Container Workload Management and Production Operations
Google Cloud via Coursera Specialization
Overview
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Running containerized applications in production requires more than deploying a Kubernetes cluster. In Container Workload Management and Production Operations, you'll build hands-on Google Kubernetes Engine (GKE) skills for deploying, scaling, securing, monitoring, and managing containerized workloads.
You'll progress from Kubernetes and GKE fundamentals to production operations such as deployment management, workload optimization, autoscaling, monitoring, backup and restore, security hardening, and multi-tenant cluster management. You'll also explore how GKE Fleets and managed service mesh capabilities support applications distributed across multiple clusters.
By the end of this specialization, you'll be able to:
Create and manage GKE clusters and deploy containerized applications Configure and scale Kubernetes deployments using kubectl and YAML Optimize workloads for availability, performance, resource use, and cost Apply autoscaling, monitoring, backup, and recovery strategies to GKE workloads Harden GKE clusters and manage access in multi-tenant environments Manage workloads and distributed services across multiple GKE clusters
Syllabus
- Course 1: Getting Started with Google Kubernetes Engine
- Course 2: Kubernetes Engine: Qwik Start
- Course 3: GKE Autopilot: Qwik Start
- Course 4: Managing Deployments Using Kubernetes Engine
- Course 5: GKE Workload Optimization
- Course 6: Understanding and Combining GKE Autoscaling Strategies
- Course 7: Manage Scalable Workloads in GKE
- Course 8: Hardening Default GKE Cluster Configurations
- Course 9: Cloud Operations for GKE
- Course 10: Managing a GKE Multi-tenant Cluster with Namespaces
- Course 11: GKE Backup and Restore
- Course 12: Manage Multi-cluster Workloads at Scale with GKE Fleets and Teams
- Course 13: Manage and Secure Distributed Services with GKE Managed Service Mesh
Courses
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Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.
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This is a self-paced lab that takes place in the Google Cloud console. Google Kubernetes Engine provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. This hands-on lab shows you how deploy a containerized application with Kubernetes Engine.
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This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how optimization in your cluster's workloads can lead to an overall optimization of your resources and costs. It walks through a few different workload optimization strategies such as container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets.
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This is a self-paced lab that takes place in the Google Cloud console. In this lab you will explore the benefits of different Google Kubernetes Engine autoscaling strategies, like Horizontal Pod Autoscaling and Vertical Pod Autoscaling for pod-level scaling, and Cluster Autoscaler and Node Auto Provisioning for node-level scaling.
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This is a self-paced lab that takes place in the Google Cloud console. This lab explores best practices in managing and monitoring a multi-tenant cluster in order to optimize your costs.
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This is a self-paced lab that takes place in the Google Cloud console. GKE Autopilot provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. Autopilot is a new managed mode of operation for Google Kubernetes Engine (GKE) in which Google creates, sizes, and automatically scales on your behalf the physical infrastructure needed to run your application workloads. In this lab, you get hands-on practice containerizing an application and deploying it to an Autopilot cluster using Kubernetes configuration and commands.
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This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates some of the security concerns of a default GKE cluster configuration and the corresponding hardening measures to prevent multiple paths of pod escape and cluster privilege escalation
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This is a self-paced lab that takes place in the Google Cloud console. In this lab you will set up Monitoring and visualizing metrics from a Kubernetes Engine cluster
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This is a self-paced lab that takes place in the Google Cloud console. Dev Ops best practices make use of multiple deployments to manage application deployment scenarios. This lab provides practice in scaling and managing containers to accomplish common scenarios where multiple heterogeneous deployments are used.
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This is a self-paced lab that takes place in the Google Cloud console. GKE cluster backup and restore
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This is a self-paced lab that takes place in the Google Cloud console. Provision and manage infrastructure resources for different teams with GKE Enterprise's fleet team management features
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This is a self-paced lab that takes place in the Google Cloud console. Learn how to run distributed services on multiple Google Kubernetes Engine (GKE) clusters in Google Cloud using Multi Cluster Ingress and GKE Service Mesh
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Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine. This course uses lectures and hands-on labs to help you explore and deploy using Google Kubernetes Engine (GKE), GKE Fleets, Cloud Service Mesh, and Config Controller capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers.
Taught by
Google Cloud Training