Sr. Devops Infrastructure Engineer

Anil Gogineni Phone: +1-978-***-****

Sr DevOps Infrastructure Engineer

E-mail: **************@*****.***

LinkedIn: www.linkedin.com/in/anil-gogineni-devops

PROFESSIONAL SUMMARY

• Over 8 years of experience in the IT industry, focusing on Continuous Integration/Continuous Deployment (CI/CD) processes, Linux Administration, Build & Release Management, DevOps practices, and Cloud Administration.

• Deep expertise in AWS, utilizing services like IAM, EC2, EKS, EBS, VPC, RDS, CloudWatch, CloudTrail, CloudFormation, Autoscaling, CloudFront, S3, SQS, SNS, Lambda, and Route53 for comprehensive cloud solutions.

• Proficient in Google Cloud Platform (GCP), employing technologies such as Compute Engine, App Engine, Cloud Storage, Cloud Functions, Cloud SQL, Dataproc, and Google Kubernetes Engine (GKE) for scalable cloud architectures.

• Developed custom scripts to validate DNS propagation and monitor record consistency across AWS, Azure, and GCP using CloudWatch and Azure Monitor.

• Experienced in managing and deploying systems in Azure, including VMs, Blob Storage, Virtual Networks, DNS, Azure Functions, and Azure Kubernetes Service (AKS).

• Administered Kubernetes clusters (EKS, AKS, GKE) for production-grade orchestration of containerized applications, including advanced RBAC and network policies.

• Expert in managing Docker-based microservices and integrating them into Kubernetes with Helm charts, ingress controllers, and service meshes.

• Migrated monolithic applications to containerized microservices deployed on Kubernetes and integrated them with CI/CD pipelines.

• Streamlined infrastructure deployments for Kubernetes clusters (GKE/EKS) using Terraform and automated cluster lifecycle management.

• Designed event-driven architectures with AWS Lambda, GCP Cloud Functions, and Azure Functions, enabling serverless automation and cost optimization.

• Developed RBAC and IAM strategies across cloud providers to enforce least-privilege access and secure workload identity in Kubernetes.

• Delivered high-availability solutions using AWS ALB/NLB, GCP Cloud Load Balancing, and Azure Application Gateway, supporting global traffic distribution.

• Implemented FinOps practices, using AWS Cost Explorer, GCP Billing, and spot instances to reduce cloud spend and improve resource efficiency.

• Passionate about driving Site Reliability Engineering (SRE), defining SLIs/SLOs, automating incident response, and fostering a culture of continuous improvement.

CERTIFICATIONS

• AWS Certified DevOps Engineer – Professional

• Certified Google Cloud DevOps Engineer – Professional

• Certified HashiCorp Certified: Terraform Associate (003)

• Certified Kubernetes Administrator (CKA)

TECHNICAL SKILLS

AWS Services EC2, ELB, VPC, RDS, AMI, IAM, S3, EKS, Cloud Formation, Kinesis, Cloud Watch, Cloud Trail, SNS, SQS, SWF, EBS, Glacier, RedShift, Route 53, ECR, Code Build, Code Deploy.

GCP Services Compute Engine, GKE, Cloud Functions, Cloud Storage, Persistent Disk, File Store, Cloud SQL, Cloud DNS, Dataproc, Pub/Sub.

Azure Services AKS, Virtual Machines (VMs), Azure Functions, Virtual Networks (VNet), Azure Active Directory (AD), ARM Templates, Key Vault, Load Balancer, Application Gateway, ACR.

Operating Systems Windows, UNIX, Linux, Ubuntu, RHEL

CI&CD Tools Gitlab, Jenkins, Bamboo, Maven, ANT, Buildkite

Configuration & Containerization Tools Vagrant, Chef, Ansible, Puppet, Salt Stack, Terraform, Docker, Docker Swarm, Kubernetes

Version Control Tools Subversion (SVN), Git, GitHub, Bitbucket, GitLab

Build Tools Code Deploy, Gradle, Ant, Maven, Artifactory

Testing Tools Selenium, Junit and Cucumber

Monitoring/Logging Tools Cloud Monitoring, ELK Stack, Cloud watch, Splunk, Prometheus, Grafana

Databases Oracle, Cassandra, Mongo DB, MySQL, PostgreSQL, No SQL

Coding Languages Java, Python, C#, Golang, Ruby, PHP, PL/SQL, Shell scripting, Groovy, Perl, Bash, Java Script, NodeJS, JSON, Python

EMPLOYMENT HISTORY

Client: Boeing, Daytona Beach, FL, (Remote) Oct 2024 - Present

Role: Sr DevOps Infrastructure Engineer

Domain: Aerospace & Defense Cloud Infrastructure

Responsibilities:

• Orchestrated multi-cloud migrations from AWS to GCP, leveraging Terraform and internal provisioning tools for consistent infrastructure deployment.

• Used AWS CodePipeline and Jenkins to implement and maintain CI/CD pipelines with a 45% reduction in deployment times.

• Eliminated configuration drift and reduced environment provisioning time by 70% using Terraform and CloudFormation to develop IaC solutions.

• Integrated AI-powered predictive analytics with AWS SageMaker and GCP Vertex AI to optimize resource scaling and utilization.

• Implemented GitOps workflows using Argo CD, achieving declarative Kubernetes management and faster rollback capabilities.

• Deployed Istio service mesh to secure microservice traffic and enable observability through tracing and metrics collection.

• Established Kubecost and CloudHealth integrations to monitor cloud spend and drive cost optimization across environments.

• Standardized distributed tracing with OpenTelemetry, improving incident response times by 45%.

• Embedded DevSecOps practices by automating container image scanning using Trivy and policy enforcement pipelines.

• Orchestrated the integration of AI-driven analytics for resource management, leading to optimized utilization and improved cost-effectiveness.

• Led cloud migration efforts from AWS to GCP, managing end-to-end migration processes including building Proof of Concepts (POCs), deploying applications, and optimizing infrastructure.

• Implemented multi-cloud services, working with AWS services like EC2, S3, Lambda, CloudWatch, and CloudFront, while deploying and managing equivalent services on GCP such as GCE, Cloud Storage, Cloud Functions, and Stackdriver.

• Orchestrated CI/CD pipelines using Buildkite, deploying applications from AWS EKS to GCP GKE, leveraging containerization with Docker and optimizing continuous integration and deployment workflows.

• Authored Ansible scripts to automate license installations on Ubuntu servers, streamlining server provisioning and reducing manual intervention.

• Worked on internal provisioning tools like Juno to automate GCP project setup, including service provisioning, budget approvals, and Vault integration for secure secret management.

• Securely managing certificates in HashiCorp Vault for easy access and deployment.

• Migrated critical applications like Teamcenter and Munki from AWS to GCP, optimizing them for performance and scalability in their new environments.

• Integrated Lambda/Cloud Functions with REST APIs, message queues (SQS/PubSub), and event-driven architectures to handle real-time data processing and asynchronous task execution seamlessly.

• Integrated GCP services such as Cloud Run and Cloud Storage for application hosting and data storage, ensuring high availability and efficient scaling for applications like Munki.

• Optimized cloud environments by automating deployments to development, staging, and production using internal tools like Juno and Terraform, reducing deployment times and manual errors.

• Integrated Cloud SQL and BigQuery for backend data storage and analytics, ensuring robust and scalable data solutions for applications migrating from AWS to GCP.

Environment: AWS Services, GCP Services, CI/CD pipelines, Terraform, REST APIs, Ansible, GCP Vertex AI,

Buildkite, OpenTelemetry, AWS SageMaker, Docker, Kubernetes, DevSecOps, Jenkins, Hashicorp Vault, Ansible, MLOps.

Client: Cruise, Austin, TX, (Remote) Nov 2023 – Sep 2024

Role: Sr DevOps Engineer

Domain: Autonomous Vehicles / Automotive Technology

Responsibilities:

• Streamlined CI/CD pipelines, resulting in reduced deployment times and improved software release reliability.

