Mon. May 29th, 2023

Sametime High Availability, what does it mean and what resources are available?

Sametime High Availability is the deployment of the Sametime Services into Clusters and the necessary modules to support fail over of the services, if one instance of a service goes down, then another instance is able to take over, without the end user being aware. This is accomplished through the user of Load Balancers, WAS HTTP Proxies, WAS SIP Proxies, and clustering the services. Please note this is not Disaster Recovery, which is another topic. There are some specific points you need to keep in mind when planning High Availability:

  • Synchronize the system clocks across all Sametime Servers
  • Clustering is not supported across the WAN.
  • Clustering Sametime Meeting server, the Recording Capturer Server and Recording Renderer Server subcomponents must be deployed on their own individual servers.  Do not install with the Base Meeting Server and Conversion Services with either the Recording Capturer Server or Recording Renderer Server.
    • Do not cluster Recording Capturer Server or Recording Renderer Server, instead create a server farm that host the same configuration role, for each with a load balancer in front.
    • Recording Renderer Server must be installed on a Win32/64 Server.
  • Use DB2 HADR for High Availability of your IBM DB2 Server.
  • WAS HTTP Proxy is required once you cluster Sametime Meeting Server.
  • WAS SIP Proxy is required once you cluster Sametime Media Manager Components
  • Never Cluster WAS HTTP Proxies, or WAS SIP Proxies
  • Start off with the latest versions of Sametime 9.0.  Find them here.

Sametime High Availability Resources:

By Jeffery Miller

I am known for being able to quickly decipher difficult problems to assist development teams in producing a solution. I have been called upon to be the Team Lead for multiple large-scale projects. I have a keen interest in learning new technologies, always ready for a new challenge.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: