IoT scalability and performance testing of your IoT Platform

The Value Proposition

IoT scalability and performance testing software helps enterprises that have already deployed or are starting to deploy IoT solutions in their IoT implementation and scaling process by ensuring that their end-to-end IoT solution can scale from proof-of-concept (POC) to production levels. This leads to faster time-to-market and decreased implemented risk for IoT use cases, thereby helping CTOs, leaders of digital business units, engineering leadership, and testing teams. 

The Problem

Enterprises and IoT service providers deploy IoT use cases without knowing if they can properly scale and if they can perform with high resiliency and reliability at production-level scale. Surprisingly, less than 10% of enterprises with IoT solutions have properly tested their end-to-end IoT software stacks. Without doing IoT performance testing, an enterprise risks large cost overruns, SLA penalties, and poor customer satisfaction for their at-scale IoT deployments.

The Solution

Fortunately, IoT performance testing software is built just for this need—helping enterprises minimize the risk of scaling-up an IoT solution, improving IoT solution performance, and accelerating time-to-market. IoT performance testing software allows enterprises to test, validate, and improve the resiliency of their end-to-end IoT solutions before they move to at-scale production. And experienced IoT testing team can help your engineering and DevOps teams test, tune, and improve your end-to-end IoT solution.

Return On Investment

The ROI of using IoT performance testing software to conduct IoT simulations and load testing is impressive. By using IoT testing software rather than legacy, website-testing tools, one multinational industrial is currently saving 60% in testing infrastructure costs and over 50% in time-to-complete performance testing. These saving are substantial and allow the industrial to devote more resources to the ongoing improvement of its end-to-end IoT software stack.

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