DevOps Automation Project
Rakesh Kumar
Expertise in Software Development Lifecycle (SDLC),
DevOps, Continuous Integration, Continuous Deployment, Infrastructure Automation, Configuration Management and Continuous Delivery.Experience in the Installation of tools like Git,
Jenkins, Maven, Docker, Jboss, Mysql, and Tomcat in a Linux environment. Deep-level expertise in Web and memory pools and load Balancing.Expertise in the delivery, maintenance, and support of Linux systems and infrastructure.Expertise in promoting and driving system visibility to aid in the rapid detection and resolution of issues.Installing, Integrating, maintaining, and monitoring tools like Splunk, New-relic,
Zabbix,Nagios,GCP profile.Experience in creating Branching strategies,
Merging, and Tagging concepts in version control systems like GIT. Maintenance experiences of a continuous integration
build engineer, such as Jenkins CI. Good experience in containerizing applications with
Docker. Experience in Deploying Applications in Tomcat
server and Jboss. Experience in cloud Environment AWS (EC2, Route53,
AMI, VPC, ELB and Autoscaling). Experience in cloud Environment GCP (Compute Engine,
Cloud Deploy, Cloud trigger, Cloud Secret Manager, GKE, and scaling). Backup and restoration of data on Linux. Hands-on experience in Creating and Managing Users
and Groups Handled environments UAT and PROD for various
releases. Experience with Ansible Playbooks. Experience with Kubernetes.Administrating and configuring Linux servers. Working with file system management and
partitioning. Package management by using RPM and YUM. Participating in On-call support to clients and maintaining the support tickets without
escalations.Monitoring
availability and taking a holistic view of the system’s health (tools like –
site 24x7, Appdynamic, Google Monitoring SRE dashboard).Expertise in developing SRE dashboards and a deep understanding of SLI, SLO, and error Budgets.
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Posted Sep 14, 2023
Led a DevOps automation project,implementing CI/CD pipelines and IAC code, resulting in reduced deployment time by 70% and improved system stability.
