Who is the Client

A US-based Fortune 500 departmental store chain with over $20B annual sales and more than 1000 stores.

The Challenge

The client sensed an urgent need to streamline the process of data-flow management in an effective way while maintaining consistency across their multiple environments. The objective was to address the problem of managing a huge volume of data flowing in and out of the system, along with ensuring high uptime and availability of servers, clusters, and applications.

The client was quite satisfied with our previous engagement on Network Operations Center (NOC) DevOps support, which is why they now wanted us to deploy Big Data DevOps methodologies while upholding the health of their environments.

The Solution

GSPANN centralized the onsite-offshore 24/7 support operations to maintain cluster health and to resolve the data-flow issues. We helped the development, support, and QA teams to function smoothly in multiple geographic locations and different time zones.

We architected and deployed different microservices for a product recommendation system, data access services, event management services, personalized assets management, etc., to discard the client’s existing lengthy and potentially error-prone processes.

GSPANN automated the execution of multiple tasks through various deployment channels while minimizing manual efforts. We personalized big data assets and displayed dynamic content to the e-commerce users as per their location and preferences. We programmed the automated monitoring dashboard in Perl and Common Gateway Interface (CGI), and integrated backend services through Shell scripts. Additionally, we developed automation Shell scripts, such as disk usage script, file monitor script, and bucket usage script to detect the issues related to infrastructure and applications.

GSPANN optimized the client's IT capabilities, data analytics, and DevOps operations through deployments, such as:

  • Developed a dashboard to monitor and manage cluster resources for all application environments based on resource consumption and proposed changes to reduce the overall cost for the client.
  • Multiple microservices helped in load balancing and decomposing a huge amount of e-commerce data.
  • Developed an innovative application to build and design a configurable UI composed of static and dynamic components.
  • Monitored the status of Hadoop cluster services running on Google Cloud Platform (GCP) and automatically executed inactive services for smooth operations.

Business Impact

  • The solution helped the client in controlling the cost by terminating the unused resources and at the same time downsizing the instances with low utilization of CPU and memory.
  • Post solution implementation, the client experienced reduced application downtime and unwanted outages because of continuous monitoring and alert notifications.

Technologies Used

Google Cloud Platform (GCP). Cloud infrastructure
MongoDB and MySQL. Application database
Ansible. Open-source software to automate software provisioning, configuration management, and application deployment
Azkaban. Batch workflow job scheduler to run Hadoop jobs
Nexus and Tonomi. Artifacts management and deployments tool
Puppet. Open-source software configuration management tool
Maven and Jenkins. CI/CD build and deployment
Gerrit. Distributed version control, source code management, and central repository

Related Capabilities

Achieve Faster Time-to-Market for New App Features with Quick Code Releases using Automation

We offer several ready-to-use DevOps solutions that enable businesses to apply DevOps’ best practices rapidly. Our DevOps engineers hold expertise in automating complex delivery requirements for large enterprise applications. We can help you deliver frequent quality code releases as per your business requirements.

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