Training Google Cloud

Training goals

code: G-ADWCR

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

 

What you'll learn

  • 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.

Who this course is for:

  • Cloud developers, API developers, customers and partners

Conspect Show list

  • Introducing Application Development with Cloud Run
    • Introducing Application Development with Cloud Run
  • Understanding Cloud Run
    • 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)
  • Building Container Images
    • 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
  • Building Container Images
    • 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)
  • Configuring Service Identity and Authorization
    • Cloud IAM
    • Cloud Run
  • Serving Requests
    • 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
  • Using Inbound and Outbound Access Control
    • Ingress settings
    • Cloud Armor
    • Using Cloud IAM to protect services
    • VPC, VPC Access Connector
    • Egress settings
  • Persisting Data
    • 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
    • Multi-region data storage (and what Spanner and Firestore can do for you)
  • Implementing Service-to-Service Communication
    • 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
  • Orchestrating and Automating Serverless Workflows
    • 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
Download conspect training as PDF

Additional information

Prerequisites
  • 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.
Difficulty level
Duration 3 days
Certificate

The participants will obtain certificates signed by Google Cloud Platform. 
Trainer

Authorized Google Cloud Platform Trainer

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