book

gRPC Microservices in Go

by Huseyin Babal

December 2023

Intermediate to advanced

200 pages

5h 20m

English

Manning Publications

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prefaceacknowledgmentsabout this bookWho should read this bookHow this book is organized: A road mapAbout the codeliveBook discussion forumabout the authorabout the cover illustration
1.1 Benefits of gRPC microservices1.1.1 Performance1.1.2 Code generation and interoperability1.1.3 Fault tolerance1.1.4 Security1.1.5 Streaming1.2 REST vs. RPC1.3 When to use gRPC1.3.1 Who is this book for?1.4 Production-grade use cases1.4.1 Microservices1.4.2 Container runtime1.4.3 CI/CD pipeline1.4.4 Monitoring and observability1.4.5 Public accessSummary
2.1 Monolithic architecture2.1.1 Development2.1.2 Deployment2.1.3 Scaling2.2 Scale cube2.2.1 X-axis scaling2.2.2 Z-axis scaling2.2.3 Y-axis scaling2.3 Microservice architecture2.3.1 Handling data consistency2.3.2 Saga pattern2.3.3 Choreography-based saga2.3.4 Orchestrator-based saga2.4 Service discovery2.5 Using gRPC for interservice communication2.5.1 Working with protocol buffers2.5.2 Generating Go source code2.5.3 Connecting wiresSummary
3.1 Protocol buffers3.1.1 Defining message type3.1.2 Protocol buffer encoding3.2 Generating stubs3.2.1 Protocol buffer compiler installation3.2.2 Using the protocol buffer compiler3.3 Maintaining .proto files3.3.1 Proto project structure3.3.2 Automation for source code generation3.4 Backward and forward compatibility3.4.1 Adding new fields3.4.2 Upgrading the server but not the client3.4.3 Upgrading the client but not the server3.4.4 Adding/removing oneof fields3.4.5 Moving fields out of or into oneof fieldsSummary
4.1 Hexagonal architecture4.1.1 Application4.1.2 Actors4.1.3 Ports4.1.4 Adapters4.2 Order service implementation4.2.1 Project folders4.2.2 Initializing a Go project4.2.3 Implementing the application core4.2.4 Implementing ports4.2.5 Implementing adapters4.2.6 Implementing a gRPC adapter4.2.7 Dependency injection and running the application4.2.8 Calling a gRPC endpointSummary

5.1 gRPC service-to-service communication5.1.1 Server-side load balancing5.1.2 Client-side load balancing5.2 Depending on a module and implementing ports and adapters5.2.1 Payment port5.2.2 Payment adapter5.2.3 Implementing the payment port5.2.4 Implementing the payment adapter5.2.5 Client configuration for a payment stub5.2.6 Using a payment adapter in gRPC5.3 Error handling5.3.1 Status codes5.3.2 Returning an error code and message5.3.3 Errors with details5.3.4 Handling errors on the client side5.3.5 Running the Payment serviceSummary
6.1 Resiliency patterns6.1.1 Timeout pattern6.1.2 Retry pattern6.1.3 Circuit breaker pattern6.2 Error handling6.2.1 gRPC error model6.2.2 gRPC error response6.3 Securing gRPC communication6.3.1 TLS handshake6.3.2 Certificate generation6.3.3 gRPC TLS credentialsSummary
7.1 Testing pyramid7.2 Testing with a unit test7.2.1 System under test7.2.2 Test workflow7.2.3 Working with mocks7.2.4 Implementing a mock7.2.5 Automatic mock generation7.3 Integration testing7.3.1 Test suite preparation7.3.2 Working with Testcontainers7.4 End-to-end tests7.4.1 Specifications7.4.2 Understanding Docker Compose service definitions7.4.3 End-to-end test folder structure7.4.4 Database layer7.4.5 The Payment service layer7.4.6 The Order service layer7.4.7 Running tests against the stack7.5 Test coverage7.5.1 Coverage information7.5.2 Testing in a CI pipelineSummary
8.1 Docker8.1.1 Building images8.2 Kubernetes8.2.1 Kubernetes architecture8.2.2 Kubernetes resources8.2.3 Eagle view of microservices deployment8.2.4 Pod8.2.5 Deployment8.2.6 Service8.2.7 NGINX Ingress controller8.3 Certificate management8.3.1 Installation8.3.2 ClusterIssuer8.3.3 Certificate usage in Ingress8.3.4 Certificates on the client side8.4 Deployment strategies8.4.1 RollingUpdate8.4.2 Blue-Green Deployment8.4.3 Canary deployment8.4.4 Final thoughts on deploymentSummary
9.1 Observability9.1.1 Traces9.1.2 Metrics9.1.3 Logs9.2 OpenTelemetry9.2.1 Instrumentation locations9.2.2 Instrumentation9.2.3 Metric backend9.2.4 Service performance monitoring9.3 Observability in Kubernetes9.3.1 Jaeger All in One9.3.2 OpenTelemetry Collector9.3.3 Prometheus9.3.4 Jaeger installation9.3.5 OpenTelemetry interceptor for the Order service9.3.6 Understanding the metrics of the Order service9.3.7 Application logging9.3.8 Logs collection9.3.9 Elasticsearch as a logging backend9.3.10 Kibana as a logging dashboardSummary