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Object Storage Management Solution

Case Studies

Client Overview

The customer is startup who provides an Object Storage solution for Enterprise customers who are looking for a storage solution that can reduce their storage costs and manage their workloads in a more transparent fashion.

Business Requirements

The key business requirements put forward by the customer included:

  1. The management solution will serve as the next generation of the current console.
  2. The product will provide a single point solution to manage the cluster of storage servers in the cloud.
  3. The application should provide real-time reports of all activity across the cluster
  4. The customer is also seeking to extend the core storage platform with real time replication and other capabilities.
  5. The replication module will be based on a sophisticated rule-based system.
  6. The system can be easily configured to work with other cloud services such as AWS S3
  7. Server monitoring using Elastic Search, Logstash & Kibana platform

The Solution in Brief

DeviceDriven worked with the customer to create the next generation management solution for their product and also implemented key extensions to the core platform.

  1. Technology Stack: The Management Solution was implemented as a Java8/J2EE based stack which included Spring, Spring Data, Hibernate, Redis, Elastic Search, RabbitMQ and Postgres. The application front-end was implemented as a HTML5, AngularJS, Bootstrap application. The web front-end interacted with the J2EE based backend over a set of REST API’s which were secured using Spring Security.
  2. The Rule Engine module provides a sophisticated yet intuitive web interface which allows users to create flexible rules that are processed by the replication engine.
  3. The core object storage solution which was implemented using Python, Cassandra and Postgres exposed a set of REST API’s via which various metrics were made available to the management application.

C.The DeviceDriven team also worked on the core Python platform developing various API’s and implementing a replication module. Based on the configured rule-set the replicate engine will perform real-time replications of objects within the cluster and also to third party storage services, thereby providing customers with a significant level of flexibility in how they manage their data.

Tags: Python, Cassandra, Java8, J2EE, Spring, Spring Data, Hibernate, MySQL(PostgreSQL) , Redis, ElasticSearch, RabbitMQ, HTML5, AngularJS, Bootstrap, CSS, Zookeeper, S3, SQS,Celery(Distributed Platform)