Case Study

Centralized data lake on AWS enabled 60% reduction in infrastructure cost

A leader in performance-based business-to-business growth solutions optimized their infrastructure cost by 60% and improved application performance by re-architecting their solution on AWS.


Challenge

The organization, which provides data-driven insights to personalize customer experience, wanted to move away from their enterprise CRM application and consolidate all their solutions on Salesforce. However, storing petabytes of customer data on Salesforce involved high licensing costs and performance issues.

The enterprise was looking for high performance and scalable cloud solutions to integrate their enterprise data with Salesforce Cloud and provide a single source of truth. They wanted to go beyond stock machine learning capabilities of enterprise CRM applications to help the customers find, convert, nurture, and retain more revenue.

 

Discovery

The growth solutions provider was facing performance issues and were unable to ingest high-velocity customer data using Salesforce and enterprise CRM applications.  Moreover, delay in data sync was creating multiple versions of the truth, providing an inconsistent picture of customer interactions and often resulting in missed opportunities.

The client was looking for a cost-effective cloud-based solution that can offer scalability, multi-tenancy, performance, and flexibility. The solution would also be able to utilize the existing enterprise data and use advanced analytics to work on a single source of truth for customer data.

 

Impact

Impetus Technologies Inc. created a microservice architecture with a tiered storage/polyglot layer solution to address scalability and performance issues. A centralized data lake in AWS utilized the existing enterprise customer data and used serverless architecture to ingest data from multiple sources automatically.

Impetus used integration-platform-as-a-service (iPaaS) to move transactional data at scale both into and out of the Salesforce applications. The hybrid cloud-based solution provisioned enterprise data lake to:

  • Host customer data from multiple sources
  • Store a copy of active transactional data on Salesforce
  • Maintain a single source of truth with real-time integrations with Salesforce/external services

The solution was more cost-effective than Salesforce, both in terms of data storage and analysis to provide real-time insights to the customers.

Highlights

  • Used micro-services and polyglot architecture (MongoDB/Solr/Elastic cache) to improve speed, scalability, and performance
  • Created serverless architecture and process automation on AWS (Lambda, DynamoDB, S3, API gateway, SNS, Data pipeline, etc.)
  • Prometheus Grafana for application monitoring
  • Sensu for incident management
  • Amazon Elastic Kubernetes Service (EKS) and docker for container orchestration
  • Jenkins/Rundeck for build deployment

 

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