
Prasanna Venkataraman
Verified Expert in Engineering
DevOps Engineer and Developer
Chennai, Tamil Nadu, India
Toptal member since April 14, 2020
Prasanna is a DevOps, SRE, and full-stack engineer with 14+ years of experience building scalable, reliable, and secure systems. A quick learner and agile practitioner, he thrives in dynamic environments, delivering solutions aligned with industry best practices. With expertise in Kubernetes, cloud infrastructure (AWS, GCP), and monitoring systems, Prasanna's key accomplishments involve migrating services to containerized environments and developing fault-tolerant systems leveraging CNCF tools.
Portfolio
Experience
- Docker - 7 years
- Python - 7 years
- Amazon Web Services (AWS) - 7 years
- Kubernetes - 6 years
- Infrastructure as Code (IaC) - 5 years
- PostgreSQL - 5 years
- Terraform - 5 years
- Prometheus - 3 years
Preferred Environment
Amazon Web Services (AWS), Kubernetes, Go, Terraform, Google Cloud Platform (GCP), Docker, Python 3, TypeScript
The most amazing...
...thing I've set up was an infrastructure using Kubernetes that handles millions of transactions for one of the biggest consulting service companies.
Work Experience
Senior AWS Engineer
Openclaw Enterprise Services (OES)
- Architected production-grade Kubernetes infrastructure on AWS EKS using Terraform, implementing fully isolated multi-tenant workloads with Kata Containers for VM-level sandboxing, Karpenter for intelligent node autoscaling.
- Engineered a tiered isolation strategy by deploying gVisor-based sandboxing, reducing infrastructure costs significantly while maintaining strong workload isolation, and reserving Kata Containers and dedicated VMs for production.
- Configured OpenClaw for enterprise deployment with security hardening (RBAC, secrets management, network isolation) and metered billing integration, enabling onboarding of enterprise customers with compliance and usage-tracking requirements.
- Instrumented observability for LLM and AI agent workflows, monitoring response accuracy and token consumption across agent interactions. Part of the model selection decisions that reduced token spend while maintaining output quality.
AWS DevOps
Backsie Inc.
- Architected and implemented Kubernetes-based container orchestration on AWS infrastructure (AWS EKS) for an AI-driven emotional journaling and therapy collaboration platform, ensuring secure and ethical handling of sensitive mental health data.
- Built end-to-end CI/CD pipelines to automate the deployment workflows for back-end and mobile applications for both Apple App Store and Google Play Store. Streamlined release processes to reduce release cycle times.
- Integrated LangChain and LangSmith into the platform's AI stack to track large language model (LLM) performance metrics, token usage, and response quality, and surfaced key insights through a centralized monitoring dashboard for ongoing optimization.
- Configured secure networking and access controls for cloud-hosted LLM services and vector database integrations, enabling the platform's AI features while maintaining strict data privacy boundaries.
Senior DevOps Engineer
Politexts LLC
- Led the migration of a 4.5 TB PostgreSQL database from DigitalOcean to AWS Aurora PostgreSQL.
- Designed and implemented the production environment on AWS EKS (Kubernetes), incorporating best practices across the stack. GitHub Actions was used for CI/CD, Terraform for Infrastructure as Code (IaC), Prometheus and Grafana for monitoring, and Datadog for centralized logging.
- Optimized database connectivity by configuring PgBouncer in transaction pooling mode and setting up Amazon RDS Proxy to efficiently manage connection pooling.
- Engineered a high-throughput message processing system capable of handling 2,000 messages per second using Redis and background worker processes. Implemented HPA in Kubernetes to ensure the system dynamically scales based on load.
AI & Infrastructure Engineer
HireSRE AI
- Built an on-call infrastructure support platform leveraging GenAI models, including Llama and GPT, and implemented a retrieval-augmented generation (RAG) system using PineconeDB to enhance information retrieval and response accuracy.
- Configured and deployed GenAI models to support on-premise AI setups using Llama, ensuring secure and efficient integration within client environments.
