Dimensioning guide

This document provides comprehensive information about the introduction and concepts around Nexthink Chatbot SDK, its API and use cases. The information contained herein is subject to change without notice and is not guaranteed to be error-free. If you find any errors, please report them to us via Nexthink Support Portal. This document is intended for readers with a detailed understanding of Nexthink technology.

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Dimensioning requirements

Appliance requirements

The table below demonstrates recommended hardware characteristics for the Chatbot SDK appliance in relation to the number of Engines and devices. Additionally, it predicts the number of user conversations supported by Chatbot SDK within given parameters.

	CPU, disk & RAM	Number of concurrent conversations
Small: 1 engine 20K devices	2CPUs 10GB disk 4GB RAM	800 concurrent conversations assuming 100 requests to Chatbot SDK per second
Medium: 20 engines 200K devices	2CPUs 20GB disk 8GB RAM	1600 concurrent conversations assuming 200 requests to Chatbot SDK per second
Large: 50 engines 500K devices	4CPUs 40GB disk 16GB RAM	3200 concurrent conversations assuming 400 requests to Chatbot SDK per second

The number of concurrent conversations is estimated with the assumption that every conversation makes 4 requests every 30 seconds. For more information refer to the Measurement methodology section below.

It is preferable to use SSD for the disk storage as there is a lot of data movement in the cache.

Discovery duration

The discovery process is responsible for downloading required information from Engines to the local cache. The table demonstrates the estimated duration time of the discovery process, which depends on the number of engines and bandwidth. The bandwidth between Chatbot SDK and Engines is critical to get a reasonable time for the discovery process.

Bandwidth Chatbot SDK - Engine	Devices	Number of engines	Discovery duration per engine
50 mbps	10k	1	< 1 minute
10 mbps	10k		1 minute
5 mbps	10k		2 minutes
50 mbps	200k	20	1 minute 35 seconds
10 mbps	200k		3 minutes 15 seconds
5 mbps	200k		5 minutes 30 seconds
50 mbps	500k	50	4 minutes
10 mbps	500k		8 minutes 15 seconds
5 mbps	500k		15 minutes

Measurement methodology

Appliance requirements

To validate a scenario with a high number of endpoints, a custom traffic generator was used to interact with the API. Chatbot SDK was installed on virtual machines where Engines were a part of the performance environment running on Azure.

The hardware requirements were calculated to avoid maximum memory and CPU usage when generating traffic that started to stress the engines. The limits were set in order to avoid an impact on the response time of Engines. They were set when the response time started to increase.

To estimate the maximum number of concurrent conversations the following scenario was used:

• For each conversation, there was one request per 30 seconds.

• With this estimation, a hundred simultaneous conversations translate to 400 requests in 30 seconds or around 13 requests per second.

Discovery duration

Different tests were conducted using the same scenario. The variables that had a higher impact on the discovery duration were:

• Network latency

• Number of engines

• Number of devices