Managed Kubernetes GKE Advanced using GCP

Module 1: GKE Best Practices
– Optimize GKE to run your application
– Application optimization for GKE
– GKE Workload Optimization
– Using Kubernetes Engine to Deploy Apps with Regional Persistent Disks
– NGINX Ingress Controller on Google Kubernetes Engine
– Deploy the NGINX Ingress Controller on Google Kubernetes Engine.
– Distributed Load Testing Using Kubernetes

Module 2: GKE Best Practices: Security and Troubleshooting
– Running a MongoDB Database in Kubernetes with StatefulSets
– Deploy a Web App on GKE with HTTPS Redirect using Lets Encrypt
– Troubleshooting Workloads on GKE for Site Reliability Engineers
– Debugging Apps on Google Kubernetes Engine
– Deploying Memcached on Kubernetes Engine
– Best practices for upgrading clusters
– Virtual machines in GKE
– Running game servers in Google Kubernetes Engine
– Deploy Cloud Vision API from a Kubernetes Cluster

Module 3: GKE with Istio
– Hello Istio
– Implementing Canary Releases
– Deploy ASP.NET Core App to GKE with Istio

Module 4: Anthos
– Migrate for Anthos: Qwik Start
– Migrate for Anthos: Windows
– Hybrid Cloud Multi-Cluster with Anthos
– Multiple VPC Networks
– Installing Anthos Service Mesh on Google Kubernetes Engine
– Managing Hybrid Clusters using Kubernetes Engine

Module 5: Implementing CI/CD pipelines in GKE (jenkins/spinakker)
– Continuous Delivery Pipelines with Spinnaker and Kubernetes Engine
– Jenkins Multi-branch Pipeline on GKE
– Continuous deployment to Google Kubernetes Engine (GKE) with Cloud Build
– Using a NAT Gateway with Kubernetes Engine
– Deploy Kubernetes Load Balancer Service with Terraform

Module 6: Implementing ML pipelines in GKE
– Distributed Multi-worker TensorFlow Training on Kubernetes
– From Notebook to Kubeflow Pipelines with HP Tuning: A Data Science Journey

Module 7: Implementing serverless pipelines in GKE
– Using Knative to deploy serverless applications to Kubernetes

Module 8: Implementation rollout strategies in GKE
– Autoscaling with GKE: Overview and pods
– Autoscaling with GKE: Clusters and nodes
– Understanding and Combining GKE Autoscaling Strategies

Module 9: Advanced Monitoring and Logging
– Cloud Logging on Kubernetes Engine
– Cloud Operations for GKE
– Using Cloud Trace on Kubernetes Engine
– Using Cloud Trace on Kubernetes Engine
– Using OpenTSDB to Monitor Time-Series Data on Cloud Platform

Module 10: Deploying mixed types workloads on GKE
– Deploy, Scale, and Update Your Website on Google Kubernetes Engine
– Deploying the Application into Kubernetes Engine – Java
– Deploy ASP.NET Core App to Kubernetes Engine
– Deploying the Application into Kubernetes Engine – Python
– Connect to Cloud SQL from an Application in Kubernetes Engine
– Running a MongoDB Database in Kubernetes with StatefulSets
– Confluent: Running Apache Kafka on GKE
– Deploy a Spring Boot Java app to Kubernetes on Google
– Deploy a Micronaut application containerized with Jib to Google

Module 11: COST optimization in GKE
– Understanding your GKE Costs
– Monitoring your GKE costs
– Managing a GKE Multi-tenant Cluster with Namespaces
– Exploring Cost-optimization for GKE Virtual Machines