Laxmman Sainapuram

Project: Digital Enrollment Platform

• Designed, deployed, and managed production-grade Kubernetes (AKS) clusters, handling full-lifecycle orchestration, node provisioning, and cluster-wide resource optimization.
• Architected and executed a comprehensive Disaster Recovery (DR) strategy for Azure Kubernetes Service (AKS) and Databricks platforms, ensuring high availability and minimal RTO/RPO.
• Provisioned and optimized Azure cloud services, including Azure Cache for Redis, Azure Data Lake Storage (ADLS), and secure Service Principal Names (SPN) via Azure Application Registrations.
• Led complex cloud data migrations, successfully transferring large-scale datasets across ADLS folder structures with zero data loss and minimal downtime.
• Automated Databricks workspace deployments and enforced governance by creating custom cluster policies, optimized cluster pools, and secure Databricks scopes/secrets.
• Developed and optimized data pipelines utilizing PySpark and Python within Databricks Notebooks to process complex datasets efficiently.
• Managed data governance and schema evolution by architecting Databricks schemas, tables, and access control policies.
• Configured and scaled MongoDB clusters, including database provisioning, custom Search Index creation, and robust user access management (RBAC).
• Administered IBM DB2 database environments, managing table creation, schema optimization, and granular user access controls.
• Centralized infrastructure security by setting up and managing HashiCorp Vault for secure token, password, and certificates/secrets creation.
• Streamlined development workflows by implementing GitHub version control and designing automated CI/CD pipelines via GitHub Actions.
• Enhanced platform visibility by building proactive monitoring dashboards in Splunk and Dynatrace, reducing mean time to detection (MTTD) for critical infrastructure alerts.Project: Digital Enrollment Platform
• Designed, deployed, and managed production-grade Kubernetes (AKS) clusters, handling full-lifecycle orchestration, node provisioning, and cluster-wide resource optimization.
• Architected and executed a comprehensive Disaster Recovery (DR) strategy for Azure Kubernetes Service (AKS) and Databricks platforms, ensuring high availability and minimal RTO/RPO.
• Provisioned and optimized Azure cloud services, including Azure Cache for Redis, Azure Data Lake Storage (ADLS), and secure Service Principal Names (SPN) via Azure Application Registrations.
• Led complex cloud data migrations, successfully transferring large-scale datasets across ADLS folder structures with zero data loss and minimal downtime.
• Automated Databricks workspace deployments and enforced governance by creating custom cluster policies, optimized cluster pools, and secure Databricks scopes/secrets.
• Developed and optimized data pipelines utilizing PySpark and Python within Databricks Notebooks to process complex datasets efficiently.
• Managed data governance and schema evolution by architecting Databricks schemas, tables, and access control policies.
• Configured and scaled MongoDB clusters, including database provisioning, custom Search Index creation, and robust user access management (RBAC).
• Administered IBM DB2 database environments, managing table creation, schema optimization, and granular user access controls.
• Centralized infrastructure security by setting up and managing HashiCorp Vault for secure token, password, and certificates/secrets creation.
• Streamlined development workflows by implementing GitHub version control and designing automated CI/CD pipelines via GitHub Actions.
• Enhanced platform visibility by building proactive monitoring dashboards in Splunk and Dynatrace, reducing mean time to detection (MTTD) for critical infrastructure alerts.

• Project : Apigee Automation
• Create the new builds and deployment pipelines for new applications in Azure Devops using tools like maven build, Azure Devops, Git, SonarQube, Check Marx, Docker, Xunit, UFT, JMeter etc.
• With using maven build create and maintain Apigee end points, policies, and security checks
• Creating the python, power shell & shell scripts to automate Continue Integrations/Deployment pipelines
apigee product, developer details with using azure pipeline automation
• Deploy share bundle in apigee hybrid platform with using build and release pipeline
• Creating build and release yaml pipeline template based on team requirements.
• Create and maintain workload, services, and load balancer ingress yaml files
• Automated cloud service creations using terraform templates
• Strong working experience in Service Mesh technologies like Istio to manage Load balancer for applications deployed in K8s
• Deploy and scale infrastructure for multiple build environments (Dev, QA, Pre-Prod and Prod)
• Create Scheduled backup for apigee environments
• Trouble shoot connectivity issue for internal/external users
• Create new environments (Sandbox, stage, prod) in apigee platform
• Architecture/Designed Primary/secondary, Active-Active and Active/Passive environments for application with well known Disaster Recovery strategy

Project : IVR Platform and Cloud transformation

• Worked on Containerized solution to deploy applications consist of more than 400 Microservice APIs and 30 Frontend application in Kubernetes Clusters created in GCP (GKE) and MS Azure Cloud(AKS)
• Worked on building Data pipeline using cloud native services - Apache Airflow and spark technologies to bring massive amount data from on-perm data warehouse to cloud data platform (SaaS products) in Google Cloud Platform
• Managing Kubernetes objects to deploy and run applications seamlessly in public cloud platform
• Engaged in decision making on deployment strategies/Architecture(blue/green and canary) for microservice APIs and frontend applications through CI/CD pipelines
• Closely engaged with Enterprise data warehousing team to design and build CI/CD for data transformation and modernizing Master Data Management(MDM) in organization level
• Managing multi-region kubernetes clusters for frontend and backend application based on business domains within organization
• Implementing application monitoring using cloud native services in Google Cloud- looks like prometheus and grafana
• Controlling access permissions for application through managed service account and access roles
• Managing cloud deployment configuration
• Worked on network/application certificate automation using cloud tools - Jetstack cert-manager
• Implemented Greenlight API Standard for continuous integration and deployment (CI/CD) of code using Azure DevOps, calibrates unit and performance tests of applications, used code quality tools (SonarQube)to ensure code coverage and quality

• Managed Azure DevOps projects to streamline software delivery.
• Developed enterprise-class, highly available CI/CD pipeline from code in highly elastic, cloud-native environment.
• Contributed to the design phase of DaaS implementation in the Data Warehousing team, focusing on the transition from on-prem storage to a cloud data platform.
• Integrate selenium, UFT and Ready API automation testing with Azure Devops CI/CD pipeline
• Involved in design phase of DaaS implementation in Data Warehousing team for modernizing on-perm storage system to cloud data platform
• Linux/Windows system administrator for both Azure VM and GCP.
• Create and delete Database, collections, index, documents using pymongo script in MongoDB Cloud Clusters
• Streamlined certificate management process through automation using PowerShell scripting.