Capacity and Planning
Overview
A Cloudify cluster consists of 3 main services:
- Cloudify Manager
 - Database
 - Messaging Queue
 
Cloudify cluster topology assures high availability and should be leveraged for mission-critical deployments. Learn more about the Cloudify cluster.
Cloudify Manager Server
For a highly available setup at least two managers are required, and 3 are recommended.
Recommended resources per manager server:
| RECOMMENDED | |
|---|---|
| vCPUs | 4 | 
| RAM | 8GB | 
| Storage | 32GB | 
- The recommended spec. is for average use of 1,000 - 2,000 workflows per hour and was certified with 1M deployments.
 - Scaling to higher volume can be achieved via:
- Additional Cloudify Managers - an almost linear scaling was verified leveraging 3 - 6 managers.
 - Higher hardware spec. - a linear scaling was verified with stronger hardware.
 
 - The equivalent AWS instance is c5.xlarge.
 - Customized sizing and tunning may further improve the supported scale. Over 2M deployed nodes and over 5,000 workflows per hour were tested in some scenarios.
 
Database (PostgreSQL) Server
For a highly available setup, 3 database servers are required.
Recommended resources per database server:
| RECOMMENDED | |
|---|---|
| vCPUs | 2 | 
| RAM | 16GB | 
| Storage | 64GB | 
- The recommended spec is for average use of 1,000 - 2,000 workflows per hour and was certified with 1M deployments.
 - Scaling to higher volume can be achieved via:
- Higher hardware spec. - a linear scaling was verified with stronger hardware.
 
 - The equivalent AWS instance is r5.large.
 
Messaging queue (RabbitMQ) Server
For a highly available setup, 3 messaging queue servers are required.
Recommended resources per messaging queue server
| RECOMMENDED | |
|---|---|
| vCPUs | 4 | 
| RAM | 8GB | 
| Storage | 32GB | 
- The recommended spec is for average use of 1,000 - 2,000 workflows per hour and was certified with 1M deployments.
 - Scaling to higher volume can be achieved via:
- Higher hardware spec. - a linear scaling was verified with stronger hardware
 
 - The equivalent AWS instance is c5.large.
 
