DevOps Engineer - AWS, CI/CD & Kubernetes

Swapna Vadlamani

Email: ******************@*****.***

Phone: +1-502-***-****

PROFESSIONALSUMMARY:

•Skilled professional with 10+ years of experience in Design, Development, Release & Deployment working on Amazon Web Services all within that suit the needs of an environment under DevOps Culture.

•Implemented Kubernetes Network Policies to secure east-west traffic between microservices, used Helm charts for installing Prometheus and graphana monitoring tools and dashboards for Kubernetes clusters.

•Experience working with LLM-based services, AI orchestration patterns, or AI-assisted decision workflows

•Expert with Installation of Linux and Windows OS such as RHEL 5.x/6.x/7, CentOS, SUSE Linux, Ubuntu, Windows Server 2003/2008-R2/2012-R2. Experience in Installs, Upgrades, Patches, Migration, Trouble Shooting, Security, Backup, Disaster Recovery, Performance Monitoring.

•Experience with Agile development Methodology (Scrum), and Waterfall.

•Extensive experience using Continuous Integration (CI) and Continuous Deployment (CD) tools like GitHub, Spinnaker, Bamboo, and Code Pipeline in the process right from the developer check-in the code to Production deployment.

•Extensive experience using Ant, Maven, and Gradle as build tools for the building of deployable artifacts (jar, war & ear) from source code.

•Experience with container-based technology developing Docker file, Docker images, and pushing them to Docker hub, Docker Trusted Registries, Elastic Container Registry. Developing Docker Compose file, Kubernetes manifest files, Helm charts and deploying them to Docker Swarm, OpenShift and Elastic Kubernetes Service.

•Leading the team and Designing, implementing, and deploying complex, HA multi-tier, end-to-end solutions using private and public multi cloud offerings including AWS EC2, S3, ELB, RDS, Route 53, RDS, IAM, Lambda, Code Pipeline, SNS, SES, Cloud trail, Cloud Formation, CloudFront and Auto Scaling.

•Extensive experience in IaaS, SaaS, PaaS.

•Experience with container-based deployments using Docker, working with Docker images, Docker hub, Docker Trusted Registries, Elastic Container Registry.

•Extensive experience with AWS networking, routing, security technologies VPC, Security groups, NACL, Route53, Load Balancing, Availability zones, Guard Duty, AWS Inspector, and WAF.

•Created IAM User, Policies, Roles to grant fine grained access to AWS resources and users.

•Building AWS Infrastructure using Cloud Formation and Terraform. Developed python scripts to manage AWS resources from API calls using Boto SDK also worked with AWS CLI.

•Experience in installing and configuring web servers like Tomcat, Nginx, and WebSphere. Knowledge of using various routed protocols like TCP, FTP, SFTP, SSH, HTTP, HTTPS.

•Extensive experience working on source code management tools like GitHub and Azure DevOps.

•Configured AWS Lambda as an event-driven, serverless computing to automatically run code in response to events and automatically manage the computer resources required by the code.

•Experience in load balancers like Kemp, Nginx. Experience working with static code analysis SonarQube.

•Implemented deployment strategies and patterns like Blue/Green deployment.

•Maintained multiple Applications that run in a Multi-Tenant Environment. Such as Load Balancer to Web server to App Server and Databases which are SQL or No-SQL Databases.

•Good understanding of Software Development Life Cycle (SDLC), Software Test Lifecycle (STLC) and Defect Life Cycle.

•Application Performance Monitoring and server Monitoring and creating alerts when the CPU and Memory exceed the threshold values using Prometheus, Grafana, New Relic, Cloud Watch.

•Self-motivated, able to set effective priorities to achieve immediate and long-term goals and meet operational deadlines. Able to work independently and as team member/Team player with strong analytical, problem solving and communication skills

TECHNICAL SKILLS

Operating Systems

RHEL/Centos 5.x/6.x/7, Ubuntu/Debian/Alpine, Sun Solaris 7/8/9/10, Windows Server 2003/2008/2012

Programming Languages

C, C++, Java, .Net and Python

Databases

Oracle, MYSQL, MSSQL, RDS

Version Control Tool

Azure DevOps, GitHub

Build Tools

Maven, and Gradle

CI/CD Tools

GitHub, Jenkins, Azure DevOps

Scripting / IaC

Python, Terraform, Shell,

Container Orchestration Tool

Docker Swarm, OpenShift and EKS

Artifact Management Tool

Nexus, JFrog

Bug Tracker and Testing

HP Quality Centre, RFT, TFS and Jira

Cloud Services

AWS EC2, EKS, ECR, S3,Glue, open shift, SQS, SNS, Lambda, Kinesis, RDS, DynamoDB, IAM, ELB, Cloud Formation, databricks,CLOUD WATCH and snowflake

Log Management Tool

Elasticsearch, Logstash, Kibana (ELK), New Relic and Splunk

Secret Management Tool

Vault, CyberArk Azure Key Vault, GCP Secret Manager

Web Servers

Apache, Nginx, IBM HTTP Server

Application Servers

JBoss, IBM WebSphere Application

APM and Server Monitoring

Prometheus, Grafana and New Relic

EDUCATION

•MS in Data Science, Cumberland University (2023-2025)

•Ph.D. in Biotechnology – NIT Warangal (2011–2015)

•M.S. in Molecular Bioengineering – Technical University Dresden, Germany (2003–2005)

•MTech in Chemical Engineering – NIT Warangal (2001–2003)

•B.Tech in Chemical Engineering – JNTU Hyderabad (1996–2000)

•Diploma in Statistical Techniques – IGNOU New Delhi (2015)

PROFESSIONAL EXPERIENCE

SAIC, NSA, Columbia MD AUG 2024 – Till Date

Role: Devops Engineer

Demonstrated expertise in designing, deploying, and maintaining highly scalable and fault-tolerant cloud infrastructure across AWS and Azure using Terraform.

Provisioned cloud resources using Terraform while maintaining configurations in version-controlled repositories and developing reusable modules for Development, Staging, and Production environments.

Experience building or consuming Agentic AI systems, including coordinating multiple AI agents via API endpoints

Implemented Kubernetes Network Policies to secure east-west traffic between microservices, used Helm charts for installing Prometheus and graphana monitoring tools and dashboards for Kubernetes clusters

Utilized advanced Terraform features such as count, for each, and dynamic blocks to automate resource creation based on input variables and external data sources.

Developed custom Terraform providers and provisioners to extend infrastructure automation capabilities.

Implemented advanced Terraform state management strategies using Amazon S3 and Azure Storage backends with encryption, locking mechanisms, backup, and recovery processes to ensure secure collaboration and compliance.

Configured GitHub Actions with self-hosted runners to automate infrastructure deployments and CI/CD workflows integrated with Git repositories.

Built and maintained Continuous Delivery pipelines using custom YAML workflows for Terraform, Python, and other automation scripts in GitHub Actions for reliable deployment across AWS and Azure environments.

Worked extensively with AWS, Azure and GCP Code Pipeline, Code Deploy, Code Build, and Code Commit to implement and manage CI/CD pipelines.

Deployed and managed Azure Machine Learning workspaces with customized clusters, nodes, and permissions to support MLOps operations.

Applied Python programming and libraries for development, debugging, reporting, automation, and data analysis activities.

Provisioned, configured, and managed Databricks clusters to optimize scalability, performance, and resource utilization for data processing workloads.

Monitored and optimized Databricks operational costs by implementing efficient resource allocation and cost-saving strategies aligned with business objectives.

Developed Python-based automation scripts for Azure Machine Learning and Databricks data import workflows, promoting DevOps best practices and operational efficiency.

Worked with Azure services including Azure Compute, Web Apps, Data Factory, Storage Accounts, and Media Services.

Managed Azure Blob Storage, Data Lake, and File Share services with role-based access controls, ACLs, and service principal permissions to ensure strong data governance and security.

Administered SQL Servers, Azure SQL Databases, and Synapse Serverless SQL Pools by managing user access, optimizing queries and indexes, and performing backup and recovery operations.

Configured security policies and managed user access for AML, Databricks, and Synapse environments using Azure AD groups and service principals, WAF, IAM and managed REST APIs, JSON payloads, authentication mechanisms, and API lifecycle management

Designed and managed Azure Data Factory ETL pipelines for orchestrating data integration, transformation, and secure access across multiple data sources.

Collaborated in architecting scalable analytics solutions using Azure Synapse Analytics for enterprise data warehousing and business intelligence initiatives.

Participated in all phases of the Software Development Life Cycle (SDLC), including requirements gathering, analysis, design, implementation, testing, troubleshooting, and deployment of .NET applications.

Designed, deployed, and maintained Azure Kubernetes Service (AKS) and Azure Container Instances (ACI) environments to support scalable and reliable containerized applications.

Utilized Azure Monitor and Log Analytics to implement proactive monitoring, alerting, and performance tracking for cloud infrastructure.

Assisted teams in deploying and managing application monitoring solutions such as Dynatrace on Linux servers for real-time monitoring and issue resolution.

Supported the setup, configuration, and maintenance of Collibra on Linux virtual machines to strengthen enterprise data governance and compliance initiatives.

Applied GitHub best practices including squashing commits, cherry-picking, and synchronizing repositories to maintain clean and efficient version control workflows.

Resolved source code conflicts related to commits, merges, and repository synchronization in Git-based environments.

Built and maintained monitoring dashboards using tools such as Nagios, Splunk, Dynatrace, CloudWatch, AppDynamics, Datadog and Splunk. And Azure Monitor.

Created secure Windows and Linux machine images using Packer and deployed them through Terraform automation in Azure Cloud environments.

Configured Linux Logical Volume Management (LVM) for dynamic storage allocation, filesystem formatting, and efficient disk utilization.

Maintained Linux server environments by automating log cleanup and cache management tasks to optimize server performance and storage efficiency.

Configured Azure Virtual Machines in compliance with organizational security standards by implementing firewall configurations, WAF and Linux policies.

Developed Ansible playbooks using YAML to automate provisioning, configuration management, and deployment processes across infrastructure environments.

Leveraged Ansible modules for package management, file operations, service administration, and remote task execution across multiple hosts.

Configured JIRA workflows, plugins, and customizations to support defect tracking, issue management, sprint planning, and release coordination.

IBX, Philadelphia, PA OCT 22 - July 2024

Role: AWS Devops Engineer

Responsibilities:

Leading and designed and implemented large-scale multi cloud GCP and AWS cloud infrastructure (250+ servers) using services including EC2, VPC, RDS, S3,glue,RDS Auto Scaling, ELB, Route 53, CloudFormation, CLOUD WATCH, Lambda, ECS, CloudFront, GKE and KMS.

Migrated 100+ TiB production file systems from Intel Lustre to AWS FSx, optimizing performance and storage costs.

Automated provisioning pipelines using Terraform, CloudFormation, and Ansible for EC2/VPC builds and configuration management.

Created lifecycle policies for S3 buckets, implemented cross-region replication and Glacier archiving to reduce storage costs.

Implemented Kubernetes Network Policies to secure east-west traffic between microservices, used Helm charts for installing Prometheus and graphana monitoring tools and dashboards for Kubernetes clusters

Used AWS Trusted Advisor to identify and implement cost-optimization measures across multiple environments.

Managed SSL certificate lifecycles across Nginx, Apache, Tomcat, and AWS ELB environments.

Deployed and scaled web applications via Elastic Beanstalk, supporting multi-language stacks (Java, Python, Node.js, PHP, Ruby).

Built and maintained CI/CD pipelines using Code Pipeline, Code Build, Code Deploy, Jenkins, and integrated unit/functional testing and code coverage tools (SonarQube).

Containerized applications using Docker and orchestrated deployments with Kubernetes on CoreOS; configured clusters, namespaces, and scaling workflows.

Implemented ECS-based migration from EC2 deployments, establishing cluster configurations via Terraform.

Developed AWS Lambda functions (Python boto3) triggered through API Gateway; created related IAM roles and permissions.

Configured CloudWatch metrics and alerts for resource monitoring and scaling automation also used Datadog and Splunk.

Installed and managed Ansible for configuration, environment setup, and automated application deployments.

Familiarity with LLM-based services, AI orchestration patterns, or AI-assisted decision workflows

Created custom Docker container images, managed ECR repositories, and automated build pipelines for base and multi-stage images.

Designed and supported HA-ready Windows SOFS and multi-AZ RDS deployments for production-critical applications.

Developed Python and Shell scripts to automate build/release processes, DevOps utilities, and analytics workflows (AWS Lambda + Big Query).

Ensured compliance and governance through Terraform policy-scanning workflows and best-practice DevOps automation.

ENVIRONMENT: AWS EC2, S3, RDS, AMI, IAM, Redshift, Lambda, VPC, Chef, Java, Git, Jenkins, Terraform, Python, Linux, Bash, Groovy, Subversion, Rest API, Ant, Maven, Nexus, U-deploy, SQL, Cloud Formation, Golang, OpenShift, Cassandra, Subversion, Selenium, UNIX, SVN, Docker, Jira, Python, Ruby, Shell Scripts, Tomcat, Databricks Ansible, Splunk.

Spectrum digitals Ltd Nov 2019 - June 2022

Role: DevOps Engineer

Responsibilities:

Written Ansible playbooks for Administration like Installing, configuring, and maintaining Dockized Jenkins (Master and Slave architecture), Nginx, Nexus, Apache Tomcat, Docker swarm 10 node architecture, Redis, ECS, EKS, OpenShift, RabbitMQ, Oracle, MySQL, JFrog Antifactory, PostgreSQL Oracle WebLogic server in Dev, QA, Staging, UAT and Prod.

Developed Cloud Formation and Terraform Cloud for provisioning AWS infrastructure like VPC, EC2, RDS, S3, SNS, IAM, SQS, ECR, ALB, NLB, API Gateway, DynamoDB, Amazon Document DB and Route53. PaaS services like EKS, Elastic Beanstalk.

Provisioned AWS VPC, Private and Public Subnets, Route tables, NACL, Security Groups, VPC peering and Direct Connect.

Deployed the microservices using Spinnaker and integrated Continuous integration using Jenkins.

Developed GitHub actions and workflow to kick off the Terraform plan and worked on Terraform Provisioners like local-exec, remote-exec to prepare the infrastructure for service.

Designed and deployed scalable data pipelines and ML-ready infrastructure using Kubernetes and Docker.

Integrated Azure DevOps pipelines with Python-based machine learning workflows.

Integrated Azure Services like App Service, Key Vault, Logic app, Azure Storage, Azure, Blob Storage, Azure VMs, Azure Queue Storage, SQL Database, Azure event grid, Azure Event Hubs, Azure Functions, Azure Data Factory, Data Bricks, RabbitMQ, Azure Monitor, and Azure Service Bus.

Implemented CI/CD automation with Terraform and Ansible for AI-driven projects using snowflake and also data bricks in one of the project for data ingestion pipelines.

Standardized the Terraform code by using TF modules so that it can be shared across different teams in our organization.

Developed Groovy scripts Modular Pipeline Library (MPL), nested libraries with shared libraries and shared across the different teams and Bamboo Java Specs to automate the CI/CD in Jenkins and Bamboo. Integrated pipeline with SonarQube, Harshi Corp Vault, Selenium WebDriver, Checkmarx, Jira Also implemented AWS Code Pipeline using the AWS developer tools like Code Commit, Code Build and Code Deploy.

Migration services from on-prem to AWS, refactoring Monolithic application to microservices architecture and migrating DB to AWS RDS.

Involved in developing high availability, scalability, reliability of infrastructure and implementing DR strategy in our datacentre.

Automated repetitive tasks using Bash, PowerShell, Ansible, and Python.

Developed Docker files, building and pushing the docker images to DTR/ECR, developed docker-compose files, Helm charts, Kubernetes Manifest files and deploying the microservices on Docker Swarm, AWS Elastic Kubernetes Service (EKS) and OpenShift.

Installed, configured Helm, and managed Kubernetes manifest files using Helm charts.

Setup load balancer to achieve high availability of applications running on EC2 instances and configure health checks for AWS ELB and use sticky sessions to redirect the users based on traffic spikes to avoid downtime.

Deploying / Promoting microservices to Docker Swarm, EKS, OpenShift.

Generating SSL certs and setting up Nginx proxy for Jenkins and SonarQube and Implemented the branching and merging strategy.

Well-versed with using Jenkins/Bamboo/Code Pipeline to drive all microservices build to the Docker registry and further deploying them to Kubernetes, creating Pods, refactoring monolithic applications to Microservices and Component-based architectures.

Engaging with the teams on understanding the application architecture and requirements for provisioning the environment and application technology stack as Infrastructure as Code (IaC).

Implemented and maintained the monitoring and alerting of production and corporate servers/storage using AWS Cloud Watch, Datadog and Splunk.

Written the Lambda functions for starting and stopping the EC2 Instances with the tag names for reducing the uptime of unused instances. Wrote a bash script to trigger the user data of an ec2 instance on every start of an instance.

Responsible for writing the Python scripts for finding the provisioned IAM resources.

Written Python scripts to automate blue green deployment using AWS ELB.

Using SonarQube for static code analysis and failing the build if it does not meet the threshold values.

Automated the java builds and deploys using shell script and .NET builds.

Troubleshoot and resolving any build and deployment failures based on the docker logs within the container.

Implemented best practices to suffice the application load during peak times by using the AWS autoscaling service for compute instances and Horizontal Pod Autoscaler (HPA) for microservices on Kubernetes platform.

Utilizing different load balancers Nginx, NLB, ALB.

Created Docker Images using a docker file, worked on Docker Container Snapshots, removing images, and managing Docker Volumes deployed using Kubernetes.

Load balancing the pods using Nginx Ingress and NLB ingress to expose the application endpoints in EKS, created API gateway to expose the end point to external customer and configured the SSL security certs to protect the ingress traffic from DDOS attacks.

Installed and configured cloud native security tool Prisma Twist Lock for finding vulnerabilities in containers and registries.

Updating the application properties as per new Vault folder structure. APM and Server monitoring using New Relic.

Logging bugs and findings in Jira and assigning it to the relevant team. Creating builds docs, run books and publishing to Confluence.

NIPER, India Mar 2014 - Sep 2019

Role: Machine Learning and Data Analyst

Responsibilities:

•Configuring and Administrating Cron Jobs. Involved in Creating Shell Scripts like Automation of Startup and Shutdown Processes.

•Configured volumes Using LVMs for increasing of disk space.

•Maintained and administered GitHub source code tool created branches and performed merges in GIT.

•Proposed and implemented branching strategy suitable for agile development in GitHub and Azure DevOps.

•Installed and configured GitHub for automating build and deployment and providing an automation solution.

•Integrated Jira into Jenkins.

•Used various plug-ins to extend the base functionality of GitHub to deploy, integrate tests and display reports

•Owned Release to Production Process, gathered approvals, signoffs from managers and QAs before going to PROD.

•Configuring Java applications to do a build once, pushing artifacts to Nexus and deploying/promoting to various environments and DR in Jenkins.

•Configured webhook in GitHub to auto trigger the build when the pull request is merged to develop branch.

•Maintained the Shell scripts for automation purposes.

•AI Model for COVID-19 Detection (Python, TensorFlow, Kera’s, Azure AI-ML)

Developed a deep learning model on 2000 HRCT chest CT images with 95% accuracy

•Machine Learning Model for Solubility Prediction

- Built predictive models in Python (linear regression, SVM, decision tree) for solubility estimation.

- Identified decision tree as the best-fit model.

•Diabetes Prediction Model

- Designed LLM a Python-based machine learning pipeline analysing risk factors (BP, age, weight, height).

- Used classification algorithms to predict diabetes outcomes.

Certifications:

•Microsoft Azure AI-ML Certified,

•Microsoft AZ-400 DevOps Engineer Expert

Contact this candidate