SUMMARY

• 7+ years of IT professional expertise in DevOps and Cloud Engineering, Build/Release Management, Linux administration, and Cloud Management at all stages of the SDLC, working in a variety of domains such as finance, communications, and understanding the business requirements of the applications.
• Hands - on experience in Azure cloud worked on Azure web application, App services, Azure SQL Database, Azure Blob storage, Azure Functions, Virtual machines, Fabric controller, Azure AD, Azure Data Factory, Azure Service Bus, and Notification hub.
• Experience with Azure Kubernetes Service to establish a production-grade Kubernetes cluster, allowing enterprises to reliably deploy and run containerized workloads in the cloud.
• Deployed and optimized two-tier Java and Python web applications to Azure DevOps CI/CD to concentrate on development using services like Repos to commit codes, Test Plans to unit test, deploy App Service, Azure Application Insight collects process health and usage data and stored artifacts in blob storages.
• Viewed the project description, added members, and checked the most recent activity using VSTS (Azure DevOps).
• Designed AWS Cloud Formation templates to create customized Virtual Private Clouds, subnets, and NAT to ensure successful deployment of web applications.
• Experienced in building up databases on AWS using RDS, configuring instance backups to S3 buckets, and storing data using S3 buckets.
• Proficient in managing third-party resources with Cloud Formation utilizing the AWS Cloud Formation Registry and CLI. Able to install AWS resources using the Infrastructure as Code (IaC) model.
• Worked with services offered by the Google Cloud Platform (GCP), including compute engine, cloud load balancing, cloud storage, cloud SQL, stack driver monitoring, and cloud deployment manager.
• Implemented Terraform modules to deploy applications across various cloud providers.
• Developed Terraform templates for GCP infrastructure as a code to generate staging and production environments, as well as automated infrastructure provisioning leveraging Terraform and Packer to automate the image-building process.
• Extensively used Terraform in AWS Cloud to automatically set up and modify settings by interfacing with control layers to create and compose all the components necessary to run applications.
• Experience in integrating Jenkins with various tools like Maven, Git, SonarQube, and Nexus and implementing CI/CD automation for creating Jenkins pipelines programmatically architecting Jenkins Clusters and troubleshooting the build issues during the build process.
• Worked in all areas of Jenkins setting up CI for new branches, build automation, plugin management, securing Jenkins, and setting up master/slave configurations.
• Developed Microservices onboarding tools leveraging Python and Jenkins allowing for easy creation, and maintenance of build jobs and deploy services in Kubernetes.
• Experienced in branching, tagging, and maintaining the version across the environments using SCM tools like Git, GitHub, GitLab, Bitbucket, Subversion (SVN), and TFS on Linux and Windows platforms.
• Experienced in authoring pom.xml, and build.xml files performing releases with the Maven, ANT, and Gradle release plugin, and managing artifacts in Sona type NEXUS, JFrog Artifactory.
• Experience in using build automation tools like MAVEN, Gradle, and ANT for the building of deployable artifacts such as WAR & EAR from source code.
• Expertise with Docker images using a Docker file, worked on container snapshots, removing Images, and managing Docker Volumes, Orchestration of Docker images and Containers using Kubernetes by creating master and node.
• Experience with container-based Virtualized deployments using Docker, working with Docker images and Docker registries, and Container Management tools Kubernetes and Swarm.
• Integrated Jenkins with Docker container using Cloud bees Docker pipeline plugin and provisioned the EC2 instance using Amazon EC2 plugin.
• Experience in Building and deploying the application code using CLI of Kubernetes called kubectl, kubelet, kubeadm, kubespray, and scheduling the jobs using Kube-scheduler.
• Managed K8s charts using Helm and created responsible builds of the Kubernetes applications.
• Designed and implemented Azure Kubernetes pod definitions, tags, labels, and multi-pod container replication. Managed the scaling and auto-scaling of multiple Kubernetes pod containers.
• Experience with Confidential Corp Vault for secret management storage and use of Ansible Vault for secrets storage and inject while running playbooks.
• Experienced in building, designing, and maintaining platform automation using Chef and involved in setting up Chef Workstation, Nodes, Cookbooks, and Recipes using Ruby Scripting and familiar with Knife in chef.
• Designed end-to-end automation of infrastructure and continuous delivery of the applications by integrating cloud formation scripts, Jenkins, AWS, CHEF cookbooks, and recipes.
• Experienced in creating automated PowerShell Scripts for web app deployment.
• Shell scripting was used to create automated procedures that run every day on LINUX installations to check disk utilization and clean up file systems.
• Jenkins was used to construct a continuous integration and delivery (CI/CD) process that built and deployed Java/J2EE to Tomcat application servers.
• Worked on Nagios Event handlers to automatically resume failed services and applications while monitoring servers and apps using shell and Python scripts, Splunk, and Nagios to fix infrastructure issues.

