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EMAIL AVAILABLE | PHONE NUMBER AVAILABLEProfessional Summary: IT Professional with 9+ years of experience in Azure/AWS Cloud, DevOps Engineering, Build/Release Management, Software Configuration Management, Version Control, Change Management, Cloud Infrastructure Management, and Operations and Integration of code from one environment to other environment and deploying to servers. Experience on complete software development life cycle (SDLC) with software development models like Agile, Scrum Model, JIRA, Waterfall models. Experienced in migrating on-premises instances or Azure Classic Instances to AWS using AWS Cloud Endure for seamless and efficient migration. Adept in the migration of workloads to AWS using methodologies like Lift & Shift, ensuring optimal resource utilization and performance. Demonstrated expertise in building and maintaining systems in AWS for both development and production environments. Proficiently managed Amazon EC2 instances, RDS databases, and other AWS services. This expertise extends to architecting standard virtual machines as well as leveraging various AWS services for optimal system design and performance. Hands-on experience in AWS provisioning and good knowledge of AWS services like VPC, EC2, S3, EKS, Lambda Functions (Code and container image), Glacier, ELB, RDS, Redshift, IAM, Route 53, VPC, Auto scaling, Cloud Front, Cloud Watch, Cloud Trail, Cloud Formation, and Security Groups. Hands on experience in AWS provisioning and good knowledge of AWS services like EC2, S3, Glacier, ELB, RDS, Redshift, IAM, Route 53, VPC, Auto scaling, Cloud Front, Cloud Watch, Cloud Trail, Cloud Formation, Security Groups. Worked with AWS CLI and AWS SDK to manage resources on AWS and created python script using API Calls to manage all resources deployed on AWS. Performed AWS Database Administrative tasks on Amazon RDS for PostgreSQL databases such as configuring the parameter group, managing IP traffic using security groups, auditing the database log files, planning backup and recovery strategies, and monitoring certain activities on the database. Hands on experience in Terraform for building, changing, and versioning of Infrastructure and wrote Templates for AWS infrastructure as a code using Terraform to build staging and production environments. Expertise in the build of staging and production environments using Terraform and writing templates for AWS and Azure IaaS (infrastructure as a service). Experienced in deploying and scaling containerized applications on AKS to meet varying workload demands, monitoring AKS cluster health and performance using Azure Monitor and other monitoring tools. Good experience with DevOps architecture, Serverless Computing and Microsoft Azure. Experience in Azure Platform Development, Deployment concepts, hosted Cloud Services, platform services and close interface with Windows Azure Multi-Factor Authentications. Experience working on Data Ingestion to one or more Azure Services - (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks. Experience in designing, configuring, and deploying Microsoft Azure for a multitude of applications utilizing the Azure Stack (Including Compute, Web & Mobile, Blobs, Resource Groups, Azure SQL, Cloud Services, and ARM), focusing on high - availability, fault tolerance, and auto-scaling. Extensive experience includes Docker, Kubernetes, GIT, AWS, Azure, DevOps, Terraform, Build/Release Management and Cloud Management and Containerization and Databases. Hands on experience in containerization and orchestration using Docker, Kubernetes, and Azure Kubernetes Service (AKS). Strong experience on Continuous Integration with Azure DevOps service and Jenkins. Extensive experience in Azure Backup, Azure policies, Azure Key Vault, Salt Stack and Tagging. Experience in migrating on-premises applications to Azure and configured VNETs and Subnets as per the project requirement also performed PowerShell scripting to do Patching, Imaging, and Deployments in Azure. Good experience in writing Azure Resource Manager (ARM) templates to deploy, update and delete multiple resources in Azure and migrating the on-premises resources to Azure with Azure Site Recovery (ASR) and /Azure Backups. Expertise in monitoring Azure Resources using Azure Monitor and Web Apps for Application Insights. Proficient in creating reusable Terraform modules in