Cloud DevOps Engineer AWS, Azure, Kubernetes expert

Laharika Kanchanapalli

New Jersey, USA 551-***-**** **********@*****.*** LinkedIn

SUMMARY

• Experienced Cloud DevOps Engineer with 4+ years of expertise in designing, deploying, and managing scalable cloud infrastructure on AWS and Microsoft Azure for enterprise and financial services applications.

• Skilled in Infrastructure as Code (Terraform, CloudFormation, ARM templates) to provision, manage, and maintain consistent multi- environment deployments across hybrid cloud platforms.

• Strong hands-on experience in containerization and orchestration using Docker, Kubernetes (EKS/AKS), and Helm, supporting microservices and AI/ML workloads in production.

• Proficient in building and maintaining CI/CD pipelines using Jenkins, Azure DevOps, and GitHub Actions, automating build, test, deployment, and release processes for cloud-native and legacy applications.

• Expertise in cloud security and governance, including IAM, RBAC, Key Vault, secrets management, and network isolation, ensuring compliance with enterprise and regulatory standards.

• Experienced in implementing centralized monitoring and logging using CloudWatch, Azure Monitor, Application Insights, ELK Stack, Prometheus, and Grafana, enabling proactive performance management and incident resolution.

• Adept at hybrid cloud architecture design and migration, including secure network design, high availability, disaster recovery planning, and cost optimization for enterprise workloads.

• Collaborative professional with experience working closely with development, security, and business teams to deliver highly available, reliable, and optimized cloud solutions aligned with organizational objectives. SKILLS

Cloud Platforms: AWS (EC2, VPC, S3, RDS, CloudWatch, IAM, Lambda, EKS), Microsoft Azure (VMs, VNets, Load Balancer, AKS, Azure DevOps, Key Vault, Storage Accounts)

Containers & Orchestration: Docker, Kubernetes (EKS, AKS), Helm, Container Security Policies CI/CD & DevOps Tools: Jenkins, Azure DevOps Pipelines, GitHub Actions, GitLab CI/CD, Artifactory, Maven, Gradle Infrastructure as Code: Terraform, AWS CloudFormation, Azure Resource Manager (ARM) Templates Monitoring & Logging: AWS CloudWatch, Azure Monitor, Application Insights, ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, Grafana

Configuration & Scripting: Bash, Python, PowerShell, YAML, JSON Security & Compliance: IAM, RBAC, KMS, Azure Key Vault, Secrets Management, SSL/TLS, Vulnerability Scanning, Security Policies Version Control:Git, GitHub, GitLab, Bitbucket

Databases & Storage: Amazon RDS (MySQL, PostgreSQL), DynamoDB, Azure SQL Database, Blob Storage, S3 Buckets Methodologies: Agile, Scrum, DevOps, CI/CD, SDLC, Incident Management, Change Management WORK EXPERIENCE

Prudential Financial Aug 2024 – Present

Cloud DevOps Engineer New Jersey, USA

• Designed and implemented a standardized Azure landing zone using Terraform and ARM templates, creating isolated dev, QA, and production subscriptions with hub-and-spoke networking that met SOC2 and internal risk governance standards.

• Provisioned and managed Azure infrastructure including Virtual Networks, private subnets, NSGs, Azure Load Balancer, VM Scale Sets, and Private Endpoints, supporting secure deployment of AI-enabled insurance and financial applications.

• Developed reusable Terraform modules for AKS, networking, monitoring, and identity, reducing environment provisioning time from multiple days to under one hour and improving infrastructure consistency.

• Built and maintained CI/CD pipelines in Azure DevOps for .NET and containerized services, automating builds, testing, container image creation, and deployments to AKS, reducing manual release effort by approximately 60%.

• Deployed and operated Azure Kubernetes Service (AKS) clusters with separate system and application node pools, autoscaling, and resource quotas to handle peak workloads for policy processing and AI-driven analytics services.

• Supported deployment of AI/ML inference services on AKS by enabling GPU-enabled node pools and optimizing container resource allocation, ensuring reliable and scalable model inference for fraud detection and risk scoring use cases.

• Integrated Azure Key Vault with AKS using the CSI driver to securely manage application secrets, model credentials, and certificates, eliminating hardcoded values and meeting internal audit requirements.

• Implemented controlled release strategies using Azure DevOps release pipelines and AKS rolling updates, enabling frequent updates to both application and AI inference services with near-zero production downtime.

• Established centralized monitoring using Azure Monitor, Log Analytics, and Application Insights, tracking application latency, pod health, and AI service response times, reducing incident detection time by about 40%.

• Optimized infrastructure and AI workload costs using Azure Cost Management, right-sizing VM SKUs, AKS node pools, and GPU usage, contributing to an estimated 20% reduction in monthly cloud spend. Capgemini Jul 2020 – Jun 2023

Cloud Engineer Hyderabad, India

• Migrated enterprise applications from on-premise to AWS, deploying EC2 instances behind Application Load Balancers with Auto Scaling Groups, increasing uptime from ~97% to 99.9% under fluctuating traffic conditions.

• Designed secure cloud networking on AWS using VPCs, public/private subnets, route tables, NAT gateways, and Internet Gateways, ensuring backend services were isolated while enabling controlled outbound traffic.

• Established hybrid application hosting on Azure, provisioning Virtual Machines, Virtual Networks, Network Security Groups, and Azure Load Balancer, supporting regional failover and disaster recovery testing.

• Developed reusable Terraform modules for compute, networking, and storage across AWS and Azure, enabling consistent environment deployment and cutting infrastructure provisioning time by over 70%, accelerating development and testing cycles.

• Containerized legacy Java and Python applications with Docker, producing standardized images that simplified deployments across development, QA, and production environments.

• Built automated CI/CD pipelines using Jenkins (AWS workloads) and Azure DevOps Pipelines (Azure workloads) to manage build, artifact versioning, approvals, and deployments, reducing manual release effort by ~60%.

• Managed access and permissions using AWS IAM roles/policies and Azure Active Directory, enforcing least-privilege access for developers, CI/CD pipelines, and service accounts.

• Implemented centralized monitoring with AWS CloudWatch metrics, alarms, logs and Azure Monitor, proactively identifying CPU, memory, disk, and application health issues, reducing incident response time by ~40%.

• Automated operational tasks including AMI creation, log rotation, backup validation, and instance health checks using Bash and Python scripts, improving system reliability and operational efficiency.

• Conducted post-migration performance optimization using CloudWatch and Azure Monitor insights, identifying and resolving scaling, storage throughput, and load-balancing bottlenecks, stabilizing production workloads. EDUCATION

Master of Science in Computer and Information System Rowan University, Glassboro, New Jersey, USA

Bachelor of Science in Computer Science

Osmania University, Hyderabad, India

CERTIFICATIONS

• AWS Solution Architect

Contact this candidate