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SoftServe IoTForge

IoTForge is a load and performance testing tool designed to simulate production-scale workloads on IoT infrastructure. It supports testing by interacting with infrastructure via different industry standard protocols, enabling businesses to validate systems behavior under different conditions, ensuring optimization, cost efficiency and readiness for future growth. With real-time monitoring, detailed reporting, and customizable scenarios, IoTForge provides a comprehensive testing capabilities to identify bottlenecks, scalability issues, and other limitations.

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About

In IoT infrastructure, ensuring optimal performance and scalability is essential to support large-scale device networks, especially as deployments grow into the hundreds of thousands or millions. Performance bottlenecks, scalability issues, and potential failures can result in costly inefficiencies and operational disruptions. IoTForge, a load and performance testing tool built on the Locust framework, helps prevent such problems by simulating large-scale loads for IoT environments. By incorporating custom test scenarios using MQTT, HTTP(S), and other protocols, IoTForge enables comprehensive system analysis, allowing businesses to proactively identify and address system limitations and performance constraints. This helps prevent major failures, improves infrastructure cost-efficiency, and optimizes system readiness before large-scale deployment.

What we do:

Provide expert services through SoftServe’s Center of Excellence (CoE) teams.

Utilize the IoTForge accelerator to validate IoT infrastructure performance under load.

Leverage AWS cloud-native components to streamline IoTForge deployment and integrate with the system under test.

Offer development and customization of test scenarios tailored to specific requirements.

Deliver a system evaluation report with insights on potential bottlenecks and recommendations for their elimination.

What you get:

Cost savings: minimize downtime and maintenance costs by detecting and addressing issues early.

Risk mitigation: identify weaknesses to prevent system failures and disruptions.

Measurable impact: use of data-driven insights to enhance efficiency and resource use.

Improved scalability: optimize resource usage to ensure desired performance metrics and scalable growth.

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