Mamta Yadlpalli, AWS DevOps Developer in Jersey City, NJ, United States
Mamta Yadlpalli

AWS DevOps Developer in Jersey City, NJ, United States

Member since June 16, 2020
Mamta is a DevOps and cloud engineer with seven years of experience in on-prem infrastructure and cloud computing. She has expertise in working with AWS and has developed web applications using various JavaScript libraries, HTML, XML, and CSS, deploying them into the cloud platform using Kubernetes and cloud formation templates using Terraform. She has a basic understanding of Google Cloud Platform (GCP) and deployed resources to GCP using terraform.
Mamta is now available for hire


  • ArrAy
    Google Cloud, Terraform, AWS, Terragrunt, GitLab, GitHub...
  • Sun Nuclear
    Git Hub actions, YAML, AWS, GitHub, AWS CloudFormation, Docker, Node.js, Python
  • Syngenta
    AWS Service Catalog, AWS DynamoDB, Amazon SageMaker, AWS NLB, AWS EC2...



Jersey City, NJ, United States



Preferred Environment

GitLab, GitHub, VS Code, Windows, Linux

The most amazing...

...project I've developed and deployed is a Data Lake that supports infrastructure solutions in AWS to meet the business requirements using AWS and Terraform.


  • DevOps Engineer

    2021 - 2021
    • Migrated the infrastructure from AWS to GCP via Terraform templates.
    • Worked with Terragrunt to manage the Terraform templates and created a staging and production environment.
    • Created a Google-managed SSL certificate using Terraform templates.
    • Architected Terraform templates to provision the resources in GCP. Provisioned the services such as cloud storage, Cloud SQL, GKE, compute engine, and log metrics, among others.
    • Set up alerting and monitoring using Stackdriver in GCP using Terraform templates. Created custom log metrics using Stackdriver logging and created charts and alerts using the custom log metrics.
    • Used GitLab and GitHub as a source code repository and created the CI/CD pipeline for the deployments in AWS and GCP.
    • Set up Terraform to automate the creation of GKE Kubernetes cluster in Google Cloud with the best security standards.
    • Set up GCP Firewall rules in order to allow or deny traffic to and from the VM's instances based on specified configuration.
    • Used Terraform and created projects, VPC's, subnetwork's, and GKE clusters for environments.
    • Created dynamic routing/load balancing capability enabling large application scaling; used Ingress rules and Ingress controllers.
    Technologies: Google Cloud, Terraform, AWS, Terragrunt, GitLab, GitHub, Google Kubernetes Engine (GKE), Kubernetes
  • DevOps Expert

    2021 - 2021
    Sun Nuclear
    • Worked with GitHub Actions for continuous integration and continuous deployment process. Responsible for creating the actions and workflows for the git repository for continuous integration and continuous deployment.
    • Created the cloud formation templates to create various resources in the AWS through the workflow. The cloud formation stacks are also created through GitHub actions. Auto destroys the cloud formation stacks on the deletion of a branch in GitHub.
    • Managed CI/CD pipelines using Github Workflows and Actions. Triggered the workflows on different events like push, pull, delete, schedule, and workflow dispatch, which is used to provide the input values by the user.
    • Worked with the workflow distributor to distribute the workflow between the repositories. This would run the workflow on a scheduled time and update the workflows in different repositories.
    • Used third-party actions from GitHub marketplace in the workflow. Workflow triggers different events of a repository to process a new build of our application.
    • Performed continuous build, continuous deploy, and test jobs using git actions.
    • Used Docker images and deployed the application in the Docker container through CI/CD using workflows in GitHub Actions.
    Technologies: Git Hub actions, YAML, AWS, GitHub, AWS CloudFormation, Docker, Node.js, Python
  • AWS-Cloud Formation

