Welcome to the first part of our comprehensive blog series on implementing a sophisticated order processing system using Temporal for microservice orchestration. In this series, we’ll explore the intricacies of building a robust, scalable, and maintainable system that can handle complex, long-running workflows.
Our journey begins with setting up the foundation for our project. By the end of this post, you’ll have a fully functional CRUD REST API implemented in Golang, integrated with Temporal for workflow orchestration, and backed by a Postgres database. We’ll use modern tools and best practices to ensure our codebase is clean, efficient, and easy to maintain.
Let’s dive in and start building our order processing system!
Before we start implementing, let’s briefly review the key technologies and concepts we’ll be using:
Go is a statically typed, compiled language known for its simplicity, efficiency, and excellent support for concurrent programming. Its standard library and robust ecosystem make it an excellent choice for building microservices.
Temporal is a microservice orchestration platform that simplifies the development of distributed applications. It allows us to write complex, long-running workflows as simple procedural code, handling failures and retries automatically.
Gin is a high-performance HTTP web framework written in Go. It provides a martini-like API with much better performance and lower memory usage.
OpenAPI (formerly known as Swagger) is a specification for machine-readable interface files for describing, producing, consuming, and visualizing RESTful web services. oapi-codegen is a tool that generates Go code from OpenAPI 3.0 specifications, allowing us to define our API contract first and generate server stubs and client code.
sqlc generates type-safe Go code from SQL. It allows us to write plain SQL queries and generate fully type-safe Go code to interact with our database, reducing the likelihood of runtime errors and improving maintainability.
PostgreSQL is a powerful, open-source object-relational database system known for its reliability, feature robustness, and performance.
Docker allows us to package our application and its dependencies into containers, ensuring consistency across different environments. docker-compose is a tool for defining and running multi-container Docker applications, which we’ll use to set up our local development environment.
Now that we’ve covered the basics, let’s start implementing our system.
First, let’s create our project directory and set up the basic structure:
mkdir order-processing-system cd order-processing-system # Create directory structure mkdir -p cmd/api \ internal/api \ internal/db \ internal/models \ internal/service \ internal/workflow \ migrations \ pkg/logger \ scripts # Initialize Go module go mod init github.com/yourusername/order-processing-system # Create main.go file touch cmd/api/main.go
This structure follows the standard Go project layout:
Let’s create a Makefile to simplify common tasks:
touch Makefile
Add the following content to the Makefile:
.PHONY: generate build run test clean generate: @echo "Generating code..." go generate ./... build: @echo "Building..." go build -o bin/api cmd/api/main.go run: @echo "Running..." go run cmd/api/main.go test: @echo "Running tests..." go test -v ./... clean: @echo "Cleaning..." rm -rf bin .DEFAULT_GOAL := build
This Makefile provides targets for generating code, building the application, running it, running tests, and cleaning up build artifacts.
Create a file named api/openapi.yaml and define our API specification:
openapi: 3.0.0 info: title: Order Processing API version: 1.0.0 description: API for managing orders in our processing system paths: /orders: get: summary: List all orders responses: '200': description: Successful response content: application/json: schema: type: array items: $ref: '#/components/schemas/Order' post: summary: Create a new order requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateOrderRequest' responses: '201': description: Created content: application/json: schema: $ref: '#/components/schemas/Order' /orders/{id}: get: summary: Get an order by ID parameters: - name: id in: path required: true schema: type: integer responses: '200': description: Successful response content: application/json: schema: $ref: '#/components/schemas/Order' '404': description: Order not found put: summary: Update an order parameters: - name: id in: path required: true schema: type: integer requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/UpdateOrderRequest' responses: '200': description: Successful response content: application/json: schema: $ref: '#/components/schemas/Order' '404': description: Order not found delete: summary: Delete an order parameters: - name: id in: path required: true schema: type: integer responses: '204': description: Successful response '404': description: Order not found components: schemas: Order: type: object properties: id: type: integer customer_id: type: integer status: type: string enum: [pending, processing, completed, cancelled] total_amount: type: number created_at: type: string format: date-time updated_at: type: string format: date-time CreateOrderRequest: type: object required: - customer_id - total_amount properties: customer_id: type: integer total_amount: type: number UpdateOrderRequest: type: object properties: status: type: string enum: [pending, processing, completed, cancelled] total_amount: type: number
This specification defines our basic CRUD operations for orders.
Install oapi-codegen:
go install github.com/deepmap/oapi-codegen/cmd/oapi-codegen@latest
Generate the server code:
oapi-codegen -package api -generate types,server,spec api/openapi.yaml > internal/api/api.gen.go
This command generates the Go code for our API, including types, server interfaces, and the OpenAPI specification.
