Generating new revenue stream for an enterprise search solutions provider through porting of a flagship search product to a cloud computing platform
Enterprises worldwide are adopting search, discovery and analytics products to uncover trends, provide ad-hoc access to information, allow analysis of past events and better leverage data within the organization.
Here is how Mindtree helped a leading provider of enterprise search solutions port its key product to the Windows Azure platform for improved functionality and business growth.
The search provider needed to make its key enterprise product available to customers through a cloud-computing platform to meet their needs and preserve its competitive position. It determined that search-as-a-service on the Windows Azure platform was its best route to achieving this goal.
In doing this, the customer required a technology partner with broad and deep capabilities that could help it port its application and:
- Provide persistent storage for LWE indexes
- Maximize Azure Virtual Machine (VM) utilization
- Integrate with existing Heroku Provisioning application for customer sign-up
- Enable unique URL access for each customer LWE instance
- Provide out-of-the-box full text search for existing Azure customers
- Ensure cost eﬀectiveness
- Make the service available across multiple data centers
- Build-pay-as you-go functionality
Mindtree collaborated with the customer to design and develop a cloud-based version of its ﬂagship product. We were tasked with:
Design, development and testing
Mindtree developed the high-level architecture; designed the ‘to be’ application and ported it to Windows Azure.
We provided 24x7 development support for production issues; and leveraged the proprietary Mindtree MWatch platform to continuously monitor existing customer instances and the performance of Azure backend virtual machines.
The team tested the ported application for each payment plan by applying varying crawl and search performance loads; and helped the customer arrive at the optimal conﬁguration for each plan by running performance tests on diﬀerent Azure virtual machine sizes.
We captured performance counters, event viewer logs and crash dumps for each virtual machine. We put in place third party tools like AzureWatch, Azure Diagnostics Manager and Azure Performance Monitor Tool to monitor performance of the virtual machines. We also instituted functionality to capture information for billing and notifying customers.
Successfully delivering the project required Mindtree to meet several technical and project management challenges, including limitations in the Azure platform; diﬀering needs of each customer plan and a highly demanding timeline.
- Enabled new revenue streams through search as a service
- Ensured optimal application performance and resource utilization
- Ensured reliability and high availability
- Enabled automatic provisioning and de-provisioning for cost eﬀectiveness
- Enabled business ﬂexibility through functionality for multiple payment plans
- Ensured security through individualized access URLs
‘We launched LWC on Azure successfully yesterday. Thanks to the team for meeting this tight deadline’. Senior Vice President of Engineering