Hardware Sizing

Sizing is the process of determining the hardware requirements for different slabs of workload. This is an interim document created to provide guidance for immediate 19.1 release deployments. The recommendations here are based on performance test runs (refer factsheet) conducted before product GA release.

These guidelines do not reflect the optimum recommended hardware for running AssistEdge. This document will be refined and updated to reflect the optimum recommendations based on different workloads. Please refer the latest updated document for provisioning production infrastructure for your engagements.

 

General Guidelines

The guidelines mentioned here are based on the validations carried out in a testing environment under specific load conditions. The server usage in the client environment varies depending on the workload and amount of data in the system. It is recommended to periodically analyze the server resource utilization and consider corrective measures.

 

Periodic archival of the data is advised. If data storage in a live system is mandatory, the configurations of the servers are to be reviewed based on the resource utilization levels seen at the implementation site.

 

The recommended server configurations support number of users/bots as per slabs, the number of automation requests processed, user types, automation complexities, and functionalities implemented. As additional users/bots/workflows are added, requests processing count increased, or if new functionalities are implemented, additional resources may need to be added to the servers.

 

Hardware Configurations

This section explains the AssistEdge RPA and Engage capacity plan scenarios for various usage scenarios. Refer the appropriate scenario depending on your implementation plan. An update to this document will provide guidance on different slabs per scenario and recommended hardware sizing.

 

Below suggestions for RPA setup are based on the automation processing load of up to 8 requests per hour per bot based on the automation process execution time.

 

Note: Below guidelines do not indicate the minimum hardware footprint of the platform for meeting a given usage scenario. The H/W guidelines are based on hardware provisioned for actual performance tests; these will be refined further to a more optimum recommended H/W based on follow-on tests.

 

The physical to virtual cores ratio is considered to be 1:2. That is, 1 physical core = 2 logical/virtual cores = 2 vCPUs

 

Reports: The reporting function utilization depends on the data queried and frequency. The system has been tested for RPA reports from a total Open Distro store size of 224 GB and Engage reports from a total Open Distro store size of 150GB. If report requirements are of higher size and frequency, the capacity of the servers should be increased appropriately as per the utilization level observed at the implementation site

 

The hardware recommendations mentioned below are based on the tests carried out. The numbers will be revised with test results from the increased load.

For requirements not mentioned in the document, please get in touch with the product team.

 

Scenarios

This section explains the AssistEdge RPA and Engage capacity plan scenarios for various usage scenarios. Refer the appropriate scenario depending on your implementation plan.

 

Below suggestions for RPA setup are based on the automation processing load of up to 8 requests per hour per bot based on the automation process execution time.

 

Engage setup suggestions are based on load tests performed on various slabs of concurrent logged in users.

The physical to virtual cores ratio is considered to 1:2. That is, 1 physical core = 2 logical/virtual cores = 2 vCPUs

 

Reports: The reporting function utilizations will depend on the data queried and frequency. The system has been tested for RPA reports from a total Elastic store size of 327 GB and Engage reports from a total Elastic store size of 224 GB. If report requirements are of higher size and frequency, the capacity of the servers should be increased appropriately as per the utilization level observed at the implementation site

The hardware recommendations below are based on the tests carried out in internal systems engineering Lab.

 

AssistEdge RPA Capacity Plan Scenarios

For AssistEdge RPA, the capacity plan is provided as per below slabs:

Non-HA Deployment

  • Small scale deployment up to 5 bots, 10 bots and 50 bots
    Small scale deployment to cater up to 5 bots, 10 bots, and 50 bots. Web and App components are in single server.
  • Medium scale deployment up to 250 bots
    Medium scale deployment to cater up to 250 bots. Web and App components are in single server.
  • Medium scale deployment up to 250 bots
    Medium scale deployment will cater up to 250 bots in the environment. Web and App components are in a Clustered setup. This also helps in High Availability.
  • Large scale deployment up to 500 bots, and 700 bots
    Large scale deployment will cater up to 700 bots in the environment. Web and App components are in a Clustered setup. This also helps in High Availability.


AssistEdge RPA With Low Code Orchestrator Capacity Plan Scenarios

For AssistEdge RPA with low code process orchestrator, the capacity plan is provided as per below slabs:

 

Non-HA Deployment

  • Small scale deployment up to 5 bots, 10 bots and 50 bots
    Small scale deployment to cater up to 5 bots, 10 bots, and 50 bots. Web and App components are in single server.
  • Medium scale deployment up to 200 bots
    Medium scale deployment to cater up to 200 bots. Web and App components are in single server.
     