both Azure and AWS cloud environments. Experience in writing Infrastructure as a Code (IaC) in Terraform to deploy the Azure resources and services Expertise in Querying RDBMS such as Oracle, PL/SQL, and MySQL by using SQL for Data integrity. Experience in upgrading and migrating various versions of Mongo database on different platforms and installing multi-Data Center and multi-rack Cassandra cluster. Skilled in installing and configuring and troubleshooting on Windows NT/Windows 2000/2003/2008 and 2012 servers using enterprise standards. Good experience in implementing CI/CD pipeline using Azure DevOps (VSTS, TFS) in both cloud and on-premises with GIT, MS Build, Docker, Maven along with Jenkins plugins. Experience in using JIRA to keep track of all the ongoing tasks and maintain bug resolutions.Education:Bachelors from JNTU University, India.Technical Skills:
Cloud EnvironmentAzure Cloud, AWS, GCPCI/CD ToolsJenkins, Azure Devops, VSTSContainer ToolsDocker, Kubernetes, AZURE KUBERNETES SERVICE (AKS), GKEMonitoring ToolsAzure Monitoring Service, CloudWatch, ELK (Elasticsearch, Logstash, Kibana)Automation ToolsAnsible, Terraform, CloudFormation, ARM templatesBuild ToolsMaven, Ant, NexusScriptingPerl, Shell, Python, C, SQL, JavaScript, PHP, HTML, JavaWeb & Application ServersApache, Nginx, JBOSS, Apache Tomcat and WebLogicTicketing ToolsJIRA, Azure BoardsDatabasesOracle, PL/SQL, MySQL, MongoDB, CassandraOperating SystemsWindows, Linux/Unix and Mac OSProfessional Experience:Client: Bed Bath & Beyond, TX, Remote Duration: July 2022 to Present
Role: Senior Cloud DevOps EngineerResponsibilities: Designed and implemented data and storage management solutions in AWS, leveraging services like RDS, S3, SQS, Lambda, EC2 instances, CloudFormation, and scripting with PowerShell and AWS CLI. Successfully migrated on-premises and Azure Classic Instances to AWS using AWS CloudEndure, employing methodologies such as Lift & Shift for optimal resource utilization. Built and maintained systems in AWS for development and production environments, managing EC2 instances, RDS databases, and other AWS services. Demonstrated proficiency in AWS provisioning, utilizing services such as EC2, S3, Glacier, ELB, RDS, Redshift, IAM, Route 53, VPC, Auto Scaling, CloudFront, CloudWatch, CloudTrail, and CloudFormation. Utilized AWS CLI and AWS SDK to manage resources on AWS, creating Python scripts with API calls for efficient resource deployment. Strong knowledge of Azure services, including but not limited to Azure Virtual Machines, Azure App Service, Azure Kubernetes Service (AKS), Azure Functions, Azure SQL Database, Azure Storage, and Azure Network Security Groups (NSGs). Performed AWS Database Administrative tasks on Amazon RDS for PostgreSQL databases, including configuring parameter groups, managing security groups, auditing log files, planning backup and recovery strategies, and monitoring database activities. Hands-on experience with Terraform for building, changing, and versioning infrastructure, writing templates for AWS infrastructure as code. Expertise in building staging and production environments using Terraform for both AWS and Azure IaaS. Worked with Terraform major features such as Infrastructure as Code, Execution plans, Resource Graphs, and Change Automation. Deployed Elastic Beanstalk applications and environments using Terraform and Terragrunt, integrating with Ansible roles. Used Ansible Tower for scheduling playbooks, managing playbooks in GIT repositories, and ensuring secure endpoint connections for CI/CD.: Installed and configured Jenkins, creating builds and release pipelines, and deploying applications using secure endpoint connections for CI/CD. Automated end-to-end Continuous Integration/Deployment/Delivery pipeline using Jenkins, Maven, and scripting. Automated infrastructure activities, continuous deployment, application server setup, and stack monitoring using Ansible playbooks. Create develop and test environments for multiple applications by provisioning Kubernetes clusters on AWS (EKS) using Docker, Ansible, and Terraform Deploy the containers to Kubernetes (EKS) by Calling ArogoCD APIs from BitBucket Pipelines and set up the ArgoCD server to implement the CI&CD Microservice deployment management with helm Expertise in Docker images using Dockerfile, managing container snapshots, and orchestrating Docker images and containers using Kubernetes. Experience and expertise in GCP environment in particular Google Pub/sub, Google cloud
