In this course, you will learn to deploy solutions using Google Kubernetes Engine (GKE), including building, scheduling, load balancing and monitoring workloads, service discovery, managing role-based access control (RBAC), security, and providing persistent storage for applications.
- Engineers DevOps
- Linux Administrators
- Systems design engineers
- IT Architects
- People who manage container orchestration in GCP Cloud
- Optimizing application and workload performance in GKE
- Security and troubleshooting best practices in GKE
- Using Istio for service mesh and Canary releases
- Using Anthos to manage hybrid and multi-clustercloud
- Implementing CI/CD pipelines with Jenkins, Spinnaker, and Cloud Build
- PipelineDistributed and serverless ML with Kubeflow and Knative
- Rollout strategies and advanced autoscaling in GKE
- Advanced monitoring and logging with Google Cloud Tools
- Deploy various workloads (Java, Python, ASP.NET Core, etc.)
- Cost optimization in GKE and managing multi-tenant clusters
- Basic Kubernetes knowledge (terminology, CLI usage, resources)
- Basic Linux and network administration experience
- Fundamental knowledge about Google Cloud Platform
- Experience with containers and complementary services in GCP
- GKE Best Practices
- GKE Best Practices: Security and Troubleshooting
- GKE with Istio
- Anthos
- Implementing CI/CD pipelines in GKE
- Implementing ML pipelines in GKE
- PipelineServerless in GKE
- Rollout strategies in GKE
- Advanced monitoring and logging
- Deploy diverse workloads in GKE
- Cost optimization in GKE
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