    NOTE: 

    Non-HA environment depicts the scalability of the application. High Availability setup is recommended in Production environment.

HA Deployment

  • Medium scale deployment up to 200 bots
    Medium scale deployment will cater up to 200 bots in the environment. Web and App components are in a Clustered setup. This also helps in High Availability.

  • Large scale deployment up to 500 bots, and 600 bots
    Large scale deployment will cater up to 600 bots in the environment. Web and App components are in a Clustered setup. This also helps in High Availability.

AssistEdge Engage Capacity Plan Scenarios

For AssistEdge Engage the capacity plan is provided as per below slabs:

 

Non-HA Deployment

  • Deployment for up to 50 logged in users
    Deployment to cater up to 50 logged in users. Web and App components are in single server.
  • Deployment for up to 300 logged in users
    Deployment to cater up to 300 logged in users. Web and App components are in single server.
     

    NOTE: 

    Non-HA environment depicts the scalability of the application. High Availability setup is recommended in Production environment.

     

HA Deployment

  • Deployment for up to 500 logged in users
    Deployment to cater up to 500 logged in users. Web and App components are in cluster setup.
  • Deployment for up to 1000 logged in users
    Deployment to cater up to 1000 logged in users. Web and App components are in cluster setup.
  • Deployment for up to 2000 logged in users
    Deployment to cater up to 2000 logged in users. Web and App components are in cluster setup.

 

AssistEdge Engage with Low Code Orchestrator Capacity Plan Scenarios

For AssistEdge Engage with low code orchestrator (web engage) the capacity plan is provided as per below slabs:

 

Non-HA Deployment

  • Deployment for up to 50 logged in users
    Deployment to cater up to 50 logged in users. Web and App components are in single server.
  • Deployment for up to 300 logged in users
    Deployment to cater up to 300 logged in users. Web and App components are in single server.
     

    NOTE: 

    Non-HA environment depicts the scalability of the application. High Availability setup is recommended in Production environment.


     
  • Deployment for up to 500 logged in users
    Deployment to cater up to 500 logged in users. Web and App components are in cluster setup.
  • Deployment for up to 1000 logged in users
    Deployment to cater up to 1000 logged in users. Web and App components are in cluster setup.
  • Deployment for up to 2000 logged in users
    Deployment to cater up to 2000 logged in users. Web and App components are in cluster setup.

 

Hardware Recommendations

RPA Capacity Plan: Non-HA Deployment

Deployment Type

Web/App Server Configuration

DB Server Configuration

Remarks

Small scale deployment up to 5 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8 GB RAM, 50 GB storage

DB can be a shared service with the mentioned specification.

Small scale deployment up to 10 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8 GB RAM, 50 GB storage

Small scale deployment up to 50 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8-12 GB RAM, 50 to 100 GB storage

Medium scale deployment up to 250 bots

1 X (4 vCPU 16 GB RAM, 300 GB)

4 vCPU 12 GB RAM, 50 to 150 GB storage

 

 

RPA Capacity Plan: HA Deployment

Deployment Type

Web/APP Server Configuration

DB Server Configuration

Remarks

Medium scale deployment up to 250 bots

3 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 12 GB RAM, 50 to 150 GB storage

DB can be a shared service with the mentioned specification.

 

System is scalable up to 700 Bots depending on the workload and transaction data volume.

Large scale deployment of up to 500 Bots

3 X (4vCPU 16 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 200 GB storage

Large scale deployment of up to 700 Bots

3 X (4vCPU 16 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 300 GB storage

 

 

 

 

RPA with Low Code Process Orchestrator: Non-HA Deployment

 

Deployment Type

Web/App Server Configuration

DB Server Configuration

Remarks

Small scale deployment up to 5 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8 GB RAM, 50 GB storage

DB can be a shared service with the mentioned specification.

Apps built on low code orchestrator are executed on server side.

Scalability will be impacted by application’s complexity, user load and transaction volumes.

Small scale deployment up to 10 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8 GB RAM, 50 GB storage

Small scale deployment up to 50 bots

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 8-12 GB RAM, 50 to 100 GB storage

Medium scale deployment up to 200 bots

1 X (4 vCPU 16 GB RAM, 300 GB)

4 vCPU 12 GB RAM, 50 to 200 GB storage

 

RPA with Low Code Process Orchestrator: HA Deployment

 

Deployment Type

Web/APP Server Configuration

DB Server Configuration

Remarks

Medium scale deployment up to 200 bots

3 X (4 vCPU 12-16 GB RAM, 300 GB)

4 vCPU 12 GB RAM, 50 to 200 GB storage)

DB can be a shared service with the mentioned specification.