    2020 - 2021
    • Developed the cloud formation scripts to provision all the services by using the cloud factory application, this is an application that is similar to Amazon console that the client is developing.
    • Migrated all the services to cloud factory UI using Cloud formation templates. Then the customer can provision the cloud services from there.
    • Worked in the AWS MALZ environment (multi-account landing zone), a centralized shared service to eliminate costs, A preconfigured network to interconnect multiple Amazon virtual private clouds, on-premises, AMS operators, and the internet.
    • Automated workflows to quickly provision new accounts, also known as an account vending machine. Cross-account logging and monitoring to facilitate audits, diagnostics, and analytics. Governance rules for security, operations, and compliance.
    • Provisioned more than 30 services using the cloud formation and integrating those scripts into the cloud factory UI. Used GitHub to push the code to code commit and run the build process.
    • Developed the UI using JavaScript and the UI updates with the glue job that ran in a 24-hour timeframe and stored the data in the test database. It integrated the test and prod environment with the glue job.
    • Created product files in the service catalog using cloud formation. The service catalog maintains the version of the code, and we can roll back if there is any code failure.
    Technologies: AWS Service Catalog, AWS DynamoDB, Amazon SageMaker, AWS NLB, AWS EC2, AWS CodeBuild, AWS CodePipeline, AWS CodeCommit, AWS CodeDeploy, AWS CloudWatch, AWS S3, YAML, JavaScript, AWS CloudFormation
  • DevOps/Back-end Developer

    2020 - 2020
    Client (via Toptal)
    • Created an application that handles the financial data and stores the purchase receipts to DynamoDB and Amazon RDS. Based on the client's request, the data is sent back to the client based on the requested data.
    • Triggered a Lambda function with API gateway, DynamoDB, S3 SQS, and SNS. Wrote Lambda functions in Node.js and Python.
    • Created CloudFormation templates for different environments (DEV/stage/prod) to automate infrastructure (ELB, CloudWatch alarms, ASGs, SNS, RDS, etc.) with the click of a button.
    • Provided the security to API Gateway with AWS Cognito. Configured and managed AWS Simple Notification Service (SNS) and Simple Queue Service (SQS).
    • Managed cryptographic keys and controlled the user to access the various platforms with Amazon KMS.
    • Created a Lambda Deployment function, and configured it to receive and store events from your S3 bucket.
    • Installed, configured, and managed RDBMS and NoSQL tools such as DynamoDB.
    • Implemented a serverless architecture using API Gateway, Lambda, and DynamoDB and deployed AWS Lambda code from Amazon S3 buckets.
    • Worked on Amazon RDS Multi-AZ for automatic failover and high availability at the database tier for MySQL workloads.
    Technologies: API Gateways, Amazon Cognito, AWS CloudFormation, AWS DynamoDB, AWS Push Notification Service (AWS SNS), Amazon SQS, AWS Key Management Service (KMS), AWS SDK, AWS S3, GitHub, AWS CloudWatch, JavaScript, Node.js, AWS Lambda
  • Senior Cloud Engineer

    2017 - 2020
    • Managed AWS EC2 instances utilizing autoscaling, elastic load balancing, and Glacier for our QA and UAT environments.
    • Built AWS infrastructure resources, load balancers (ELBs), VPC EC2, S3, IAM, importing volumes, EBS, security group, auto-scaling, and RDS in Cloud Formation templates.
    • Migrated an existing on-premises application to AWS. Used AWS services like EC2 and S3 for small data set processing and storage. Maintained the Hadoop cluster on AWS EMR.
    • Set up a continuous integration environment using Jenkins for building jobs and to push the artifacts into an Artifactory repository on successful builds.
    • Added a multi-factor authentication (MFA) to protect the user identity and validated the sign in details. Created user pools to maintain the user directory using Amazon Cognito. Customized workflows and user migration through AWS Lambda triggers.
    • Automated the download process with Shell scripting from AWS S3 bucket. Worked with EMR and set up the Hadoop environment in AWS EC2 instances.
    • Created AWS CloudWatch alarms to monitor the performance environment instances for operational and performance metrics during load testing.
    • Provided 24x7 on-call support to all other engineering, administration, development, and application support teams.
    • Created automated scripts that will build, configure, deploy, and test applications deployed to different environments; maintained, supported, and enhanced the continuous integration environment.
    • Assisted an automation scripting and execution framework design and development using Selenium WebDriver. Analyzed test requirements and automation feasibility. Used JUnit and TestNG controllers for data extraction and generation of proper reports.
    Technologies: Amazon Web Services (AWS), Jenkins, Apache Tomcat, Python, Bash Scripting, Shell Scripting, AWS, Express.js, Node.js
  • DevOps Engineer

