Infrastructure, BizOps & Database Operations Digital Transformation for an Enterprise Client (with Partner)
Business Problem
The client has been running their Infra, Biz Ops and Database Ops separately with a separate team structure. It was a complex environment with 300+ applications across these various towers with 20+ applications that were mission critical and 150+ applications that were business critical. Whenever there was an outage, despite having a Crisis Management Desk, a resolution and coordination was very difficult. The client was looking to transform this operational environment and to drive efficiency across various towers.
Technology Landscape
The scope included release planning & production deployment, alerts and monitoring, server application and security vulnerability, CMD, 24×7 on-call support and health check, DevOps and SRE, trouble ticketing support for applications, and release planning for databases. The client environment was Linux, Solaris with Websphere, Weblogic, Tomcat middleware in HTML, Java, PLSQL, CSS, Dockerfile etc. with third party products including Cisco, Netcracker, Informatica, Juniper and HP. Monitoring was on New Relic, Kibana on EC2 and Cloudwatch.
Our solution and team accomplishments
Our team created a solution that brought productivity improvements to BizOps services through Smart Operations, Automation, Site Reliability Engineering through DevOps and an integrated team. The solution included Automation and AI Pod (intelligent and cognitive automation in (1) patching (2) Instance Provisioning (3) Servers); SRE Operations – multi skilled SRE Ops for Infra & automation, Critical Incident response, Business Event response, automated CI/CD pipeline with embedded quality and security engineering; providing Cross Functional Services with tighter interlocks. SRE approach followed a methodology in 3 phases – incubate, benchmark and blueprint, target interventions and scale, mature and transform.
Business Outcome
Following the Agile DevSecOps model and integrating various teams into one cohesive management and delivery unit, provided year one efficiency increase of 15%, and we anticipate that we should be able to double that over the next three years as we deploy automation and RPA tools for process automation. We anticipate that deduplication of functions will further reduce headcount driving overall efficiency. As the project matures further additional AI tools are slated to be deployed further increasing efficiency.
