Excelente demo, muy sencillos los comando de GCP
Compute on Google Cloud Platform
Introducci贸n al curso de Google Cloud for Developer Community
Lectura: introducci贸n de instalaci贸n
Tutorial de Qwiklabs
C贸mputo en la nube de Google
Opciones de c贸mputo en la nube
M谩quinas virtuales a profundidad
Tutorial para instalar Qwiklabs
Demo: m谩quinas virtuales a profundidad
C贸mputo sin administraci贸n con plataformas como servicio
Demo: c贸mputo sin administraci贸n
Lectura: 驴qu茅 son los contenedores?
C贸mputo contenerizado con App Engine Flex
C贸mputo contenerizado con Cloud Run
Funciones serverless
Continuous Integration, Continuous Delivery
CI/CD en Google Cloud Platform
Estrategias de Despliegue
Repositorios de c贸digo
Construcci贸n y despliegue de artefactos
Infraestructura como c贸digo
Despliegue en Servicios Serverless
Google Kubernetes Engine
Kubernetes Overview
Demo Kubernetes
Planeaci贸n de tu despliegue
Anthos
Cloud Run for Anthos
Demo Cloud Run for Anthos
Anthos Service Mesh
Site Reliability Engineering con Anthos
Streaming Data Analytics
Integraci贸n de datos e ingesta de datos totalmente administrada sobre GCP
Demo: ingesta de datos
Ingesta de datos confiable en streaming sobre GCP
Demo: ingesta de datos confiable
Demo: configuraci贸n de Apache Kafka
Visualizaci贸n de mensajes de una base de datos relacional en Google Cloud
Data Warehouse: el modelo tradicional para construir un repositorio de datos empresarial
Data Lakehouse: el nuevo y moderno enfoque para construir un repositorio de datos empresarial
El portafolio de gesti贸n de datos en Google Cloud
Desglose del portafolio de gesti贸n de datos (Bases de datos) en Google Cloud
Gobierno de datos de punta a punta para garantizar la seguridad en tu Data Lake
Gobierno de datos: calidad y monitoreo
Machine Learning
驴Qu茅 es ML y AI?
Plataforma de AI en GCP
Auto ML con datos estructurados
Demo Auto ML con datos estructurados
Predicci贸n de tarifas usando AI notebooks
Demo predicci贸n de tarifas usando AI notebooks
TensorFlow Extended
Sesiones en vivo
Sesi贸n en vivo con Pablo P茅rez Villanueva
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Resources
How to launch a service on Cloud Run?
Launching a service in Cloud Run on Google Kubernetes Engine (GKE) is a process that may seem complex, but with the right tools and configurations, it becomes an affordable task. This tutorial will guide you step-by-step to deploy your application using Cloud Run, optimizing with features like autoscaling and load balancing. Let's dive into how to run this operation efficiently and straightforwardly.
How do I set up the environment for Cloud Run?
First, it's essential to get our infrastructure ready. Before launching your application, make sure you have configured the Kubernetes cluster. Here we show you the fundamental command to create it:
gcloud container clusters create [CLUSTER_NAME] \ --addons=HorizontalPodAutoscaling,CloudRun \ --enable-ip-alias \ --enable-stackdriver-kubernetes \ --machine-type=n1-standard-2\ --zone=us-central1-a- HorizontalPodAutoscaling: Essential to use Cloud Run.
- CloudRun: Allow our applications to run on this platform.
- enable-ip-alias and enable-stackdriver-kubernetes: Tools to monitor and manage the cluster.
- machine-type: Defines the type and size of the virtual machine.
- zone: The geographical location for resource and latency optimization.
How to deploy a service in the cluster?
With the cluster prepared, we move on to the deployment of the service. Follow these steps:
gcloud run deploy my-service \ --namespace default \ --image gcr.io/[PROJECT]/cloud-run-hello \ --platform gke \ --cluster PlatziCluster \ --cluster-location us-central1-a- my-service: Is the name given to your service.
- namespace: Indicates the workspace, by default used here.
- image: Container image to use, registered in Google Container Registry.
- platform and cluster: Specify where the service will be launched.
- cluster-location: Specific location in the cluster.
How to verify that the service is active?
Once deployed, it is important to verify that your service is working properly. This can be done through a simple curl command:
curl -o output.html [SERVICE_URL].If executed successfully, you will get an HTML file that you can open in a browser to visualize your service in action.
Congratulations! If you followed these steps, you have successfully deployed a Cloud Run service on GKE. Remember that each deployment generates a YAML that you can reuse for future deployments, thus facilitating the management and scalability of your cloud applications. Continue to explore and experiment with new configurations to optimize your projects.
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