What servers do I need to record Microsoft Teams? - Call Recording

What servers do I need to record Microsoft Teams?

In most cases, the Atmos deployment for Microsoft Teams compliance recording is deployed on our global cloud infrastructure and does not require the deployment of either on-prem or cloud-based recording or capture services.

However, there are exceptions to this, namely:

  • The customer wants dedicated infrastructure (not shared with other companies).
  • The customer wants to record Microsoft Teams video or screen sharing and wants to ensure bandwidth availability.
  • The customer wants to control all data flow through their cloud (Azure) environment.
  • The customer requires full or partial on-premise deployment (usually associated with regulatory compliance \ data sovereignty) needs.

Once the decision to deploy an on-prem \ cloud server has been reached, there are additional considerations, specifically when designing the size and number of servers required for Video. These considerations include:

  • The size (resolution) of the Video being recorded (recommended 320 x 180p).
  • The size (resolution) of the screen share being recorded (recommended 1080p).
  • The number of concurrent video sessions (at peak).
  • The number of active participants to be recorded simultaneously (Microsoft limits this to 9).
  • The number of servers to be deployed (redundancy).

The minimum VM instance for hosting a recording server (real-time media bot) must have at least 4 CPU cores. For Azure, a Dv2-series virtual machine is recommended. For other Azure VM types, a system with 4 virtual CPUs (vCPU) is the minimum size required. For Azure deployments, we recommend a Standard_B4ms VM size.

Our engineering team is available to discuss the configuration options and to design a deployment architecture that meets each customer’s unique requirements.

Additional Resources:
https://docs.microsoft.com/en-us/microsoftteams/platform/bots/calls-and-meetings/requirements-considerations-application-hosted-media-bots#scalability-and-performance-considerations

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