    2015 - 2017
    • Implemented and supported monitoring and alerting of production and corporate servers/storage via AWS CloudWatch.
    • Maintained and expanded AWS (Cloud Services) infrastructure using AWS Stack.
    • Automated provisioning and maintained a large number of servers on AWS instances. Experienced in cloud migration to AWS. Involved in the planning, implementation, and growth of our infrastructure on Amazon Web Services (AWS).
    • Created complete CI/CD pipelines using Jenkins.
    • Configured networking concepts DNS, NFS, and DHCP, troubleshooting network problems such as TCP/IP.
    • Maintained, updated, and configured all Windows and Linux servers to ensure 24/7 uptime.
    • Built and maintained Docker container clusters managed by Kubernetes Linux, Bash, Git, and Docker on AWS.
    • Built, maintained, and scaled the infrastructure for production, QA, and development environments.
    • Implemented a cloud infrastructure with full automation and created the first regulated exchange production disaster recovery in the cloud on Amazon’s AWS platform.
    • Secured an EMR launcher with custom spark-submit steps using S3 Event, SNS, KMS, and Lambda function. Executed Hadoop/Spark jobs on AWS EMR using programs and data stored in S3 Buckets.
    Technologies: Ansible, Chef, Puppet, Bitbucket, Jenkins, Nginx, Amazon Route 53, AWS CloudTrail, AWS CloudWatch, Terraform
  • Software Developer

    2013 - 2014
    • Worked with the Serverless framework. Involved in gathering the requirements from the stakeholders.
    • Developed ad-hoc reports and worked with RESTful APIs.
    • Handled the deployment, scaling, and performance of our applications through their entire lifecycle from development to production.
    • Created a migration road map and CI/CD delivery processes to convert the application from a monolithic to microservices architecture.
    • Developed an SMTP protocol and servlets for securing the application.
    • Created and managed various development, build platforms, and deployment strategies.
    • Implemented Autosys for scheduling the ETL, Java, WebLogic, and PL/SQL jobs.
    • Performed regular updates and installation of patches using RPM and YUM.
    • Wrote PowerShell scripts to pull the data from the APIs.
    • Delivered scalable, resilient, and automated builds in a cloud environment using Cloudformation, Ansible, and Jenkins for high-quality data pipelines.
    Technologies: AWS DynamoDB, MySQL, Servlets, Microsoft SQL Server, Vue.js, Windows, Linux, YAML, JSON, jQuery, Java


  • Trans Automation

    The app generates reports to help users know about the portfolio of their accounts in different categories like loans, credit card statements, and billing management. Annual reports are then generated automatically by analyzing those individual reports.
    Each functionality is divided into separate microservices, the front end is developed with Vue.js, JavaScript, HTML5, and CSS3. The back end is developed with Node.js. I used EMR to securely handle a large amount of data. The application is stored in an S3 bucket. Once the clusters are created, EMR integrates with Amazon cloud watch to monitor the cluster. Automatic troubleshooting using debug GUI. EMR destroys the cluster automatically.


  • Libraries/APIs

    Node.js, Vue.js, REST APIs, jQuery, Terragrunt
  • Platforms

    Amazon Web Services (AWS), Kubernetes, Docker, Linux, AWS EC2, AWS Lambda, Windows, AWS NLB, Google Cloud Platform (GCP)
  • Languages

    HTML, JavaScript, Python, Java, YAML
  • Frameworks

    Express.js, AWS EMR, Selenium, TestNG, JUnit
  • Tools

    Terraform, Jenkins, AWS IAM, Amazon Cognito, Amazon SQS, VS Code, GitHub, GitLab, AWS CloudFormation, AWS CloudWatch, AWS SDK, AWS Key Management Service (KMS), AWS Push Notification Service (AWS SNS), Apache Tomcat, AWS CloudTrail, Nginx, Bitbucket, Puppet, Chef, Ansible, Amazon EKS, AWS CodeDeploy, AWS CodeCommit, AWS CodeBuild, Amazon SageMaker, Google Kubernetes Engine (GKE)
  • Paradigms

    Testing, Data Science, Continuous Integration (CI), Continuous Development (CD)
  • Storage

    MongoDB, SQL Server 2012, AWS S3, AWS DynamoDB, JSON, Microsoft SQL Server, MySQL, Google Cloud
  • Other

    Kubernetes Operations (Kops), AWS DevOps, Machine Learning, Git Hub actions, API Gateways, AWS, Shell Scripting, Bash Scripting, Amazon Route 53, Servlets, AWS CodePipeline, AWS Service Catalog, GitHub Actions


  • Master's degree in Computer Science
    2015 - 2016
    New York Institute of Technology - New York


  • Certified Solutions Architect - Associate

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