SUMMARY:

• An experienced IT professional with 7+ years of work experience as a Cloud/DevOps engineer. Good knowledge in hybrid cloud platforms like Amazon Web Services(AWS), Microsoft Azure. Experience in provisioning resources to Infrastructure as code with tools like Terraform, Cloud
• Formation. Hands - on experience in containerization, orchestration tools like Docker, Kubernetes. configuration management tools like Ansible, Chef, Puppet. Worked with continuous Integration and Continuous Delivery(CI/CD) tools like Jenkins to Build and Release applications.
• Experience in configuring and maintaining Amazon Web Services which include services like Amazon EC2, ELB, Auto-Scaling, S3, Route53, IAM, VPC, RDS, Dynamo DB, Cloud Trail, Cloud Watch, Elastic Cache, SNS, SQS, Cloud Front, and Lambda, EMR, Elastic Beanstalk and focusing on high-availability, fault tolerance, and Auto-scaling in AWS CloudFormation.
• Experience in Designing data models to be used in data-intensive AWS Lambda applications which are aimed to do complex analysis creating analytical reports for end-to-end traceability, lineage, the definition of Key Business elements from Aurora.
• Expertise in configuring AWS Multi-Factor Authentication in IAM to implement 2 step authentication of user's access using Google Authenticator and AWS Virtual MFA and Included security groups, network ACLs, Internet Gateways, and Elastic IP's to ensure a safe area for the organization in AWS public cloud.
• Expertise in writing AWS CloudFormation templates in JSON to use them as blueprints for building and deploying multiple AWS resources also worked on Kinesis Data Streams &, Kinesis Firehouse &, integrated with AWS Lambda for serverless data collection.
• Experience on AWS, focusing on high-availability, fault tolerance, and auto-scaling using Terraform templates. Along with (CI/CD) with AWS Lambda and AWS Code Pipeline. Good Knowledge using AWS Lambda for server-less computing using python and java.
• Experi

PROFESSIONAL EXPERIENCE:

Confidential

DevOps Consultant

Responsibilities:

• Worked on different AWS services like S3, route53, EFS, EKS, ECS to manage and maintain the workloads in the EKS cluster. Used different storage services like EBS volumes, EFS, RDS Aurora in a Kubernetes application as shared and un - shared storage classes. Used S3 buckets to store data across regions for backup, restore, and disaster recovery purposes. Used Terraform for Infrastructure as code to deploy
• EKS clusters and spin up a agent to access the cluster. Created many AWS services using Terraform to automate the process for higher environments. Developed many Terraform modules to create IAM roles and policies for different third-party applications and used Kubernetes service accounts to use the roles. Worked with Kubernetes to provide a platform for automating deployment, scaling, and operations of application containers across clusters of hosts and managed containerized applications using its nodes. Deployed Kubernetes Clusters on cloud environments, wrote many YAML files to create many services like pods, deployments, auto-scaling, load balancers, and Managed
• Kubernetes charts using Helm. Extensively worked on deploying several third-party applications on to the EKS cluster using helm charts and automated the whole process of building and deploying the charts using Jenkins. Used Prometheus for Kubernetes integration for service discovery and monitoring of metrics of the application and integrated the Prometheus endpoint into Datadog agent to visualize them. Involved in deploying Cloudbees CD application onto a EKS cluster and halped teams migrate from an existing CI/Cd environment to EKS environments.
• Used Fluent Bit to handle the data logs from AWS cloud watch and routed them to specified log groups to make them easier to manage. Used Nexus as a Binary, Artifact hub to store application related artifacts, helm charts and download them through Jenkins deployment jobs. Used Datadog to create dashboards for different applications and AWS accounts to get real time metrics for services like
• Kubernetes workloads by deploying Datadog agents in the EKS cluster. Deployed Kasten a tool used for backup and restore of Kubernetes workloads onto a EKS cluster using helm charts and used Jenkins to deploy the same chart onto multiple AZ. Used Kasten to backup the applications and restore them to a different AZ and failover in case of DR. Written custom scripts using shell to automate the Backup and DR process for applications running in the EKS clusters.