Implemented security measures to comply with industry-specific standards such as PCI-DSS, HIPAA, and GDPR. Automated deployment with Chef to provision AWS EC2 instances for continuous deployments. Used Splunk, Nagios, and ELK for log monitoring, CloudWatch for creating monitors, alarms, and notifications. Integrated Dynatrace monitoring with Netcool for alerts and paging application teams, setting up collectors in various data centers. Deployed a managed Kubernetes cluster in Azure using Azure Kubernetes Service (AKS) and configured an AKS cluster through various methods including the Azure portal, Azure CLI, and template-driven deployment options such as Resource Manager templates and terraform. Experience in Designing, Architecting, and implementing scalable cloud-based web applications using AWS and GCP and migration of On-prem to cloud projects for AWS and GCP. Utilized ArgoCD for continuous deployment, maintaining release versions using GitLab tags, and integrating with Kubernetes for resource management. Set up Datadog monitoring across different servers and AWS services, creating Datadog dashboards for various applications. Continuous Integration with Jenkins and Python Scripts: Responsible for implementing Continuous Integration (CI) and Continuous Delivery (CD) processes using Jenkins, Python, and Shell scripts. Developed automation scripts in Python for deploying and managing Java applications, using Puppet for Java application deployment across Linux servers. Proficient in managing various file systems using Logical Volume Manager (LVM), and installed/configured Apache Tomcat Web Server.Environment: AWS, Terraform, AWS CloudFormation, GCP, AKS, AWS IAM, Prometheus, Splunk, Maven, Ansible, Docker, Kubernetes, Python, Ruby, XML, Shell Scripting, EKS, PowerShell, Nexus, JFrog Artifactory, Jira, GitHub, Tomcat, Nexus, PCF, Office 365.Client: Quantum Health, Dublin, OH, Remote Duration: September 2020 to June 2022Role: Senior Cloud DevOps EngineerResponsibilities: Modernize CI/CD pipelines with Azure cloud services. Focus on Continuous Integration, Continuous Delivery, and Continuous Deployment (CI/CD) for ensuring high availability and fault tolerance. Implement CI/CD/CT solutions to streamline builds, deployments, and automated testing operations. Configure Azure IaaS services, including Cloud Services, Resource Groups, Express Route, VPN, Load Balancing, Application Gateways, Virtual Networks, and Virtual Machines. Provision Azure Kubernetes Cluster (AKS) and Azure Container Registry for managing microservices. Design and maintain infrastructure for applications using Terraform. Create ARM templates and Terraform scripts for automated and standardized pipeline strategies. Set up CI/CD pipelines using Azure DevOps (VSTS, TFS) both in the cloud and on-premises with tools like MS Build, Docker, and Maven. Proficient in designing hybrid cloud solutions, integrating on-premises infrastructure with AWS and GCP services using VPNs, Direct Connect, and Cloud Interconnect. Configure pipelines to deploy applications to multiple destination servers and VMs using deployment groups. Develop and design Azure DevOps pipelines for managing Azure resources across multiple subscriptions. Configure Azure environments for provisioning services executed by providers and Linux servers as per requirements. Implement testing with Azure DevOps using test cases, test plans, and test suites. Integrate tools like SonarQube, Maven, Nexus, and Veracode into the CI/CD pipeline for unit testing and code quality. Utilize Azure Kubernetes Service (AKS) for containerization to build and deploy various microservices. Orchestrate Docker containers using Kubernetes and Helm templates for efficient management. Configure Azure Active Directory, user management, and Azure Multi-Factor Authentication (MFA) to ensure secure user authentication. Implement Azure Key Vault for securely storing and accessing secrets. Set up monitoring tools, scripts, and data feeds for operationally critical environments. Utilize Azure Log Analytics and Dynatrace to monitor applications' health, CPU-memory stats, and server performance. Build an API management platform and API gateway using Azure to enhance integration capabilities. Develop custom functionality using services like Excel Services and the SharePoint REST API.