- Developed AI agents using LangChain and LangGraph to proactively monitor infrastructure, enabling automated issue detection and first-level resolutions.
- Implemented AgenticOps to monitor LLM models, tracking token usage and call costs, optimizing model performance and cost efficiency for production-grade applications.
Lead DevOps Engineer
Pi42 Inc
- Migrated services from a virtual machine-based system to Kubernetes-based infrastructure, achieving improved scalability, operational efficiency, and reduced maintenance overhead.
- Developed and deployed a dynamic rate-limiting system to throttle requests based on user plans, enhancing user experience while maintaining system reliability and fairness.
- Managed infrastructure supporting $100,000 worth of transactions daily, ensuring high availability, performance, and compliance with operational standards.
- Engineered a resilient, fault-tolerant system in Google Cloud using CNCF tools like Jaeger and Istio, delivering robust observability and service mesh capabilities for efficient issue diagnosis and traffic management.
Lead DevOps Engineer
Dacio AI
- Designed and implemented infrastructure for real-time video streaming platform using Cloudflare Streams, R2, Amazon Kinesis, and Amazon S3, ensuring seamless playback and high availability.
- Architected and deployed a scalable and cost-optimized cloud infrastructure using the AWS Well-Architected Framework, achieving measurable cost reductions and improved performance.
- Established and maintained CI/CD pipelines for Kubernetes-based infrastructure leveraging GitHub Actions, ensuring zero downtime deployments and streamlined release cycles.
- Implemented and optimized monitoring and centralized logging solutions with Prometheus, Grafana, and the ELK stack, providing actionable insights and reducing issue resolution time by 40%.
Lead DevOps Engineer
nDimensional Inc
- Contributed to the migration of the whole infrastructure from VM-based to Kubernetes with support for zero-downtime deployment, option to roll back deployments, and canary-based deployments. Revamped the entire CI/CD process using Jenkins.
- Managed three DevOps engineers following the practice of Agile-based methodologies along with support for managing the production system. Set up a production-ready system with Prometheus, Papertrail, Jaeger, and Istio.
- Did capacity and AWS cost estimation for a big data application with workloads for real-time data of 3 GB/min and storage of 2 TB in Cassandra. Managed distributed systems, including Kafka, Cassandra, Spark, Flink, and Akka Clusters in Kubernetes.
Architect | Lead DevOps Engineer
Francium Technologies
- Set up a multi-cloud infrastructure leveraging services from AWS, GCP including orchestrating 30+ microservices using Kubernetes and creating CD pipelines which significantly reduced the time to put services to production.
- Established a proper monitoring-and-tracing system and scaled the product to handle 50x load with half the infrastructure cost. Set up the fitness function to track cost as one of the metrics for infrastructure (AWS and GCP).
- Architected and led the company in high-performance DevOps culture by following principles of XP/lean for DevOps and automating the entire infrastructure using Terraform.
Technical Lead
ThoughtWorks
- Worked as part of multiple engagements ranging from startups to massive enterprises and led many projects involving various technology stacks. Followed TDD and agile (XP/lean) methodologies in all teams and tech stacks.
- Set up an authentication system for a popular bank in Spain and handled many requests. Chose the tools to track performance and utilize the infrastructure efficiently. Used Kubernetes, Go, Prometheus, Redis, and Elasticsearch.
- Worked at a client's location (UK) to refactor their core pricing engine. Followed a strangulation approach and, in the process, improved their CI/CD pipelines.
Senior Software Engineer
Pramati Technologies
- Built a type of warehouse management software for one of the enterprise companies and was responsible for developing the back-end system using Java, Spring, and JPA technology stack.
- Developed a high-performance, real-time bidding engine which handles millions of requests in Scala and Akka framework.
- Set up virtual machines using Ansible and Bash scripts and used Jenkins for continuous integration and deployment.
Application Developer
Oracle
- Contributed to the Oracle E-Business Suite development and handled the EU region's payroll system.