Confidential

Senior AWS Cloud Engineer

Responsibilities:

• Designed and maintained application deployments AWS infrastructures utilizing services such as EC2, RDS, VPC (managed network and security), Route 53, Direct Connect, IAM, Cloud Formation, AWS Ops Works (automate operations), Elastic Beanstalk, AWS S3, Amazon
• Glacier (storage in the cloud) and Cloud Watch monitoring management. Created S3 buckets for storage, managed policies for S3 buckets, and experience in configuring instance backups to S3 buckets to ensure high availability and fault tolerance. Developed Python scripts to put nexus backup to the S3 Buckets Utilized AWS CLI for spinning up Redis Elastic cache. So dat cloud applications can use Redis elastic cache for the data reads, theirby increasing performance for the application Designed AWS Cloud Formation templates to create custom - sized
• VPC, subnets, NAT to ensure successful deployment of Web applications and database templates. Configured auto-scaling in customized VPC, based on elastic load balancer (ELB) traffic and using ELB health check to trigger auto-scaling actions. Implemented a centralized logging system using log stash configured as an ELK stack (Elastic Search, Log stash, and Kibana) to monitor system logs, AWS Cloud Watch, VPC Flow logs, Cloud Trail Events, changes in S3. Executed HTTPS/HTTP requests through the running AWS EC2 instances, theirby enhancing connection requests to the systems. Thus, enabling a faster data transaction between the Target groups which are attached to AWS
• Security groups and Autoscaling groups. Worked on Terraform for automating VPCs, ELBs, security groups, SQS queues, S3 buckets, and continuing to replace the rest of our infrastructure and managed different infrastructure resources Cloud, VMware, Bare Metal Servers, and
• Docker containers. Developed Terraform modules dat implement DynamoDB with support for autoscaling and Wrote many Infrastructure as a code library using Terraform and transformed Terraform as an enterprise-level infrastructure automation tool. Implemented AWS Elastic Container Service (ECS) scheduler to automate application deployment in the cloud using Docker Automation techniques. Worked on several
• Docker components like Docker Engine, Hub, Machine, Docker images, compose, Docker registry, and handling multiple images primarily for middleware installations and domain configurations. Used Docker containerization to make our application platform to be consistent and flexible even when they are shifted in multiple environments Created Docker images using a Docker file. Worked on Docker container snapshots, removing images and managing Docker volumes and experienced with Docker container service. Involved in launching Docker containers on pods on top of the multi-node Kubernetes cluster in an AWS environment with the halp of KOPS and Kubectl. Deployed
• Kubernetes Clusters on cloud environments, wrote many YAML files to create many services like pods, deployments, auto-scaling, load balancers, and Man

Confidential

Cloud DevOps Engineer

Responsibilities:

• Worked with AWS CLI and AWS API to manage resources on AWS for many services such as an EC2, S3, VPC, Cloud Watch, ELB, Auto - scaling, created python script using AWS API Calls to manage all resources deployed on AWS. Worked with AWS S3 and IAM services, created S3 buckets, and configured them with permissions, logging, versioning, and tagging and created new IAM users and groups, defined roles, policies, and identify providers.
• Familiar with AWS Lambda to run the code in response to events, such as changes to data in an Amazon S3 bucket, Amazon DynamoDB table, HTTP requests using AWS API Gateway, and invoked the code using API calls made using AWS SDKs. Has been part of a team to perform POT's/POC's on Azure cloud utilization in our organization and has been part of migrating our application from AWS to Azure cloud.
• Experienced in Azure Development, worked on Azure web application, Virtual machines, Virtual Networks, Azure data factory, Resource
• Groups, Load Balancing, Application Insights, Azure AD, Azure blob storage. Experience in using Azure service fabric to package, deploy, and manage scalable and reliable microservices and containers. Created and implemented ARM templates and deployed them using the Azure portal, also used Azure quick-start templates for Cloud Infrastructure design and implementation to deploy Web applications on Azure
• PowerShell Workflow. Deployed and optimized two-tier web application to Azure DevOps to focus on development by using services such as Repos to commit codes, Test Plans to trigger application, and unit test. Worked with Terraform Templates to automate the Azure IaaS virtual machines using Terraform modules and deployed virtual machine scale sets in a production environment and implemented Terraform
• Enterprise to provision infrastructure across Azure workloads and Kubernetes clusters. Wrote terraform scripts from scratch for building Dev,
• Staging, Prod, and DR environments and Automated the provisioning and repetitive tasks using Terraform and Python, Docker container, Service Orchestration. Used Docker for setting Azure Container Registry with Docker and Docker-compose, actively involved in deployments on Docker using Kubernetes. Expertise in using Docker to containerize custom web applications and deploy them on Digital Ocean with
• Ubuntu instances through SWARM Cluster and to automate the application deployment in the cloud using Vagrant. Worked on deploying the
• AKS (Azure Kubernetes services) cluster by installing the Kubernetes through CLI using ACR authentication and then configured and connected it to the cluster Used Azure DevOps pipelines to drive all microservices builds out to the Docker registry and then deployed to Kubernetes, Created Pods, and managed using Kubernetes. Created an Azure cloud using Kubernetes dat supports DEV, TEST, and PROD environments. Implemented a production-ready, load-balanced, highly available, fault-tolerant, auto-scaling Kuber