Environments: Azure Cloud, IaaS, PaaS, SaaS, Azure Resource Manager (ARM), Azure Microservices, GCP, Functions, Logic, Docker, Kubernetes, SonarQube, Veracode, Ansible, Terraform, AIPM, Power Shell, Bash, Maven, Nexus Repository Manager, Git, JIRA, Azure Boards, Azure Repos, Azure pipelines, Azure Artifacts, Key Vault.Client: Oportun, SFO, CA Duration: July 2018 to August 2020Role: Cloud DevOps EngineerResponsibilities: Provisioned and administered EC2 instances and configuring EBS, Simple Storage(S3) cross region replication, Elastic Load Balancer, configure Auto scaling, setting up CloudWatch alarms, Virtual Private Cloud (VPC), mapping with multi-AZ VPC instances and RDS, based on architecture. Worked on Amazon EC2 setting up instances, virtual private cloud (VPCs), and security groups and created AWS Route53 to route traffic between different regions and used BOTO3 and Fabric for launching and deploying instances in AWS. Configured Amazon S3, Elastic Load Balancing, IAM and Security Groups in Public and Private Subnets in VPC, created storage cached and storage volume gateways to store data and other services in the AWS. Architected and configured a virtual data center in the AWS cloud to support Enterprise Data Warehouse hosting including Virtual Private Cloud (VPC), Public and Private Subnets, Security Groups and Route Tables. Used Security Groups, Network ACLs, Internet Gateways, NAT instances and Route tables to ensure a secure zone for organizations in AWS public cloud. Worked on migration services like AWS Server Migration Service (SMS) to migrate on-premises workloads to AWS in easier and faster way using Rehost "lift and shift" methodology and AWS Database Migration Service (DMS), AWS Snowball to transfer large amounts of data and Amazon S3 Transfer Acceleration. Written Terraform scripts to automate AWS services which include ELB, CloudFront distribution, RDS, EC2, database security groups, Route 53, VPC, Subnets, Security Groups, and S3 Bucket and converted existing AWS infrastructure to AWS Lambda deployed via Terraform and AWS Cloud Formation. Created and maintain highly scalable and fault tolerant multi-tier AWS environment spanning across multiple availability zones using Terraform and CloudFormation. Implemented AWS Elastic Container Service (ECS) scheduler to automate application deployment in the cloud using Docker Automation techniques. Written terraform scripts from scratch for building Dev, Staging, Prod and DR environments. Setting up the build and deployment automation for java base project by using Jenkins and Maven. Implemented Docker maven plugin in Maven pom.xml files to build Docker images for all microservices and later used Docker File to build the Docker images from the Java jar files also Created Docker images using a Docker File, worked on Docker container snapshots, removing images, and managing Docker volumes. Worked on creating the Docker containers and Docker consoles for managing the application life cycle and Jenkins is Built on Docker container and the Master controller Kubernetes controls pods. Implemented CI/CD allowing for deploy to multiple client Kubernetes/AWS environments and leveraging kops implemented a Kubernetes Container Orchestration solution within AWS allowing for easy management, creation and recovery of AWS assets. Created Docker images, upload/download in and out from the Docker Hub and Worked on setting up new tools such as Kubernetes with Docker to assist with auto-scaling, continuous integration, rolling updates with no downtime. Created HELM charts for deployments and managing resources such as deployment, replication controller, replica set, Daemon sets and stateful set using pod templates. Monitored Kubernetes Cluster components Kubernetes Node includes Kubernetes components such as hosts, Orchestration level metrics, internal kube system components and kube state metrics using Prometheus and Grafana. Maintained Artifacts in binary repositories using JFrog Artifactory and pushed new Artifacts by configuring the Jenkins project Jenkins Artifactory plugin. Planned and implemented in maintaining applications in production with zero downtime using Blue-Green deployment and monitoring the applications using Datadog and pager duty. Worked on using database like MongoDB and SQL in production environment for performance tuning of databases and run simple queries. Worked on POC to compare identity access management system (IAM) with GCP s configure GCP with roles and service accounts. Python scripts have been implemented to automate the deployment and management of serverless functions on cloud computing infrastructure like AWS Lambda maximizing resource efficiency and lowering costs. Python scripts can be used in conjunction with configuration management programs like Ansible to automatically provision and configure infrastructure parts while guaranteeing consistency and scalability. Written wrapper scripts to automate the deployment of cookbooks on nodes and running the chef-client on them in a Chef-Solo environment. AWS Cloud management using Chef Automation and Automated the cloud deployments using Chef, Python and AWS Cloud Formation Templates.Environment: AWS, Terraform, Chef, Docker, Jenkins, Git, Jira, GCP, Kubernetes, Maven, Datadog, ELK, Java, SonarQube, Shell, Bash, Python, DynamoDB, Splunk, Prometheus and Grafana.Client: TD Bank, Cherry Hill, NJ Duration: January 2017 to June 2018Role: DevOps Engineer