• Migrated production workloads from GCP to AWS, leveraging services such as EC2, DynamoDB, and CloudFormation.

• Analyzed system performance metrics to identify bottlenecks, implementing solutions that enhanced application efficiency and user experience.

• Developed and integrated infrastructure as code, leading to more consistent and repeatable deployments across environments.

• Led end-to-end MLOps pipeline development with SageMaker, automating model training, deployment, and monitoring.

• Implemented GitOps workflows with FluxCD to standardize Kubernetes deployments and improve release consistency.

• Defined and monitored SLIs/SLOs with Grafana dashboards and Prometheus metrics, improving system reliability alignment.

• Automated Kubernetes cluster rightsizing with Karpenter and Spot Instance adoption, reducing compute costs by 25%.

• Deployed Launch Darkly for feature flag management, enabling progressive rollouts and A/B testing.

• Conducted Chaos Mesh experiments to validate failure scenarios and strengthen platform resilience.

• Integrated Trivy scans into CI/CD pipelines to proactively address container vulnerabilities.

• Involved in the design and deployment of multiple applications across the AWS ecosystem, leveraging EC2, Route53, S3, RDS, DynamoDB, VPC, SNS, SQS, and IAM to enhance high availability, fault tolerance, and auto-scaling capabilities using AWS Cloud Formation.

• Executed seamless migration of production infrastructure to AWS, utilizing a comprehensive suite of services including AWS Server Migration Service (SMS), AWS Database Migration Service, Elastic Beanstalk, CloudFormation, Redshift, DynamoDB, Code Deploy, Code Commit, and EBS, transitioning from GCP Cloud.

• Deployed FluxCD for continuous delivery to Kubernetes clusters across staging and production.

• Integrated DNS with Kubernetes (ExternalDNS) to dynamically update DNS records for ingress controllers and microservices in multi-region clusters.

• Responsible for Ansible setup for AWS and GCP environments, authoring playbooks for automated provisioning and configuration, and enhancing infrastructure as code practices.

• Developed end-to-end MLOps pipelines leveraging AWS SageMaker for model training, deployment, and lifecycle management, AWS Lambda for serverless data processing and AWS Step Functions for orchestrating machine learning workflows. This architecture streamlined the model deployment process, reducing deployment cycles by 30% and enhancing model accuracy.

• Implemented Infrastructure as Code using Terraform, achieving consistent deployments and minimizing configuration errors across environments.

Environment: AWS Services, GCP Services, Karpenter, Hashicorp Vault, JIRA, VMware, GITHUB, Docker, YAML, Grafana, SageMaker, FluxCD, Artifactory, Shell, Glue, Terraform, Gitlab CI/CD, TypeScript, MAVEN, Python, Jenkins, Google BigQuery, GKE, SDK, CLI.

Client: Entain, Hyderabad, India. Mar 2021 – June 2023

Role: Azure DevOps / Cloud Engineer

Domain: Online Gaming & Real-Time Betting Systems

Responsibilities:

• Implemented CI/CD pipelines using Azure DevOps, enhancing deployment frequency and reducing lead time for changes.

• Adopted GitOps with FluxCD to enable declarative AKS deployments and automated reconciliation.

• Implemented Aqua Security for container runtime protection and image scanning.

• Standardized observability using Azure Monitor and Application Insights for distributed tracing.

• Established Azure Policy and Blueprints to enforce compliance and governance controls.

• Integrated Event Grid with serverless workflows for automated incident remediation.

• Create CI/CD pipelines for the deployment of services and tools to the Kubernetes cluster hosted on bare metal.

• Utilized CloudFormation and Bicep templates for declarative DNS configurations to support CI/CD pipeline deployments.

• Deployment of CNF on Kubernetes clusters using Helm charts and the TCA tool.

• Create value files based on test deployments done on test clusters and elevate them to production clusters.

• Install and configure the ELK stack on the environment to ship logs from applications hosted on a cluster.

• Configured and automated the Azure DevOps Pipelines & Jenkins Pipelines/Build jobs for Continuous Integration and Deployments Dev to Production Environments.

• Designed and developed the pipelines using Databricks and automated the pipelines for the ETL processes and further maintenance of the workloads in the process.

• Creation of hooks on Bitbucket repositories in aid of the automation of Jenkins jobs.

• Configuring Azure Key Vault services for development teams for handling secrets in dev, test, and production environments using both UI and CLI in Jenkins jobs.

• Create and manage the Azure & AWS cloud infrastructure for applications from various channels in the organization using Terraform.

• Working on upgrading the Kubernetes cluster and commissioning & decommissioning nodes and pods.

Environment: Azure Services, Azure Policy, GitOps, FluxCD, Key Vault, Bitbucket, Kubernetes, AWS, Jenkins, Databricks, Azure DevOps Pipelines, ETL, ELK, Helm, Bicep, DNS, CloudFormation, CI/CD.

Client: Cotiviti, Hyderabad, India. Nov 2018 - Mar 2021

Role: Site Reliability Engineer / Cloud DevOps Engineer

Domain: Healthcare

Responsibilities:

• Built containerized microservices using Docker and Kubernetes.

• Created infrastructure automation with Terraform, Ansible, and HashiCorp Vault for secrets management.

• Developed self-service Terraform modules and Jenkins libraries to accelerate developer workflows.

• Implemented Gremlin chaos engineering to test system resilience under failure scenarios.

• Transitioned to immutable AMI deployments, improving security and consistency.

• Optimized AWS costs through EC2/RDS rightsizing and reserved instance purchasing.

• Built serverless data pipelines with Lambda, Step Functions, and Glue for real-time processing.

• Established secrets management with HashiCorp Vault and Consul.

• Created inventory in Ansible for automating the continuous deployment and wrote playbooks using YAML scripting.

• Experience with container-based deployments using Docker, working with Docker images, Docker Hub and Docker-registries and Kubernetes and (Jfrog and Artifactory).

• Developed AWS CLI script automation for EMR (end-to-end) and other AWS services and built serverless architecture using Lambda (boto3) and Step Functions.

• Experienced in leveraging Splunk for log and data analysis, enabling proactive monitoring, security threat detection, and actionable insights to support decision-making and enhance system performance.

• Dockerized Jenkins with master and slave architecture in the OpenShift platform and automated the build jobs.

• Optimized volumes and EC2 instances. Used IAM to create new accounts, roles, and groups.

Environment: AWS, GIT, Jenkins, OpenShift, Ansible, Maven, Hashicorp Vault, Docker, AWS Glue, Consul, Terraform, JIRA, WebSphere, Python, Kubernetes, Splunk, Jfrog, and TypeScript.

Client: Pennant Technology, Hyderabad, India. Jul 2017 - Nov 2018

Role: Build & Release Engineer

Domain: Banking

Responsibilities:

• Designed and maintained Git branching strategies and automated build pipelines.

• Implemented configuration management using Puppet to standardize environments.

• Standardized artifact management workflows in Artifactory to improve release traceability.

• Established immutable build and deployment practices using Maven and Git tagging.

• Developed declarative Jenkins pipelines for consistent CI/CD processes.

• Involved in periodic archiving and storage of the source code for disaster recovery.

• Used ANT and MAVEN as a build tool on Java projects for the development of build artifacts on the source code.

• Deployed Puppet, Puppet Dashboard, and Puppet DB for configuration management to existing infrastructure.

• Wrote Puppet manifests for deploying, configuring, and managing collected metrics for metric collection and monitoring. Managed Puppet infrastructure through major version upgrades.

• Worked on Java-based applications, responsible for writing business logic using Java, Maven, Spring Boot, REST web services, and web technologies.

• Designed branching strategies and build pipelines with Git and Maven

• Implemented configuration management with Puppet across 100+ servers

• Automated disaster recovery procedures and backup strategies

• Built deployment automation for Java applications on WebLogic

Environment: Subversion, GIT, Anthill Pro, Python, Java/J2EE, Spring Boot, ANT, MAVEN, JIRA, LINUX, UNIX, XML, WebLogic, MySQL, Perl Scripts, Puppet, and Shell Scripts.

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