Failover Vs. Load Balancing
- A failover cluster (high availability) is a group of servers that work together to maintain high availability of applications and services. If one of the servers, or nodes, fails, another node in the cluster can take over its workload without any downtime (this process is known as failover).
- Load balancing (scaling) improves the distribution of workloads across multiple computing resources and helps to avoid overload of any single resource.
Failover (High Availability)
You can provide failover for Data Services batch jobs only (no real-time jobs) through using a Windows/AIX cluster. Only the DS Job Server is supported on a Windows Cluster.
Almost Failover (High Availability) and Load Balancing
You need to have 2 machines with both Information Platform Services (or Business Intelligence Platform) and Data Services installed and then configure them in the following way:
5. You need to set your SIA's to run under an account that has access to the remote highly available share.
6. Have both DS job servers pointing to same DS repository.
7. Use a Job Server Group to which both of your respective DS job servers belong.
8. Ensure that on each SIA node you have both AJS and EIM APS installed
Note: For batch jobs that are using the RFC Client (loading of BW and extraction from BW via Open Hub) you have to be on Data Services 4.2 SP1 for this to work since the RFC Service that's running on EIM APS will not work correctly if you have two EIM APSs exposing this service and belonging to a clustered CMS environment.
Note: Clustering of BI with IPS is not supported. You can cluster one BI with another BI, and one IPS with another IPS, however not mix them.
Load Balancing - Scaling
Load Balancing Through Job Server Group
Load balancing is achieved through the logical concept Job Server Group.
A server group automatically measures resource availability on each Job Server in the group and distributes scheduled batch jobs to the Job Server with the lightest load at runtime.
All the Job Servers in an individual server group must be associated with the same repository, which must be defined as a default repository. The Job Servers in the server group must also have:
Each computer can only contribute one Job Server to a server group.
Job Server Overhead
Compared to normal Job Servers, Job Servers in a server group each:
- Collect a list of other Job Servers in their server group
- Collect system load statistics every 60 seconds:
- Number of CPUs (on startup only)
- Average CPU load
- Available virtual memory
- Service requests for system load statistics
- Accept server group execution requests
Load Balance Index
Installing Second Job Server
Configuring Second Job Server
Creating Job Server Group
Ensure Jobs Can Run On Any Job Server
See video: Planning for SAP Data Services and SAP Information Steward Installation at http://help.sap.com/bods
1603393 - Installation Scenarios - Data Services 4.x
Check KBA: 1799669 - How to cluster Information Platform Services 4.x with Business Intelligence Platform 4.x
Please reference the Data Services Performance Guide to understand the different methods of distributed execution for DS batch jobs.
Jobs will still have to be re-run and recovery built into them. Please see Designer Guide.
The above configuration does not cover load balancing or scaling of Real-Time jobs. See KBA 1592957 for more info..