Responsibilities: Setup CI/CD pipeline using Azure DevOps in both cloud and on-premises with MS Build, Docker, Maven. Helped teams to configure webhooks in Bitbucket to trigger automated builds in Jenkins. Configured Docker containers using Kubernetes. Performed automation and scaling of applications using Kubernetes. Deployed Azure IaaS Virtual Machines (VMs) and Cloud services (PaaS role instances) into secure VNets and Subnets. Created and managed Azure AD tenants, and configure application integration with Azure AD. Configured monitoring for Azure virtual machines using Azure Monitor, Log Analytics and App Insights. Setup and installed servers through Azure Resource Manager Templates (ARM) Automated environment for the DevOps services using Python and Shell scripts Worked on Azure Storage, SQL Database, Key Vault, Traffic Manager. Configured Azure Load Balancer (Internal and External) and Azure Traffic Manager Developed Terraform modules to provision cloud infrastructure in different environments Maintained and administered GIT source code tool. Configured Jenkins to build and deploy by setting up SonarQube, Maven, Nexus to build CI/CD pipeline Automated the build and release management process including monitoring changes between releases. Used JIRA for ticketing and as well as defect tracking system and configure various workflows, customizations, and plug-ins for Jira bug/issue tracker.Environment: Azure Cloud, Azure DevOps, Azure Resource Manager (ARM), Azure AD, Docker, Kubernetes, Ansible, Puppet, Terraform, Python, Power Shell, Bash, Visual Studio Code, Maven, Jenkins, Git, JIRA, Windows Azure, AIPM, Key vault, Docker, KubernetesClient: Thomson Reuters, Hyderabad, India Duration: January 2015 to November 2016Role: DevOps EngineerResponsibilities: Cloud Infrastructure provisioning and management, Configuration management, Deployments, Monitoring Working with AWS EC2 services like Instances management, simple storage service, IAM, Load Balancers (Classic and Application), Volume management, Code Deploy for Deployment, S3, Glacier, ElastiCache Service, and cloud formation Developed and implemented the custom cloud formation templates as per client requirements for on-demand and repetitive tasks. Setting up SPLUNK monitoring on Linux and windows systems. Automate the windows Instances provisioning with the help of customized AMIs and configure IIS servers for deployments ready. Hosting IIS websites and as Virtual Directory. Creating a fully automated build and deployment Platform and coordinating code builds promotions and orchestrated deployments using Jenkins, Harness and GitHub AWS RDS, Working with MSSQL databases for INT, QA, and UAT Environments. Create and Manage the AWS Classic and Application Load balancers and target groups, and define the Load balancer rules for traffic routing to the instances. Implemented the Auto Scaling alongside launch configurations to scale the instances (Horizontal and Vertical scaling). Monitored and tracked SPLUNK performance problems, administrations and open tickets with SPLUNK. Manage the code deployments to the IIS servers with AWS Code Deploy Service.
Connecting to the client Infrastructure with VMWare with RSA code, and accessing the Client resources and AWS instances and configuration management in the client network.
Configuration changes in deployment jobs whenever new requirements are received.
Create and Configure the Jenkins jobs for Continuous integration to manage builds to generate the artifacts and security checks with SonarQube Analysis.
Configured SonarQube and Enabled the Quality Gate to measure the code quality and custom Quality profiles.
Automated the deployment procedure and T-SQL analysis using the SQL Enlight tool for the potential code quality violations for SQL files. Predefined DEV, QA, STAGING, AND PRODUCTION environments and easy swap from stage to production when everything working and UAT is signed off. Automated the process of deployment from a lower environment to a higher one with the provisioned deployment pipelines and quality parameters.
Ability to deploy the environment-specific configurations using config files pre-defined templates or scripting.
Providing Production on-call support for off-peak hours in order to maintain the application availability. Configuration management in deployment jobs Implemented the SQL violations from the SQL scripts from sql teams and then analyse publish to SonarQube with SqlEnlight. Implemented the functional code coverage report generation with MSTest and NCover and publish it with the Jenkins job and on the SonarQube dashboard.Environment: Windows, Linux, .Net, SQLEnlight, SonarQube, Jenkins, MSTest, NCover, Chef, AWS EC2, S3, Glacier, ELB, ALB, VPC, Security Groups, Cloud Watch, Launch Configuration, AWS Code Deploy, AWS Code Commit, RDS, ElastiCache, OpenSearch Service, etc. |
