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Contenedores en la nube
Bienvenida
Introducci贸n a contenedores
Introducci贸n a Docker
Trabajando con contenedores
Introducci贸n a Kubernetes y Google Kubernetes Engine
Conceptos clave de Kubernetes: el Pod
Conceptos clave de Kubernetes: despliegue y servicios
Kubernetes Engine en acci贸n: Online Boutique
Introducci贸n al c贸mputo h铆brido y multi-nube con Anthos
Arquitectura de un despliegue h铆brido y multi-nube
Aplicaciones en la nube
Introducci贸n a la malla de servicios
Instalaci贸n de la malla de servicios
Beneficios de la malla de servicios
Introducci贸n a Istio Ingress
Laboratorio Multi-Cloud
Malla de servicios en acci贸n
Malla de servicios en acci贸n - monitoreo y servicios de tracing
Conclusiones
Conclusiones
Proyecto: Clon de Google Photos (Parte 3 de 4)
Continua con tu proyecto de Google Cloud
Despliegue de la aplicaci贸n web
Working in a multicloud environment can be daunting. Not only does it mean using multiple cloud services, but also ensuring their interoperability. In this lab, we will learn how to manage infrastructures using Google Cloud Platform (GCP) and Amazon Web Services (AWS). Let's see how to start provisioning, configuring and visualizing our applications in a multicloud environment.
To conduct the lab, you need to have:
We start by logging into the GCP console(console.cloud.google.com
) using the provided credentials. It is important to choose the right project using gcloud config set project
. This ensures that we work in the right environment.
gcloud config set project <YOUR_PROJECT_ID>
Next, we configure the environment variables that will be needed to provision the infrastructure on AWS. These include the secret_access_key
, AWS_access_key_id
, among others. Next, we create a directory for our project with mkdir
and prepare it to work there:
mkdir ~/AnthosMulticloudcd ~/AnthosMulticloudexport WORKDIR=~/AnthosMulticloud .
The provisioning process uses scripts that have defined instructions to deploy the necessary infrastructure. We use Terraform to provision resources in GCP and AWS in different environments: development, staging and production.
git clone <REPO_URL>cd AnthosMulticloudWorkshop./build.sh
We monitor the process from Cloud Build in the Google console, where we will see how several jobs are deployed to lift the infrastructure.
The deployment creates:
During the provisioning script, tasks such as cluster creation and networking configuration are performed for each environment. This process can take 20 to 25 minutes.
To ensure that our infrastructure is working properly, we access the deployed services and review their performance. We use kubectl
to verify the Kubernetes clusters, and Kiali to monitor the traffic and status of the services in real time.
kubectl get pods -n istio-system
Kiali provides a visual graph showing how services connect to each other and the flow of traffic between microservices.
One of the essential aspects of the multicloud approach is to move services between clouds quickly:
For example, if the cart service
in AWS stops working, we recreate it in GKE, which restores the application without the end user noticing any interruptions.
Finally, we deploy different instances of the front end in both GCP and AWS clouds using tags and selectors. This allows load balancing between clouds and ensures high availability. When accessing our application, we can switch between instances on GCP and AWS without interrupting the user experience.
With these configurations and scripts, we have achieved a robust multi-cloud environment that is ready to handle traffic and contingencies effectively. Continue to explore and gain hands-on experience to become proficient in multi-cloud environments - you have everything you need to continue learning and improving your skills!
Contributions 5
Questions 1
Se ve muy interesante el hands on! Ojala estuviera en Qwiklabs! 馃捇
Mis respetos al contenido de este laboratorio, desde el tiempo dedicado hasta la configuraci贸n del repositorio.
Lindo ver este laboratorio en ejecuci贸n!! Realmente aterriza todo lo aprendido!
Genial lo f谩cil que lo hacen ver, pero con scripts ya hechos 馃槄
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