![Developing Applications with Google Cloud
# Imports the Google Cloud client library
from google.cloud import datastore
# Instantiates a client
datastore_client = datastore.Client()
# The kind for the new entity
kind = "Order"
name = "order1"
# The Cloud Datastore key for the new entity
order_key = datastore_client.key(kind, name)
order = datastore.Entity(key=order_key)
order["description"] = "Milk"
order["created"] = datetime.datetime.now()
# Saves the entity
datastore_client.put(order)
Application
google-cloud-storage==1.4.0
GCP SDK
{
"Name/ID":"order1",
"description":"Milk",
"created":"2023/07/29 14:00:00"
}
Cloud Firestore](https://image.slidesharecdn.com/coscup2023rich-230729030413-3bb7b5eb/85/COSCUP-2023-Building-Portable-and-Reliable-Applications-on-Google-Cloud-10-320.jpg)
COSCUP 2023 Building Portable and Reliable Applications on Google Cloud
- 1. 2023 Building Portable and Reliable Applications on Google Cloud
- 2. 李琦 Rich Application Architect • Microservices • Event-driven • Cloud Native App Development • Kafka & Event-driven consultant rich04230@gmail.com RICH0423 @rich04230 About Me
- 3. Agenda Cloud Native Application Application Development in Google Cloud Dapr : Distributed Application Runtime Application Resiliency Patterns
- 4. What is Cloud Native?
- 5. Cloud native is building software applications as a collection of independent, loosely coupled, business-capability-oriented services that can run on dynamic environments in an automated, scalable, resilient, manageable, and observable way. <<Design Patterns for Cloud Native Applications>> Kasun Indrasiri and Sriskandarajah Suhothayan
- 6. Distributed Systems Communication Service A • Core functionality • Retry / Timeout • Logging • Configuration request Service B • Core functionality • Retry / Timeout • Logging • Configuration
- 7. Distributed Systems Communication – Sidecar Service A • Core functionality Service B • Core functionality • Retry / Timeout • Logging • Service Discovery Sidecar • Retry / Timeout • Logging • Service Discovery Sidecar
- 8. Problems with Cloud Native Application Any cloud or edge infrastructure Application Code Client SDK GCP SDK AWS SDK AZURE SDK Spring
- 9. Application Code Problems with Cloud Native Application Any cloud or edge infrastructure Client SDK GCP SDK AWS SDK AZURE SDK Spring Application high coupled
- 10. Developing Applications with Google Cloud # Imports the Google Cloud client library from google.cloud import datastore # Instantiates a client datastore_client = datastore.Client() # The kind for the new entity kind = "Order" name = "order1" # The Cloud Datastore key for the new entity order_key = datastore_client.key(kind, name) order = datastore.Entity(key=order_key) order["description"] = "Milk" order["created"] = datetime.datetime.now() # Saves the entity datastore_client.put(order) Application google-cloud-storage==1.4.0 GCP SDK { "Name/ID":"order1", "description":"Milk", "created":"2023/07/29 14:00:00" } Cloud Firestore
- 11. Dapr Dapr
- 12. Support any language Provides over 70+ components
- 14. My App Pub/sub Brokers Bindings & Triggers Secret Stores Observability Prometheus AppInsights Jaeger Zipkin State Stores Configuration Distributed Lock Workflow Dapr components
- 15. Swappable component model Service 2
- 16. Swappable component model Service 2
- 17. Swappable component model Service 2
- 18. Using Dapr and Firestore DEMO
- 19. cloud-firestore.yaml apiVersion: dapr.io/v1alpha1 kind: Component metadata: name: orderstore spec: type: state.gcp.firestore version: v1 metadata: - name: type value: service_account - name: project_id value: dascs-lab - name: private_key_id value: 486ec036cca569ecc151c4cd5aa17ba46fb - name: client_email value: sa@rich- lab.iam.gserviceaccount.com Developing Applications with Dapr Application key Field value myapp||order1 description "Milk" myapp||order1 created 2023/07/29 14:00:00 Cloud Firestore <code>
- 21. Application Resiliency – Retry Pattern Service A • Core functionality • Retry / Timeout (Retries = 4, duration=2 sec) request Service B • Core functionality • Retry / Timeout 200 500 500 The Retry pattern enables a service to retry a failed request operation a (configurable) number of times with an exponentially increasing wait time.
- 22. Application Resiliency – Circuit Breaker Pattern Service A • Core functionality • Retry / Timeout (Retries=4, duration=2 sec) • Circuit Breaker (failed count = 5, check = 30sec) request Service B • Core functionality • Retry / Timeout The Circuit Breaker pattern can prevent an application from repeatedly trying to execute an operation that's likely to fail. After a pre-defined number of failed calls, it blocks all traffic to the service. 5
- 23. resiliency.yaml apiVersion: dapr.io/v1alpha1 kind: Resiliency metadata: name: myresiliency spec: policies: retries: retryForever: policy: constant duration: 5s maxRetries: -1 circuitBreakers: simpleCB: maxRequests: 1 timeout: 5s trip: consecutiveFailures >= 5 • Resiliency patterns can be applied across Dapr APIs • Retries • Timeouts • Circuit breakers • Declarative and decoupled from application code • Available across all component types, service invocation and actors. Dapr - Resiliency
- 25. Order Processor Checkout Pub/sub queue Inbound Outbound 1 Outbound component resiliency policies for `retries`, `timeouts and `circuit breakers` can be applied to message publishing 1 Additionally, many pub/sub components have `retry` capabilities built-in. The policies are configured on a per component basis. Resiliency in PubSub 1 Inbound component resiliency polices for `retries`, `timeouts and `circuit breakers` policies can be applied to subscriptions when delivering messages
- 26. Key Takeaways 💪 Cloud Native Application on Google Cloud 💪 Decoupling from Cloud Provider/Infra with Dapr 💪 Resilience patterns and implement with Dapr