Confidential -Huston TX

AWS Infrastructure Engineer

Responsibilities:

• Involved in designing and deploying a multitude of applications utilizing almost all the AWS stack including EC2, Route53, S3, RDS, Dynamo DB, SNS, SQS, LAMBDA, REDSHIFT, focusing on high - availability, fault tolerance, and auto-scaling in AWS cloud formation. Created AWS
• IAM to securely control users' access to AWS services and resources by enforcing granular permissions, controlling share access to AWS accounts, applying multi-factor authentication, and enabling identity federation. Designed AWS Cloud Formation templates to create custom-sized VPC, subnets, NAT to ensure successful deployment of Web applications and database templates Creating Cloud formation scripts for hosting software on AWS Cloud. Automating the installation of Software through PowerShell scripts. Written Cloud Formation Templates (CFT) in JSON and YAML format to build the AWS services with the paradigm of Infrastructure as a Code (IaaS). Developed Templates for AWS infrastructure as a code using Terraform to build staging and production environments. Set up CI/CD pipeline integrating various tools with
• CloudBees Jenkins to build and run Terraform jobs to create infrastructure in AWS. Included Vulnerability Detection as a part of the CI/CD workflow using Jenkins Pipelines, SonarQube Quality Gates. Installed Jenkins/Plugins for GIT Repository, Setup SCM Polling for Immediate
• Build with Maven and Maven Repository. Built Jenkins jobs to create AWS infrastructure from GitHub Repos containing terraform code. Generating artifacts by integrating Jenkins with Git and Maven and storing artifacts into Nexus and deploying them into the application server.
• Used Jenkins for Continuous Integration and deployment into Tomcat/Web Logic Application Server and Implemented continuous integration and tracking source code changes using Jenkins. Worked Jenkins and Build forge to perform Nightly builds and Milestone builds and
• Continuous Integration. Worked with Chef Environment, Installing Workstation, Bootstrapping Nodes, setting up Chef Server, bundling recipes into cookbooks, and uploading them to Chef-server. Written Chef Cookbooks for various DB configurations to modularize and optimize product configuration, converting production support scripts to Chef Recipes. Build, manage, and continuously improved the build infrastructure for global software development engineering teams including implementation of build scripts, continuous integration infrastructure, and deployment tools1.
• Perform root cause analysis for service interruption recovery, created preventative measures, and present to management Assisted in the analysis, design, and development of a roadmap and implementation based upon a current vs. future state in a cohesive architecture viewpoint.

Confidential

DevOps Engineer

Responsibilities:

• Experience in Branching, Merging, Tagging, and maintaining the version across the environments using SCM tools like Subversion (SVN), GIT (GitHub, GitLab). Integrated GIT into Jenkins to automate the code check - out process and configured the components from GitHub into Jenkins server. Responsible for automated scheduled build/emergency build and release using ANT and Maven scripts for enterprise application.
• Used Puppet server and workstation to manage and configure nodes and wrote Puppet manifests to automate the configuration of a broad range of services. Developed Puppet modules and role/profiles for installation and configuration of software required for various applications/blueprints.
• Assisted Operations Team by writing specific Puppet manifests to deal with application installations and related configuration files. Involved in the troubleshooting of issues during the build, integration, and deployments of the code and created scripts for taking the backups of important files and folders in the Linux environment.
• Created JIRA issues to prioritize and act on what's important and stayed up to date with what's going on around the project. Involved in setting up
• JIRA as a defect tracking system and configured various workflows, customizations, and plugins for the JIRA bug/issue tracker. Installed and configured Nagios to constantly monitor network bandwidth, memory usage, and hard drive status. Monitored the health of the application using Nagios Involving and partitioning formatting disks and managed filesystem with RAID, LVM. Installed and maintained the Splunk adds-on including the DB Connect 1, Active Directory LDAP for work with directory and Dynamo database. Developing Splunk queries and dashboards targeted at understanding application performance and capacity analysis.

Confidential

Jr Python Developer

Responsibilities:

• Developed several Python APIs dat work both in Linux and windows and maintaining them using the version control SVN. Developed Python wrapper for instantiating multi - threaded applications and running with other applications. Used and connected application through Django ORM to interacting with the
• SQL database. Used HTML, CSS for developing the front end of the application. Worked with TCP/IP, IPv4, and IPv6 protocols in an environment, which provides multithreading, multitenancy, and high availability support at Network Layer.