Manish Reddy

About Manish Reddy

Experienced DevOps Engineer working on a high-impact project at IBM, leveraging a diverse set of cloud and DevOps technologies to drive automation, scalability, and security. Proficient in IBM Cloud, Azure, GCP, Yandex Cloud, and G4D2 Cloud, with expertise in OpenShift, Tekton Pipelines, and GitOps for container orchestration and CI/CD automation. Skilled in Azure DevOps Boards, Azure Pipelines, Terraform, and Ansible, ensuring seamless infrastructure deployment and management. Strong background in monitoring and logging using Grafana, Kibana, Prometheus, and Fluentd, and implementing security best practices with OWASP. Experienced in Java, TypeScript, and Go, with hands-on API testing using Postman and Newman. Passionate about optimizing workflows, enhancing system reliability, and delivering innovative cloud solutions.

Experience

1. Cloud Devops Engineer

   IBM

   May 2021 — Present

   Designed and implemented CI/CD pipelines using Jenkins and Google Cloud Build, reducing deploymenttime.• Managed GCP resources and services, including Compute Engine, GKE, and Cloud Functions, optimizing performance and cost.• Migrated legacy applications to Kubernetes on GKE, reducing infrastructure costs and increasing deployment efficiency through containerization and orchestration.• Automated infrastructure provisioning and management using Terraform, leading to reduction in manual configuration errors.• Worked on hybrid cloud migration projects, integrating on-premises environments with cloud platforms, ensuring smooth data flow and minimal downtime.• Collaborated with development teams to establish best practices in version control, code reviews, and release management.• Configured the applications in ArgoCD and setup ArgoCD to auto sync Kubernetes YAML file to deploy to GKE cluster.• Migrated legacy Jenkins pipelines to CircleCI, improving ease of use, speed, and maintainability of build and deployment workflows.• Performed GKE cluster upgrades and patches with minimal disruption, ensuring continuous availability and compliance with the latest Kubernetes features and security updates.• Integrated GCP Pub/Sub and Cloud Functions into event-driven architectures, automating processes and scaling applications dynamically based on traffic demand.• Utilized GCP Artifact Registry and Container Registry to store, manage, and deploy Docker images and other artifacts, streamlining CI/CD pipelines for cloud-native applications.• Managed GCP project organization and billing using Cloud Billing and GCP’s resource hierarchy, ensuring optimal resource allocation and cost governance.• Managed Kubernetes clusters on GCP Kubernetes Engine, optimizing resource utilization and scaling applications based on demand.