TECHNICAL SKILLS

Cloud Environments: Microsoft Azure, Amazon Web Services

Configuration Management: Ansible, Ansible Tower, Chef, Puppet

Build Tools: ANT, Maven, Gradle

CI/CD Tools: Jenkins, Hudson

Monitoring Tools: Splunk, CloudWatch, Nagios, Prometheus, Grafana

Container Tools: Docker, Kubernetes

Scripting/Programming Languages: Python, Java, Shell (PowerShell/Bash), Ruby, YAML, JSON, Perl

Version Control Tools: GIT, Subversion, Bit Bucket, Git Lab

Operating Systems: Windows, UNIX

Databases: MYSQL, DynamoDB

Testing/Ticketing Tools: Jira, SonarQube

Web/Application Servers: Apache Tomcat, WebLogic, Oracle Application Server

PROFESSIONAL EXPERIENCE

Confidential, Nashville, TN

Sr. DevOps Engineer

Responsibilities:

• Experience in moving Azure Classic and On-premises Instances to an Azure ARM Subscription with Azure Site Recovery.
• Creating and managing users and groups in Azure AD. Designed, deployed, maintained, and led the implementation of Microsoft Azure and underlying technologies cloud solutions.
• Worked closely with several application teams to fully understand the requirements for automating and migrating on-premises applications to the Azure Cloud.
• Worked on implementing tagging across Azure with PowerShell for cost and billing management of deployed resources.
• Leverage Azure DevOps to manage test plans, suites, and cases. Installed the testing and feedback extension in the Azure DevOps Marketplace for authors to run and analyze manual tests.
• Worked with Azure Data Bricks Cloud to organize data in notebooks and easily visualize data using dashboards.
• Deploy an Azure Data Bricks workspace in an existing virtual network with public and private subnets and properly configured network security groups.
• Set up blue-green deployments via Azure DevOps to avoid application downtime.
• Implemented high availability in Azure Classic and Azure Resource Manager deployment models.
• We used Azure Container Service (AKS) to manage our Kubernetes environment and orchestrate our Docker containers.
• Extensive experience designing Azure Resource Manager templates and designing custom build steps using PowerShell.
• Wrote Azure infrastructure templates as code using Terraform to create staging and production environments.
• Provisioned Azure IaaS virtual machines and cloud services in secure virtual networks and subnets.
• Involved in deploying infrastructure using Terraform and creating a deployment, test, and production environments for developing projects using Azure.
• Created a Terraform template to deploy virtual networks, subnets, virtual machine scale sets, load balancers, and NAT rules, and used terraform diagrams to visualize execution plans using the diagram command. Azure infrastructure templates are written as code using Terraform to create staging and production environments.
• Terraform templates are automated to create an infrastructure through Azure DevOps pipelines.
• Establishing the Azure devops pipeline for the dot net core application that needs to be installed on the Azure app service plan.
• Deployed and optimized two-tier Java and Python web applications to Azure DevOps CI/CD to concentrate on development using services like Repos to commit codes, Test Plans to unit test, deploy App Service, Azure Application Insight collects health performance and usage data of the process, stored artifacts in blob storages.
• Created Git branch strategies by creating develop and release branches to maintain a high quality, up-to-date main branch.
• Worked on the infrastructure using Docker containerization. Worked with development support team to set up a continuous delivery environment using Docker.
• Deployed a Windows Kubernetes (K8s) cluster using Azure Container Service (ACS) from the Azure CLI to leverage Kubernetes and the Docker for CI/CD system runtime environment to build, test, and deploy Octopus.
• Worked on Docker-Compose, and Docker-Machine and built Docker containers for testing applications in QA.
• Involved in developing test environments for Docker containers and configuring Docker containers using Kubernetes.
• Used Kubernetes to automatically scale nodes, load balancers during peak traffic times, and initialize and update applications by assigning addresses to containers on a network overlay.
• Created Kubernetes non-production cluster pods, deployments, services, and configuration cards, created reproducible builds of Kubernetes applications and managed Kubernetes manifest files.
• Used Ansible to coordinate server configuration, software deployment, and continuous deployment for continuous updates without downtime.
• Automated recurring tasks, deployed applications, controlled changes, automated software updates, and functional validation using the configuration management tool Ansible.
• Worked with Ansible to document all infrastructures into version control.
• Using AppDynamics, performance management assistance and technical mentoring were given to application teams.
• Created YAML scripts for Ansible to restart JBoss, Tomcat, and Jetty servers via the GUI.
• Led efforts to improve system performance and availability, resulting in a 50% reduction in downtime.
• Collaborated with administrators to ensure Splunk is running and monitoring the current Infrastructure implementation actively and accurately.
• JIRA was used to track bugs, and issues, and manage projects.

