7.2
Table Of Contents
- Reference Architecture
- Contents
- vRealize Automation Reference Architecture Guide
- Updated Information
- Initial Deployment and Configuration Recommendations
- vRealize Automation Deployment
- vRealize Business for Cloud Deployment Considerations
- vRealize Automation Scalability
- vRealize Business for Cloud Scalability
- vRealize Automation High Availability Configuration Considerations
- vRealize Business for Cloud High Availability Considerations
- vRealize Automation Hardware Specifications
- vRealize Automation Small Deployment Requirements
- vRealize Automation Medium Deployment Requirements
- vRealize Automation Large Deployment Requirements
- Index
vRealize Automation Scalability 4
Consider all applicable scalability factors when conguring your vRealize Automation system.
Users
The vRealize Automation appliance is congured for syncing less than 100,000 users. If your system
contains more users, you may need to add memory to vRealize Automation Directories Management. For
detailed information on adding memory to Directories Management, see "Add Memory to Directories
Management" in Conguring vRealize Automation.
Concurrent Provisions Scalability
By default, vRealize Automation processes only eight concurrent provisions per endpoint. For information
about increasing this limit, see Conguring vRealize Automation.
VMware recommends that all deployments start with at least two DEM-Workers. In 6.x each DEM-Worker
could process 15 workows concurrently. This was increased to 30 for vRealize Automation 7.0 and later.
If machines are being customized through Workow Stubs, you should have 1 DEM-Worker per 20
Machines that will be provisioned concurrently. For example, a system supporting 100 concurrent
provisions should have a minimum of 5 DEM-Workers.
For more information on DEM-Workers and scalability see “Distributed Execution Manager Performance
Analysis and Tuning,” on page 19
Data Collection Scalability
Data collection completion time depends on the compute resource capacity, the number of machines on the
compute resource or endpoint, the current system, and network load, among other variables. The
performance scales at a dierent rate for dierent types of data collection.
Each type of data collection has a default interval that you can override or modify. Infrastructure
administrators can manually initiate data collection for infrastructure source endpoints. Fabric
administrators can manually initiate data collection for compute resources. The following values are the
default intervals for data collection.
Table 4‑1. Data Collection Default Intervals
Data Collection Type Default Interval
Inventory Every 24 hours (daily)
State Every 15 minutes
Performance Every 24 hours (daily)
VMware, Inc. 17