A technology firm providing an enterprise data management and analytics platform that runs on a private cloud, AWS, Azure, or GCP, allowing users to store and analyze data spanning hybrid and multi-cloud environments.
The Challenge
To remain competitive in the data management and analytics software market, our client needed a partner who could increase the pace of engineering and development, rapidly adding more product features and improving topline revenues. In particular, they wanted to scale up engineering for their Data Platform, in the areas of Data Performance Engineering (DPE), SRE/DevOps, Common Vulnerabilities & Exposures (CVE) and Product Engineering. These technologies were vital for distribution of bigdata (Hadoop) and Apache Spark libraries of the platform.
The Solution
Persistent addressed these needs with its scalable engineering and professional services “levers” — We proposed creating an extended offshore team to scale up engineering operations, and over four months we brought together 41 engineers with ready skills on the client’s stack. To speed up the pace, Persistent provided an approach to fix vulnerabilities at the library level (rather than going “Jira-by-Jira”). The cross functional team then quickly cleared the large backlog of security and vulnerability issues, across the platform.
Next, we developed and implemented an automated, end-to-end performance framework for the data platform, replacing a manual system with one that delivered results “at the click of a button.” This included benchmarking against a standard data set and cluster config, to provide comparative metrics versus competitor products across features such as query execution time, hive replication, and backup/restore, etc.
Persistent also provided 24/5 support to resolve any issues in the production environments. Our team assisted the client in SRE/DevOps activities such as automated build deployment, ad hoc SQL scripts, handling tools and technologies such as DataDog, PagerDuty, Jenkins/Spinnaker for CI/CD pipelines, Elastic Kubernetes Service (EKS), and Terraform for the infrastructure automation.
Finally, we created targeted teams for various Apache tracks (Livy, Zeppelin, Ozone, SDX) to clear up product backlog, customer escalations and add new features, and contributed to the “SaaSification” of SDXi services (i.e., moving from PaaS to SaaS).
The Outcome
Persistent Professional Services assumed complete ownership of “KTLO” work for SRE/DevOps tracks, providing 24×7 support from offshore, which otherwise would have required teams in multiple time zones. Our scale-up and support activities enabled the transfer of work from client teams to Persistent, giving their CORE team the flexibility to focus on critical and key growth areas. As a result, our client was able to re-allocate 30-40% of CORE team bandwidth to other product improvements.
Our Performance Benchmarking Automation solution delivered quicker turnarounds (saving both time and money), and our faster remediation of vulnerabilities/ security concerns contributed to the timely availability of a critical FEDRAMP certification release, for a key end customer. And now, a deep pool of skilled resources is ready 24×7 to meet the complex demands of Big Data and Data Engineering.
