Application Development with Cloud Run

This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, implement, deploy, secure, manage, and scale applications on Google Cloud using Cloud Run.


Neste curso, os participantes aprenderão as seguintes habilidades:
  • Gain detailed understanding of Cloud Run, Google Cloud’s fully managed compute platform for deploying and scaling containerized applications quickly and securely.
  • Write and migrate code your way using your favorite languages (Go, Python, Java, Ruby, Node.js, and more).
  • Secure service to service communication based on service identities and grant applications only the permissions they need.
  • Learn how to build highly available applications with low end-user latency, globally.
  • Learn how to connect to, and persist data in the managed database offerings on Google Cloud.
  • Understand how abstracting away all infrastructure management creates a simple developer experience.
  • Público-alvo

    Esta aula destina-se ao seguinte público:
    • Cloud developers, API developers, customers and partners


    Para aproveitar ao máximo este curso, os participantes precisam atender aos seguintes critérios:
    • Familiarity with Linux commands and command line interface.
    • Basic understanding of Google Cloud.
    • Basic understanding of networking.
    • Basic understanding of one or more programming languages like Go, Python, Java, Ruby, or Node.js.
    • Basic understanding of shell scripts, YAML, JSON, HTTP, and TLS.


    3 dias


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    Dependências de outros cursos e certificações com o curso de Application Development with Cloud Run
    Dependências de outros cursos e certificações com o curso de Application Development with Cloud Run

    Resumo do curso

    • A general understanding of Cloud Run
    • Understand how how high availability, low end-user latency and developer productivity are important architectural drivers for web based applications today
    • Understand the advantages of serverless on Google Cloud.
    • You can use any language, any library and any binary. Cloud Run expects your app (in a container image) to listen on a port and respond to HTTP requests.
    • Use a docker repository on Artifact Registry to store your images: Cloud Run only deploys from there.
    • Cloud Run uses autoscaling to handle all incoming requests
    • Pay for use pricing model
    • No background tasks: Container lifetime is only guaranteed while handling requests
    • There is no persistent storage: Store data downstream
    • Cloud Run is portable (containers and Knative)
    • The contents of a container image (deep dive)
    • There are two ways to build container images
      – Buildpacks (hands-off)
      – Docker (you’re in control)
    • Cloud Run supports both source-based and a container image based workflow
    • The most important considerations of building a secure container image
    • Container lifecycle
      – Idle vs serving
      – Shutdown lifecycle hook
    • Cold starts
      – Min instances
    • Container readiness
    • The service resource and what it describes
    • Configuring memory limits and CPU allocation
    • Deploying a new revision
    • Traffic steering (tagging, gradual rollouts)
    • Cloud IAM
      – Service account, policy binding, roles, types of members, resource hierarchy (in practice)
      – Service accounts
      – Cloud Run IAM roles
    • Cloud Run
      – Default service account
      – Risks of using the default service account
    • Custom Domains
    • Global Load Balancer
      – URL Map
      – Frontend
      – Backend services
    • Benefits and drawbacks of GLB over custom domain
    • Types of GLB Backends
    • Multi-region load balancing
    • Multi-regional applications challenges
    • Cloud CDN
    • Ingress settings
    • Cloud Armor
    • Using Cloud IAM to protect services
      – Understand how authenticated requests (IAM + OIDC tokens) work (builds on Module 5)
    • VPC, VPC Access Connector
    • Egress settings
    • Understanding why you need to store data externally when running a workload on Cloud Run.
    • Connect with Cloud SQL from Cloud Run
      – Understand how it works (managed Cloud SQL Proxy)
    • Managing concurrency as a way to safeguard performance (understand why and when)
    • Connecting with Memorystore
    • VPC Connector
      – Challenges with scaling Memorystore (throughput)
    • Briefly introduce Cloud Storage, Firestore and Cloud Spanner, while reinforcing how the client libraries use the built-in service account to connect (Module 5 is prerequisite knowledge).
    • Multi-region data storage (and what Spanner and Firestore can do for you)
    • Understanding Cloud Pub/Sub
      – Understanding topics, push subscriptions
      – Idempotency (Handling retries and at-least-once invocation)
      – Event ID, design for resume, or use a lease
      – Handling undeliverable messages
    • How to asynchronously schedule a background task on a different service
    • Cloud Tasks, and when to choose it over Cloud Pub/Sub
    • Benefits of using Pub/Sub to pass messages over making sync RPC requests
    • Learn about services in Google Cloud with a built-in integration to push events to Pub/Sub (Cloud Build, Artifact Registry, Cloud Storage, IOT Core, BigQuery)
    • Cloud Scheduler to invoke services on a schedule.
    • CloudEvents
    • EventArc, and how to consume Audit logs
      – What to expect now, and how EventArc will develop over time
    • Conceptual overview of Cloud Workflows
    • Invoking and passing parameters
    • Understand steps and jumps
    • Defining, using and passing values with variables
    • Using the switch statement to add logic
    • Workflow visualization
    • Calling HTTPS endpoints
    • Calling an authenticated Cloud Run service
    • Example: polling API for completion