- Implemented performance fine-tuning for a Java virtual machine (JVM) and analyzed and optimized SQL query performance.
- Handled multiple clients for the EU region and was in charge of a complete module.
Experience
Authentication System for Openbank SA
CI/CD Setup for Monolith to Microservice Migration
https://nd.comInfrastructure Setup for the Consulting Group
I analyzed and suggested pros and cons for the entire DevOps stack, implemented the right tool for each and effectively communicated with developers to set up seamless auto-deployment and one-click deployment for the apps.
Took sessions with the development team on the proper usage of tools for logging and monitoring.
Education
Bachelor's Degree in Computer Science
Thiagarajar College of Engineering - Madurai, India
Certifications
Certified Kubernetes Security Specialist
Cloud Native Computing Foundation
Certified Kubernetes Administrator
The Cloud Native Computing Foundation
AWS Certified Solutions Architect — Associate
Amazon Web Services (AWS)
Skills
Libraries/APIs
Amazon API, Vue 2, Node.js, Vue, React, OpenAI API
Tools
Terraform, IntelliJ IDEA, Ansible, Helm, Google Kubernetes Engine (GKE), Amazon EKS, Amazon CloudFront CDN, Logging, GitHub, NGINX, AWS CloudFormation, Amazon Elastic Container Registry (ECR), Shell, Amazon ElastiCache, AWS IAM, AWS CloudTrail, Amazon Cognito, Amazon Virtual Private Cloud (VPC), Grafana, Amazon Elastic Container Service (ECS), AWS CodeBuild, ELK (Elastic Stack), GitLab CI/CD, Docker Swarm, Confluence, AWS Cloud Development Kit (CDK), AWS Batch, n8n, Vim Text Editor, Jenkins, Flink, Mesos, CircleCI, Traefik, Papertrail, Kubernetes Operators, Amazon CloudWatch, Amazon QuickSight
Languages
Java, Python, Bash, Go, Scala, Python 3, TypeScript, JavaScript, PHP, Ruby
Frameworks
Ruby on Rails (RoR), Next.js, Spring 5, JPA, Laravel, Express.js, Spring, Spark, Akka, Apache Spark, gRPC
Paradigms
Agile Software Development, Test-driven Development (TDD), Continuous Deployment, Continuous Integration (CI), DevOps, Microservices, Automation, Functional Programming, HIPAA Compliance
Platforms
Docker, Kubernetes, Amazon Web Services (AWS), Google Cloud Platform (GCP), Linux, Apache Kafka, Amazon EC2, Vercel, Heroku, Dokku, DigitalOcean, AWS Lambda, Oracle Database, Azure
Storage
PostgreSQL, Redis, Datadog, Amazon S3 (AWS S3), Google Cloud, Elasticsearch, MySQL, Amazon Aurora, MongoDB, Amazon DynamoDB
Other
Prometheus, Infrastructure as Code (IaC), Shell Scripting, CI/CD Pipelines, API Testing, AWS Cloud Architecture, AWS DevOps, Networking, Cloud Architecture, Cost Control, Amazon RDS, AWS Certified Solution Architect, Cloud Services, Scalability, Load Balancers, Cost Reduction & Optimization (Cost-down), Cloud Infrastructure, Cloud, Containerization, Orchestration, Scripting Languages, Cloud Migration, GitHub Actions, Full-stack Development, Platform Engineering, Architecture, Argo CD, GitOps, Certified Kubernetes Administrator (CKA), WebSockets, Infrastructure, Infrastructure Architecture, Apache Cassandra, Monitoring, Kubernetes Operations (kOps), Immutable Infrastructure, Cloudflare, AWS CodePipeline, Security, AWS VPN, FastAPI, Site Reliability Engineering (SRE), Amazon Bedrock, Web Security, Pulumi, Monorepos, Large Language Models (LLMs), LangChain, AI Agents, Vector Databases, Large Language Model Operations (LLMOps)
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
Share your needs
Choose your talent
Start your risk-free talent trial
Top talent is in high demand.
Start hiring