SAADULLAH W.

Certified Kubernetes Developer, AWS Certified Solution Architect and GCP certified DevOps Engineer currently working in AI Healthcare company as a DevOps Engineer. Hands-on skills: • Linux (User management, Disk Partitions, Process Management, SElinux etc) • Kubernetes (Deployments Strategies, sevices, Ingress controller, RBAC, Taints and Toleration,Pod Anti Affinity Application healthniess probes- Liveness & Readiness etc.) • Hands-on on diff CICD tools (Self hosted Runners with GitHub, GitLab, BitBucket, Jenkins, Sonar Cloud and ArgoCD) • Have experience to build the production grade CICD pipeline on GCP using Cloud Build, Cloud Deploy with manual approval, optimization, dynamic environment creation and destruction for testing and many other features for Cloud Run or GKE with Monitoring and logging facilities. • On-Premises Kubernetes Clusters provisioning with Rancher, k3s and Hyper-V Manager. • Hands-on in managing the GPU workloads via Time-slicing, metrics exporter and scalability with adapters and plugins *Hands-on on managing and deploying open source AI tools like Vector Database (Qdrant) Argilla sever for GBs of data with high availability. • Monitoring tool’s implementation(Prometheus, Grafana,Loki, Thanos, Kiali, Elastic Search, Kibana, Fluentd and Cloud-watch) • IaC tools (Terraform and Terragrunt) implementation with GitOps methodology like with Spacelift or Terraform Cloud • Hands-on on scaling the Kubernetes cluster with Cluster Auto scalar, HPA and VPA. • Security and Encryption (Istio,App Mesh, HashiCorp Vault and SQL proxy) • Managing Micro-services secret injection via External Secret Operator (Vault and Secret Manager) • Monitoring alerts for third party services availability and Microservices deployed in Kubernetes cluster on slack channels. • Dockers & Docker Compose for local environment testing in CI process. • Thought Machine (Core banking system tool) upgradation from 3.3.10 to 3.3.11. • SMTP server deployment via CPanel from Namecheap. • Packer (Building custom cloud image via code) • Successful migration of resources deployed on AWS to Google cloud.