In this course, "Architecting with Google Kubernetes Engine: Workloads," you learn about performing Kubernetes operations; creating and managing deployments; the tools of GKE networking; and how to give your Kubernetes workloads persistent storage.
이 강좌는 Architecting with Google Kubernetes Engine 특화 과정의 일부입니다.
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배울 내용
Understand the role of the kubectl command
Create and use deployments, and create run jobs and cron jobs
Create services and use load balancers to expose services to external clients
Understand and work with different Kubernetes storage abstractions
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강의 계획표 - 이 강좌에서 배울 내용
Course Introduction
In this module, you'll become familiar with the structure and layout of the course.
Kubernetes Operations
In this module you will learn about the kubectl command, which is the command line utility used to interact with and manage the resources inside Kubernetes clusters. You'll learn how to connect it to Google Kubernetes Engine clusters, and use it to create, inspect, interact and delete Pods and other objects within Kubernetes clusters. You'll also use kubectl to view a Pod’s console output, and sign in interactively to a Pod.
Deployments, Jobs, and Scaling
GKE works with containerized applications: in other words, applications packaged into hardware-independent, isolated user-space instances. In GKE and Kubernetes, these packaged applications are collectively called workloads. In this module you will learn about Deployments and Jobs, two of the main types of workload. You will also learn about the mechanisms that are used to scale the GKE clusters where you run your applications. You'll learn to control on which Nodes Pods may and may not run. You'll also explore ways to get software into your cluster.
Google Kubernetes Engine (GKE) Networking
In this module, you’ll learn how to create Services to expose applications running within Pods, which allows them to communicate with the outside world. You'll also learn how to create Ingress resources for HTTP or HTTPS load balancing. You'll also learn about GKE's container-native load balancing, which allows you to directly configure Pods as network endpoints with Google Cloud Load Balancing.
Persistent Data and Storage
In this module you’ll learn about the different types of Kubernetes storage abstractions. You’ll learn about StatefulSets and how to use them to manage ordered deployments of Pods and storage. You’ll also learn how ConfigMaps can save you time during application deployment by decoupling configuration artifacts from container definitions. Finally, you’ll learn how to keep sensitive information safer from accidental exposure using Kubernetes Secrets.
검토
- 5 stars79.55%
- 4 stars16.22%
- 3 stars2.67%
- 2 stars0.69%
- 1 star0.86%
ARCHITECTING WITH GOOGLE KUBERNETES ENGINE: WORKLOADS의 최상위 리뷰
Some of the quiz and labs are pretty challenging which could really test my understanding on K8s!
The course is pretty good, but it should really be split into 3 separate weeks, one for each module.
Extremely informative and inclusive! Ample hands-on lab work that really drives the concepts home.
Some topics results difficult a lot to understand because instructors repeat lot of times the name of the concepts that are trying to explain
Architecting with Google Kubernetes Engine 특화 과정 정보
The Architecting with Google Kubernetes Engine specialization will teach you how to implement solutions using Google Kubernetes Engine, or GKE, including building, scheduling, load balancing, and monitoring workloads, as well as providing for discovery of services, managing role-based access control and security, and providing persistent storage to these applications.

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