Akash S

DevOps Engineer

Adobe • Full time

Aug 2018 - Nov 2025 • 7 yrs 3 mos

Worked with a US-based client to lead engineering efforts focused on delivering automated, scalable, and reliable infrastructure and application deployments. Led an engineering team to design and implement DevOps best practices, improving deployment speed, reliability, and operational efficiency. Automated infrastructure provisioning and management for high-performance, cloud-based environments, reducing manual configuration and improving consistency. Deployed and managed applications on web servers and Kubernetes, ensuring scalability, fault tolerance, and high availability. Implemented monitoring, logging, and observability solutions to enable proactive incident detection, faster troubleshooting, and detailed post-mortem analysis. Managed SLOs, SLIs, SLAs, and error budgets, improving system reliability while reducing operational overhead and manual toil. Supported global high-availability deployments and provided 24×7 operational support for applications and infrastructure. Enabled real-time data processing through fault-tolerant messaging systems, ensuring reliable and scalable data workflows. Collaborated closely with Product, Development, QA, and Operations teams to meet performance, security, cost optimization, and maintainability standards.

DevOps and SRE Engineer

Trustonic • Full time

Feb 2014 - Aug 2018 • 4 yrs 6 mos

Worked with a European client to design, automate, and manage scalable cloud infrastructure and DevOps processes. Managed Infrastructure as Code (IaC) using Terraform across multiple environments (Dev, QA, UAT, Production), supporting 50+ production servers and Kubernetes clusters. Led production release planning and implemented zero-downtime deployment strategies, reducing deployment downtime by ~40% through automated CI/CD pipelines using Jenkins, Maven, Git, and Bitbucket. Implemented end-to-end monitoring, logging, and alerting for 100+ services using Prometheus, Grafana, exporters, and logging agents, enabling proactive incident detection and faster troubleshooting. Managed database environments, including performance tuning, backups, patching, and automation to ensure high availability and reliability. Deployed and maintained containerized applications using Docker and Kubernetes, delivering scalable and fault-tolerant infrastructure. Optimized AWS and GCP cloud environments for cost efficiency, performance, and security, while automating operational tasks through shell scripting. Reduced MTTR from ~2 hours to under 30 minutes by improving observability, alerting, and incident response processes, significantly enhancing system reliability and operational efficiency.