Environment: Azure, Azure Devops, PowerShell, Azure DevOps pipeline, git, Java, Python, Jira, Docker, Kubernetes, Ansible, Terraform, AppDynamics, JBoss, Splunk.

Confidential

Cloud Engineer

Responsibilities:

• Worked on the AWS code deploy service to do deployments onto Demand instances built on the fly and to push artifacts into S3.
• Created AWS S3 buckets, managed objects and folders within each bucket, and managed cloud trail logs.
• Developed AWS cloud formation templates to build VPCs, subnets, EC2 instances, ELBs, and security groups with specific sizes.
• The development of a tagging standard for EC2 instances as well as additional AWS Services like Cloud Front, Cloud Watch, RDS, S3, Route53, SNS, SQS, and Cloud Trail was done.
• Used a highly available AWS environment to launch the applications in various locations and used AWS Lambda and CloudFront to lower latency.
• Using JSON scripting to create Terraform templates, I automated and provisioned AWS resources including VPC, NAT subnets, and NACLs for the deployment of Web application and database templates.
• Created reusable Templates for Terraform to create environments for staging and production when providing AWS infrastructure as code.
• Worked on migration services like AWS Server Migration Service (SMS), AWS Database Migration Service (DMS), AWS Snowball to transfer large amounts of data, and Amazon S3 Transfer Acceleration to migrate on-premises workloads to AWS in an easier and faster way using Rehost "lift and shift" methodology.
• Installation and configuration of Web Application servers like Apache, Tomcat and WebLogic.
• Installed Apache Tomcat 6, 7 and Apache Http Servers on the EC2 instances using CHEF and deployed the artifacts.
• Manage infrastructure servers for GIT and Chef as well as our QA and UAT environments using AWS EC2 instances with Auto Scaling, Elastic Load Balancing, and Glacier.
• Worked with Chef on a Continuous Integration (CI)/Continuous Delivery (CD) pipeline for AWS cloud services.
• Installed Chef-Server Enterprise On-Premises/Workstation, bootstrapped the Nodes with Knife, worked with Chef Enterprise Hosted and Written Cookbooks, uploaded them to Chef-Server, and managed on-premises applications/services.
• Using Docker Automation, AWS Elastic Container Service (ECS) scheduler was implemented to automate the deployment of applications in the cloud.
• Participated in automation of AWS EC2/VPC/S3/SQS/SNS-based services using Terraform, Python, and Bash scripts. adopted new Amazon features like ELB and EBS when they were available.
• Created reusable Templates for Terraform to create environments for staging and production when providing AWS infrastructure as code.
• Using a variety of APIs, CLI commands, and terminal operations managed highly available and fault-tolerant systems in AWS.
• Developed build and deployment scripts in Jenkins using Maven as the build tool to move from one environment to another environment.
• Worked on AWS costs by writing Ansible Playbooks to automate the start/stop of AWS resources at various times of the day by triggering it from Jenkins, as well as knowledge of RHEL on Ansible Playbooks, Modules, and Roles.
• Applied Docker containerization to work on infrastructure. worked with development support teams to put up a Docker-based continuous delivery system.
• Using customized Docker Images, added more Docker Slave Nodes for Jenkins and downloaded them from the cloud.
• Also worked on all the major Docker components, including the Daemon, Hub, Images, and Registry.
• Managed Kubernetes clusters and worked on many pods, services, deployments, labels, and health checks.
• Worked on OpenStack nova, Kubernetes monitoring, New Relic for app performance, and Sumo logic for log monitoring performance.
• Setting up and managing the DNS system on AWS using Route53 and integrating Jenkins with GIT for code pull, push, and tag creation for build and deployment.
• Performed the SVN to GIT/Bit Bucket migration and used the GIT flow procedure to manage branching strategies. Controlled repository access, security, triggers, workflows, hooks, and user access.
• Had good debugging skills for connectivity difficulties and had configured the load balancers and VPC with private subnets.
• Expertise in configuring monitoring and alerting tools such as AWS CloudWatch, AWS CloudTrail, Dynatrace, Nagios, Datadog, and Splunk Enterprise for VPN connections based on the requirements.
• System logs were monitored using Splunk, which was essential for finding problems and halting deployment operations.
• Infrastructure management, infrastructure health metrics and performance monitoring usingCloud Watch, Nagios, Logstash, Splunk, Grafana, Prometheus.
• Managed HA services, as well as Amazon EC2, Node.js, and MySQL.

