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.
In this course, participants will learn the following skills:
- 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.
This class is aimed at the following job roles:
Cloud developers, API developers, customers and partners
To get the most of out of this course, participants should have:
- 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.
Check the next open public class in our enrollment page. If you are interested in a private training class for your company, contact-us.
- 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
– 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.
- 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