Personal details

VAIBHAV T. - Remote DevOps engineer

VAIBHAV T.

Timezone: Pacific Time (US & Canada) (UTC-7)

Summary

Skill Set:
Programming/Scripting Languages: Ruby, Shell Scripting
Public Cloud Applications: AWS, GCP
Container Orchestration: Kubernetes(Kops, GKE, EKS), AWS ECS, Docker Swarm
Operating Systems: Linux ( Ubuntu, Centos )
System Monitoring: Nagios, Sensu, Node-Exporter, Graphite, Grafana, Datadog, Dynatrace, PagerDuty, VictorOps
Logging: Elasticsearch-Filebeat-Kibana (EFK), Cloudwatch, Stackdriver
Container Monitoring: Prometheus (Thanos), Kube-state-metrics, Grafana, Alertmanager, Datadog
Configuration Management: Chef ( Hosted HA and OpsWorks), Terraform, Ansible
Continuous Integration: TravisCI, GitlabCI, Jenkins, SemaphoreCI, Teamcity
Continuous Delivery: Spinnaker, ArgoCD

Fight On! ✌🏻

Work Experience

Senior DevOps Engineer
Tigera | Nov 2019 - Present
Azure
Elasticsearch
Google Cloud Platform
Kubernetes
Grafana
Prometheus
CI/CD
Gitops
Argo CD
- Managing GKE, AKS, and EKS infrastructure for Calico Cloud (Calico Enterprise SaaS Offering) - Designed and implemented pipelines for automated provisioning and de-provisioning for ephemeral Kubernetes clusters required for product trials, evaluations and internal/external training workshops. - Architected complex monitoring and logging infrastructure for multi-cluster GKE infra using Prometheus clustered with Thanos and EFK. - Architected GitOps CI/CD pipelines for Kubernetes workloads using ArgoCD and SemaphoreCI. - Managing rollouts for 6000+ ArgoCD applications across 700+ Kubernetes clusters - Awarded Aim High and Rockstar award for 3 quarters in FY2021 - Participation in 24x7 On-call rotation
DevOps Engineer
Scalefactor | Jul 2019 - Nov 2019
Jenkins
Kubernetes
Prometheus
- Managing AWS infrastructure using Terraform - Leading Containerization initiatives in both application deployment and QA - Leading app migration from AWS Elasticbeanstalk to Kubernetes (KOPS) - Managing Jenkins Blue-Ocean CI/CD pipelines - APM and Infrastructure monitoring using Datadog - Leveraging Datadog for collecting infrastructure and application logs