https://juniper.net/documentation/us/en/software/apstra4.2/Apstra-Server-Clustering-Guide/Apstra-Server-Clustering-Guide.html

Resource Recommendation
Memory 64 GB RAM + 300 MB per installed off-box agent*
CPU 8 vCPU
Disk 80 GB
Network 1 network adapter, initially configured with DHCP
Note:

Apstra off-box agent memory usage is dependent on the number of IBA collectors enabled. We recommend that you use the Apstra UI to monitor memory/cpu usage in the Cluster Monitoring tab.

Dashboard for cluster monitoring showing memory usage at 8 GB across top 12 nodes over the last day in a linear graph with hourly intervals.

Cluster management interface showing node 172.20.75.3 named controller with roles controller, tags iba and offbox, capacity score 119, 4 CPUs. Usage: 3 percent container service with 10 containers, 67 percent memory, 6 percent CPU. Disk usage: aos-server-vg-var/log 4 percent, aos-server-vg-root 41 percent, aos-server-vg-var/lib/aos/db 0 percent, aos-server-vg-var 17 percent. Options for expanded or compact view.

Table showing container details with columns: Name, State, Debug Mode, Memory Usage Mb, CPU Usage, and Cumulative File Size Mb. Memory Usage is highlighted.
Note:

Although an Apstra server VM might run with fewer resources than specified above, the CPU and RAM allocations may be insufficient, depending on the size of the Apstra network. In this case, the system encounters errors or a critical “segmentation fault” (core dump). If this happens, delete the VM and redeploy it with additional resources.

Related Documentation