Environment: AWS (EC2, ELB, S3, EBS, VPC, Route53, API Gateway, Lambda, RDS, SNS, SQS, CloudWatch), Apache Tomcat, Docker, Chef, Maven, Jenkins, GIT, Bitbucket, Python, Splunk, Nagios, Datadog.

Confidential

DevOps Engineer

Responsibilities:

• Developed IAM policies to allow access to various resources and created and improved procedures to do so.
• Using IAM, new accounts, roles, and groups were created on AWS while the JSON template was customized, and Glacier was used for backup and storage.
• Created custom sized VPCs, subnets, and NAT gateways using AWS Cloud Formation templates to ensure the deployment of Web applications and database templates.
• Integrated AWS DynamoDB with AWS Lambda to back up the Dynamo DB streams and save the values of items.
• Worked with AWS Lambda and has deployment experience with Elastic Beanstalk for AWS.
• Creating AMI Images and Cloud formation scripts to deploy instances and snapshots of EC2 instances regularly, as well as S3 backups.
• When the data is not in use, S3 backups are stored as Glaciers.
• Created S3 buckets, policies, and IAM role-based policies, as well as customized the JSON template and Glacier for storage and backup on AWS.
• Featured development release branches were created in GIT for various applications to support releases and CI builds.
• Previous experience administering GIT in distributed environments, as well as maintaining and administering the GIT source code tool.
• Developed branching, labeling, and merging strategies for all Git applications.
• Implemented and orchestrated large-scale infrastructure migration from on-premises to AWS cloud using Terraform and Cloud Formation templates.
• Administered and Engineered Jenkins for weekly Build, Test, and Deploy chain management, as well as SVN/GIT with Dev/Test/Prod Branching Model for weekly releases.
• Deployed and troubleshot Jenkins issues. Jenkins plugins were installed, upgraded, and downgraded.
• Worked on Docker Hub, primarily for middleware installations and domain configuration, creating Docker images, and managing multiple images.
• Virtualized servers with Docker for test and development environments, as well as configuration automation with Docker containers.
• Created Chef Cookbooks for various DB configurations to modularize and optimize the end-product configuration, as well as converting production support scripts to Chef Recipes and using Chef Recipes to provision AWS servers.
• Developed the Cookbook to deploy web applications using Chef. In addition, I'm in charge of creating and importing all the environments needed to run the project.
• Maven-based automated Java builds with multiple plugins for code analysis, Junit, code coverage, PMD, SonarQube, and other tools.
• Installed and managed the Artifactory repository for deploying Maven artifacts.
• Helped internal Splunk users design and maintain production-quality dashboards.

