Google Cloud Training: GCP Essentials

https://google.qwiklabs.com/quests/23

A Tour of Qwiklabs and the Google Cloud Platform

A GCP Project is an organizing entity for your Google Cloud resources. It often contains resources and services e.g. a pool of virtual machines, a set of databases, and a network that connects them with one another. Projects also contain settings and permissions, which specify security rules and who has access to what resources.

• More information on all GCP services: https://cloud.google.com/docs/overview/cloud-platform-services#top_of_page
• API Design Guide: https://cloud.google.com/apis/design/ - used internally by Google and published to help everyone
• APIs Explorer: https://developers.google.com/apis-explorer/#p/ - browse all APIs easily

Creating a Virtual Machine

Activate Google Cloud Shell

Google Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Google Cloud Shell provides command-line access to your GCP resources. See: https://cloud.google.com/sdk/gcloud

Understanding Regions and Zones

A region is a specific geographical location where you can run your resources. Each region has one or more zones. Resources that live in a zone are referred to as zonal resources. Virtual machine instances and persistent disks live in a zone. To attach a persistent disk to a virtual machine instance, both resources must be in the same zone. Similarly, if you want to assign a static IP address to an instance, the instance must be in the same region as the static IP. See: https://cloud.google.com/compute/docs/regions-zones/

SSH

See: https://cloud.google.com/compute/docs/instances/connecting-to-instance

1. Create new configuration for authentication: gcloud config configurations create qwiklabs-gcp-8fa25fcdb0d890b7
2. Initialise configuration: gcloud init and choose 1 to reinitialize
3. SSH using gcloud compute ssh gcelab2 --zone us-central1-c

Create a VM

• gcloud compute instances create gcelab2 --machine-type n1-standard-2 --zone us-central1-c
• gcloud compute instances create --help
• gcloud config set compute/zone - set default zone to save entering each time
• gcloud config set compute/region - set default region

Getting Started with Cloud Shell & gcloud

• List configurations: gcloud config list
• List of all possible configurations: gcloud config list --all
• Make a bucket: gsutil mb gs://unique-name-hippo
• List buckets (etc): gsutil ls
• Copy a file to a bucket: gsutil cp test.dat gs://unique-name-hippo

Kubernetes Engine: Qwik Start

The Google Kubernetes Engine (GKE) environment consists of multiple machines (specifically Google Compute Engine instances) grouped together to form a container cluster.

• https://cloud.google.com/container-registry/ - google container registry
• https://console.cloud.google.com/gcr/images/google-samples/GLOBAL - samples inc hello-app

A cluster consists of at least one cluster master machine and multiple worker machines called nodes.

• Create a cluster: gcloud container clusters create [CLUSTER-NAME]
• Get credentials for the cluster: gcloud container clusters get-credentials [CLUSTER-NAME]

The Deployment object is used for deploying stateless applications like web servers.

• Creates a new Deployment hello-server from the hello-app container image: kubectl run hello-server --image=gcr.io/google-samples/hello-app:1.0 --port 8080
• Inspect a deployment: kubectl get deployment hello-server

The Service object define rules and load balancing for accessing your application from the Internet

• creates a Service to expose the application to external traffic: kubectl expose deployment hello-server --type="LoadBalancer" (creates a Compute Engine load balancer for the container)
• Inspect a service: kubectl get service hello-server
• Clean up: gcloud container clusters delete [CLUSTER-NAME]

Set Up Network and HTTP Load Balancers

• Network load balancer (L3) see: https://cloud.google.com/compute/docs/load-balancing/network/
• HTTP load balancer (L7) see: https://cloud.google.com/compute/docs/load-balancing/http/

First need to create a cluster of machines. This can be achieve using instance templates.

• Create a startup.sh script to install nginx and alter the default index.html to display the hostname
• Create an instance template: gcloud compute instance-templates create nginx-template --metadata-from-file startup-script=startup.sh
• Create a target pool: gcloud compute target-pools create nginx-pool
• Create a managed instance group using the instance template:

gcloud compute instance-groups managed create nginx-group \
         --base-instance-name nginx \
         --size 2 \
         --template nginx-template \
         --target-pool nginx-pool

• Configure a firewall to access the machines on port 80:

Network Load Balancer

Allows load balancing based on IP protocol data e.g. address, port, protocol type. Additional options at packet level available which isn't available for HTTP load balancing.

gcloud compute forwarding-rules create nginx-lb \
         --region us-central1 \
         --ports=80 \
         --target-pool nginx-pool

• List the forwarding rules to see the LB IP address: gcloud compute forwarding-rules list

HTTP Load Balancer

Allows load balancing based on URL routes. Requests are always routed the the instance closest to the user.

• Create a health check: gcloud compute http-health-checks create http-basic-check to verify instances are responding to HTTP traffic
• Define an HTTP service and map a port name to the correct port for the instance group: gcloud compute instance-groups managed set-named-ports nginx-group --named-ports http:80
• Create a backend service and add the instance group to the backend service
• Create a URL map to map all incoming requests to all the instances
• Create an HTTP proxy to route requests to the URL map
• Create a global forwarding rule to route incoming requests to the proxy