Load simulation for validating your cloud usage estimates

Iteratively fine-tune the system and optimize your cloud cost

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Success Story: Cloud Usage Optimization

Cloud Usage Optimization

IoT app architectures are multi-layered with each component having its own throttles, queue sizes, and throughput specifications. With such a complex stack, theoretical estimates of cloud consumption often don’t hold true in production. This can adversely impact your P&L in unimaginable ways as the application scales.

Doppelio lets you easily simulate load scenarios to validate your cloud usage estimates. You can iteratively fine tune the system and optimize your cloud usage before releasing it into production.

 

Doppelio Screen

Cost impact analysis throughout the cycle

Initial Design to Go-Live

  • Test prototypes / MVPs for projected loads to establish business case viability
  • Test builds for different scales to ensure that the unit costs hold
  • System test with various loads prior to go-live to ensure cloud cost is within estimates

Major Releases

  • New features and platform changes can impact message sizes, compute, and storage requirements
  • Important to monitor the cost assumption in every program increment
  • System test with various loads prior to go-live to ensure cloud cost is within estimates

Minor Releases

  • Even without significant feature additions, configurations and resource requirements could have changed resulting in deviations from the baseline cost
  • System test with various loads prior to go-live to ensure cloud cost is within estimates

Purpose-built to test IoT applications

  • Doppelio’s patent-pending approach leverages the concepts of virtualization and simulation to give you a testbed that is a very close replica of the real world.
  • Test scenarios are easy to create with Doppelio Web Application without having to write even a single line of code.
  • Doppelio is being continuously updated to incorporate new protocols and IoT platforms to enable test automation of your unique IoT environment.

  • Support for popular protocols like MQTT, AMQP, Protobuf, RabbitMQ, HTTP,  custom application protocols built on TCP/UDP, and more.

  • Out-of-the-box support for IoT Cloud platforms like Azure IoTHub, AWS IoT Core, and Google Cloud IoT. Custom-built IoT platforms are also supported.

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