Hardware Requirements

Overview

Tricentis Analytics 1.3.1 runs on a Windows OS, however, if you are using Linux or Docker you can still use Tricentis Analytics! In this case, you will need to use a Windows VM.

Below are details on hardware requirements that are based on your organizations volume of data, as well as for running the Tricentis Analytics application itself.

Read the information carefully, to gain a full understanding on how Tricentis Analytics is deployed.

Tricentis Product Reporting

Tricentis Analytics provides a combined reporting platform for both Tosca and qTest customers. Your organizations number of servers are also dependent on the Tricentis products you are reporting on.

  • qTest : qTest Manager 9.7.1 and ElasticSearch are required and must be running on other servers than your Tricentis Analytics deployment.
  • Tosca Customers: Tosca Commander is required to be set up on the same server.

Tricentis Analytics Application

The Tricentis Analytics application includes the following components:

  • Snapshotter: this component captures the data from your Tricentis products Reporting Database
  • qTest SyncApp: this component syncs the data from your qTest Reporting Database, to your Tricentis Analytics Reporting Database
  • Tricentis Analytics Web Authority App
  • Qliksense Enterprise

Required Hardware

The number of servers needed to run your Tricentis Analytics application, and its associated Reporting Database are determined by your Data Volume (read more below.) General hardware requirements, are as follows:

  • Windows Server(s) 2012/2016 
    • for the Tricentis Analytics application, and its associated Reporting Database
  • MSSQL 2016
    • used for the Reporting Database

 

Data Volume Size Query

The query below is for qTest customers to run against your Postgres database used for qTest Manager 9.7.1.

SELECT relname, reltuples::bigint AS approximate_row_count
FROM pg_class pc
inner join unnest('{projects,releases,test_suites,requirements,test_cases,test_case_run,defects,test_case_results,custom_fields,requirements_aud,test_cases_aud,defects_aud}'::varchar[])
WITH ORDINALITY t(name, ord)
on pc.oid = t.name::regclass
order by t.ord asc;

 

Data Volume Sizing Guide

Your data volume size determines the number of Windows servers needed. You can find sizing requirements below determined by your Data Volume:

  • Data Size Small: one Windows server
    • used for both Tricentis Analytics and its Reporting Database
  • Data Size Medium and Large: two separate Windows servers
    • one server for Tricentis Analytics
    • one server for the Reporting Database

 

Data Volume Sizing Table

The following table gives an approximate data volume sizing guide to use for hardware specs:

Refer to this table for Data Volume Sizing Specs
  

Data Volume Sizing

 
Data Volume # of Total Machines Tricentis Analytics Reporting DB (MSSQL 2016)

Data Size Small

 

 

 Releases: 600
Requirements: 12,000
Test Cases: 6,000
Test Runs: 12,000
qTest Defects: 5,000
Site Level Fields: 44 

One machine

OS: Windows Server 2012/2016 

16GB RAM  

CPU 2.50GHz (4CPUs)  

HDD 200GB+  

Data Size Medium

 

 

 

 Releases: 1,200
Requirements: 120,000
Test Cases: 840,000
Test Runs: 600,000
qTest Defects: 30,000
Jira Defects: 30,000
Site Level Fields: 55
Jira Defect Custom Fields: 50  
Two separated machines, one for Tricentis Analytics and one for the reporting database  OS: Windows Server 2012/2016 
  16GB RAM 
CPU 2.50GHz (4CPUs) 
HDD 200GB+
  OS: Windows Server
2012/2016 (for MSSQL 2016)     8GB RAM 
CPU 2.50GHz (4CPUs) 
HDD 200GB+  

Data Size Large

 

 

 

 Releases: 2,500
Requirements: 150,000
Test Cases: 1,000,000
Test Runs: 1,000,000
qTest Defects: 120,000
Jira Defects: 30,000
Site Level Fields: 55
Jira Defect Custom Fields: 50 

Two separated machines, one for Tricentis Analytics and one for the reporting database

OS: Windows Server 2012/2016    
32GB RAM 
CPU 2.50GHz (4CPUs) 
HDD 200GB+ 
 OS: Windows Server 2012/2016 (for MS SQL 2016)
    8GB RAM
  CPU 2.50GHz (4CPUs)
  HDD 200GB+ 

 

 


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Tricentis Analytics Manual 1.3.1 © Tricentis GmbH