Apps built on low code orchestrator are executed on server side.

Scalability will be impacted by application’s complexity, user load and transaction volumes.

Large scale deployment up to 500 Bots

3 X (4 vCPU 16 GB RAM, 300 GB)

4 vCPU 12-16 GB RAM, 100 to 300 GB storage)

Large scale deployment up to 600 Bots

3 X (4 vCPU 16 GB RAM, 300 GB)

4 vCPU 12-16 GB RAM, 100 to 300 GB storage)

 

 

 

 

 

Engage: Non-HA and HA Deployment

 

Deployment Type

Web/App Server Configuration

DB Server Configuration

Remarks

Non-HA Deployment up to 50 logged in users

1 X (4 vCPU 12 GB RAM, 200 GB)

4 vCPU 12 GB RAM, 50 GB storage

DB can be a shared service with the mentioned specification.

Non-HA Deployment up to 300 logged in users

1 X (4 vCPU, 16 GB RAM, 200 GB)

4 vCPU 12 to 16 GB RAM, 100 GB storage

HA Deployment up to 500 logged in users

3 X (4 vCPU, 12-16 GB RAM, 300 GB)

4 vCPU 12 to 16 GB RAM, 50 to 300 GB storage

HA Deployment up to 1000 logged in users

3 X (4 vCPU, 16 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 50 to 300 GB storage

HA Deployment up to 2000 logged in users

3 X (8 vCPU, 24-32 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 100 to 300 GB storage

 

 

 

 

 

 

 

 

 

 

 


 

 

Engage with Low Code Orchestrator: Non-HA and HA Deployment

 

Deployment Type

Web/App Server Configuration

DB Server Configuration

Remarks

Non-HA Deployment up to 50 logged in users

1 X (4 vCPU 12 GB RAM,

200 GB)

4 vCPU 12 GB RAM, 50 GB storage

DB can be a shared service with the following specification.

 

Apps built on low code orchestrator are executed on server side.

 

Scalability will be impacted by application’s complexity, user load and transaction volumes.

Non-HA Deployment up to 300 logged in users

1 X (4 vCPU, 16 GB RAM, 200 GB)

4 vCPU 12 to 16 GB RAM, 100 GB storage

HA Deployment up to 500 logged in users

3 X (4 vCPU, 12-16 GB RAM, 300 GB)

4 vCPU 12 to 16 GB RAM, 50 to 300 GB storage

HA Deployment up to 1000 logged in users

3 X (4 vCPU, 16 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 50 to 300 GB storage

HA Deployment up to 2000 logged in users

3 X (8 vCPU, 24-32 GB RAM, 300 GB)

4 vCPU 16 GB RAM, 100 to 300 GB storage

 

 

Following are recommendations for setting up of heap size:

 

User Base

Recommended Elastic Heap Size

50 Logged in Users without reports

1 GB

50 Logged in Users with reports

2 GB

500 - 1000 Logged in Users

4 GB

2000 Logged in Users

8 GB

 

 

 

 

 

 

 

 

Suggestions

Following are the guidelines on server types in Azure and AWS:

Azure: Corresponding configuration in General Purpose D series can be looked at for production implementations.

AWS: Corresponding configuration in General Purpose M series can be looked at for production implementations.

 

Refer AssistEdge Hardware Sizing recommendations for the different supported scenarios for automation deployment. In addition, following are a few generic recommendations:

  • Adjust/ increase heap size of ElasticSearch based on the total number of robots and concurrent requests being processed.
  • Sizing for machines running robots should factor resource utilization by 3rd party client applications and number of bots planned in the machine.
  • Ensure appropriate Load Balancer settings in HA deployment to ensure that load is distributed evenly amongst the different nodes of the configured cluster.

 

Engage-RPA-Automation Studio Client/ Development Components

Below requirements are applicable for Engage Client, Automation Studio and Robot Farm.

 

Technical Component

Hardware requirement

Remarks

Engage Client/ AE Attended RPA/ Albie Workbench

Minimum:

2 Core 4+ GB RAM

 

NOTE: Disk space: 1 GB for product binaries. Remaining disk space to be calculated based on number of Robots and expected log size etc. consideration.

Minimum head room required for the client tools is 15% of CPU and 120 MB RAM

Automation Studio

Robot Farm including Robot Agent, Robot and Proctor