Environment: AWS, IAM, VPC, NAT, DynamoDB, EC2 instances, git, Jenkins, Maven, Docker, Chef, Java, Splunk, SonarQube.

Confidential

Build and Release Engineer

Responsibilities:

• As a member of the release engineering group, redefined processes and implemented tools on UNIX platforms for software builds, patching, source control, and release tracking and reporting.
• Create an automated build and deployment process with Ant and Hudson/Jenkins, with Tomcat as the application server.
• Jenkins server administration includes Jenkins setup, configured nightly builds, parameterized builds, and deployment automation.
• Jenkins was used for nightly builds and testing.
• Installed multiple plugins to ensure a smooth build, released build pipelines, and set up a master/slave configuration to implement multiple parallel builds.
• Maintained and managed the GIT source code tool.
• Worked on Jenkins for integrating with GIT to automate the code check-out process.
• Maintained build-related shell scripts for Maven builds. POM.xml and other build configuration files were created and modified.
• Integrated Jenkins with GitHub private repositories with Nexus Artifact repository for pushing successful build code using Maven as build Automation tool.
• Delivered specific versions of various application components into target environments.
• Data was moved to the appropriate DEV and QA Oracle databases before the code was deployed.
• Participated in the setup of JIRA as a defect tracking system, as well as the configuration of various workflows, customizations, and plugins for the JIRA bug/issue tracker.
• Installed and managed the Artifactory repository, which is used to deploy Maven artifacts and store dependent jars used during the build.
• Created build and deployment scripts in Jenkins using ANT and MAVEN as build tools to move from one environment to another.
• By configuring the Nexus repository manager, we were able to share the artifacts.
• Constantly strive to improve the scalability of the build, release, and deployment processes.
• Utilized Configuration Management tools such as Chef to automate system operations using Chef cookbooks.
• Managed all server configurations using Chef-configured Jenkins builds for continuous integration and delivery.
• Extensively used Ruby scripting on Chef Automation for creating cookbooks comprising all resources, Data Bags, templates, attributes.
• Ensure cross-team communication for release plans and policies.
• Designed and implemented an automated rollback deployment on the Staging/Production server.
• The goal is to undo previous deployment changes in the database, properties files, and war files.
• Used Confluence to create, share and collaborate on content and projects.

Environment: SVN, Shell Scripts, UNIX, SCM, GIT, Jenkins, Maven, ANT, Ruby, Jira, Puppet, Chef, Shell, Cloud computing.

Confidential

Linux System Administrator

Responsibilities:

• In charge of creating releases, staging, and deploying software across multiple environments (DEV, QA, demo, test, staging, UAT, and production).
• Developed shell scripts for backups, log collection and classification, installation, and monitoring of various system tasks.
• Create, install, and configure Red Hat Linux servers in a data center setting.
• Managing users, such as creating, deleting, and granting appropriate privileges, as well as system security
• Oversaw the administration of the Apache/Tomcat server, mail server, and MySQL databases in both development and production environments.
• Performed administrative and management tasks on Linux by running shell scripts written in the CRON tab, Python, Bash, and Python scripting languages.
• Experience with UNIX shell scripting and Python scripts for administrative task automation. By writing Python, Perl, and Shell scripts, helped with the compilation and deployment process.
• Monitored and supported UNIX systems, including upgrades to servers and workstations, backup and disaster recovery monitoring, user account setup, and security administration.
• System performance metrics such as storage, CPU utilization, and network bandwidth utilization were tracked.

Environment: Red Hat Linux, CRON tab, Python, Perl, MySQL, Apache, Tomcat server, JBoss, UNIX, Shell Scripting, Bash.