US based leading manufacturer that produces residential and commercial water heaters and boilers, as well as heating, ventilating and air conditioning equipment delivering a new level of efficiency, convenience and comfort to users.
The client has 75K+ devices (legacy & new) on field and 70+ servers managing and processing those devices. With such a large number of servers involved, it was challenging and a hassle for the client to manage, upgrade and keep all the servers stable. Also, this resulted in huge infrastructure cost. Client was looking for a cost – effective and technologically upgraded solution over AWS that would reduce the number of servers required and simplify the architecture along with long term visibility, maintained security and quick performance without delays. They also require technical support for their customer support team to resolve live devices issues.
VOLANSYS helped its home automation client to simplify the cloud architecture by reducing the number of servers involved from 70+ to mere 10 to effectively manage its 75K+ on-field devices. We developed a cloud based Wi-Fi adapter which has the capacity to manage 8K devices resulting in reduced server requirements. Our team implemented some configuration level changes in AWS EC2 and Linux OS. This Wi-Fi adapter helped the client reduce their infrastructure cost by 60%.
- Developed cloud Wi-Fi adapter using Spring Boot technology, which handles 8K+ concurrent devices
- Merged different technology codes – Dart, Erlang and Java in single Java technology
- Configuration level changes in AWS EC2 using AWS load balancer and Auto Scaling Group that reduced number of servers required from 70+ to just 10
- Integrated AWS S3 for storing devices logs at regular interval of time
- Increased number of Threads support by changing value of threads and file descriptor on OS (Linux 18.04)
- Increased data fetching frequency from field devices to Wi-Fi adapter from 2 minutes to just 3 to 5 seconds making processing 24 times faster
- End-to-end functional testing involving end devices, business application on IoT platform and mobile application
- Conducted load testing for Wi-Fi adapter with simulators (developed using Python & Locust), memory and CPU monitoring using Datadog
- Extended technical support to resolve on-field devices issues
Java 8 | Spring boot | AWS EC2 | S3 | Elastic Load Balancer | Auto Scaling Group | Cloud Migration | Cloud
- Reduced infrastructure cost by 60% with cloud based Wi-Fi adapter
- Robust and simplified architecture with just 10 Wi-Fi adapters, reducing the hassle of managing large servers