aiShare Your Requirements
Technologies Involved:
POSTGRESQL
KUBERNETES
Area Of Work: Machine Learning
Project Description

A fast-growing IoT enterprise focused on remote device telemetry and control sought a scalable solution to support its expanding network of connected devices. The client required a robust Kubernetes-based deployment of ThingsBoard to manage high-frequency data, ensure uptime, and streamline orchestration. Oodles delivered a customized microservices setup designed for real-time IoT infrastructure.

Scope Of Work

The project aimed to simplify microservices deployment while enabling flexibility in database configuration, container orchestration, and API-based data handling. The client sought Oodles for an automated solution to manage deployments, scale resources dynamically, and support protocols like REST and MQTT. The scope covered areas such as cluster setup, ingress routing, database provisioning, and resource monitoring.

Our Solution

To meet the client's requirements, Oodles deployed ThingsBoard in Kubernetes-based microservices mode, enabling scalable IoT data management with automated provisioning and flexible architecture. Key features include:

  • Dynamic Deployment Configuration: Allowed switching between PostgreSQL and hybrid (PostgreSQL + Cassandra) database setups through a single .env file.
  • High-Availability Infrastructure: Enabled clustered deployment of Redis, Kafka, and Zookeeper to ensure resilience and failover support for critical services.
  • Automated Setup and Upgrade: Utilized CLI scripts for installation, third-party resource deployment, and version upgrades with rollback capability.
  • Ingress Routing: Configured ingress controllers on Minikube for seamless access to the ThingsBoard UI and REST/MQTT APIs.