Create a new file internal/api/handler.go:
package api import ( "net/http" "github.com/gin-gonic/gin" ) type Handler struct { // We'll add dependencies here later } func NewHandler() *Handler { return &Handler{} } func (h *Handler) RegisterRoutes(r *gin.Engine) { RegisterHandlers(r, h) } // Implement the ServerInterface methods func (h *Handler) GetOrders(c *gin.Context) { // TODO: Implement c.JSON(http.StatusOK, []Order{}) } func (h *Handler) CreateOrder(c *gin.Context) { var req CreateOrderRequest if err := c.ShouldBindJSON(&req); err != nil { c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()}) return } // TODO: Implement order creation logic order := Order{ Id: 1, CustomerId: req.CustomerId, Status: "pending", TotalAmount: req.TotalAmount, } c.JSON(http.StatusCreated, order) } func (h *Handler) GetOrder(c *gin.Context, id int) { // TODO: Implement c.JSON(http.StatusOK, Order{Id: id}) } func (h *Handler) UpdateOrder(c *gin.Context, id int) { var req UpdateOrderRequest if err := c.ShouldBindJSON(&req); err != nil { c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()}) return } // TODO: Implement order update logic order := Order{ Id: id, Status: *req.Status, } c.JSON(http.StatusOK, order) } func (h *Handler) DeleteOrder(c *gin.Context, id int) { // TODO: Implement c.Status(http.StatusNoContent) }
This implementation provides a basic structure for our API handlers. We’ll flesh out the actual logic when we integrate with the database and Temporal workflows.
Create a docker-compose.yml file in the project root:
version: '3.8' services: postgres: image: postgres:13 environment: POSTGRES_USER: orderuser POSTGRES_PASSWORD: orderpass POSTGRES_DB: orderdb ports: - "5432:5432" volumes: - postgres_data:/var/lib/postgresql/data volumes: postgres_data:
This sets up a Postgres container for our local development environment.
Install golang-migrate:
go install -tags 'postgres' github.com/golang-migrate/migrate/v4/cmd/migrate@latest
Create our first migration:
migrate create -ext sql -dir migrations -seq create_orders_table
Edit the migrations/000001_create_orders_table.up.sql file:
CREATE TABLE orders ( id SERIAL PRIMARY KEY, customer_id INTEGER NOT NULL, status VARCHAR(20) NOT NULL, total_amount DECIMAL(10, 2) NOT NULL, created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP ); CREATE INDEX idx_orders_customer_id ON orders(customer_id); CREATE INDEX idx_orders_status ON orders(status);
Edit the migrations/000001_create_orders_table.down.sql file:
DROP TABLE IF EXISTS orders;
Add a new target to our Makefile:
migrate-up: @echo "Running migrations..." migrate -path migrations -database "postgresql://orderuser:orderpass@localhost:5432/orderdb?sslmode=disable" up migrate-down: @echo "Reverting migrations..." migrate -path migrations -database "postgresql://orderuser:orderpass@localhost:5432/orderdb?sslmode=disable" down
Now we can run migrations with:
make migrate-up
go install github.com/kyleconroy/sqlc/cmd/sqlc@latest
Create a sqlc.yaml file in the project root:
version: "2" sql: - engine: "postgresql" queries: "internal/db/queries.sql" schema: "migrations" gen: go: package: "db" out: "internal/db" emit_json_tags: true emit_prepared_queries: false emit_interface: true emit_exact_table_names: false
Create a file internal/db/queries.sql:
-- name: GetOrder :one SELECT * FROM orders WHERE id = $1 LIMIT 1; -- name: ListOrders :many SELECT * FROM orders ORDER BY id; -- name: CreateOrder :one INSERT INTO orders ( customer_id, status, total_amount ) VALUES ( $1, $2, $3 ) RETURNING *; -- name: UpdateOrder :one UPDATE orders SET status = $2, total_amount = $3, updated_at = CURRENT_TIMESTAMP WHERE id = $1 RETURNING *; -- name: DeleteOrder :exec DELETE FROM orders WHERE id = $1;
Add a new target to our Makefile:
generate-sqlc: @echo "Generating sqlc code..." sqlc generate
Run the code generation:
make generate-sqlc
This will generate Go code for interacting with our database in the internal/db directory.
Add Temporal to our docker-compose.yml:
temporal: image: temporalio/auto-setup:1.13.0 ports: - "7233:7233" environment: - DB=postgresql - DB_PORT=5432 - POSTGRES_USER=orderuser - POSTGRES_PWD=orderpass - POSTGRES_SEEDS=postgres depends_on: - postgres temporal-admin-tools: image: temporalio/admin-tools:1.13.0 depends_on: - temporal
Create a file internal/workflow/order_workflow.go:
package workflow import ( "time" "go.temporal.io/sdk/workflow" "github.com/yourusername/order-processing-system/internal/db" ) func OrderWorkflow(ctx workflow.Context, order db.Order) error { logger := workflow.GetLogger(ctx) logger.Info("OrderWorkflow started", "OrderID", order.ID) // Simulate order processing err := workflow.Sleep(ctx, 5*time.Second) if err != nil { return err } // Update order status err = workflow.ExecuteActivity(ctx, UpdateOrderStatus, workflow.ActivityOptions{ StartToCloseTimeout: time.Minute, }, order.ID, "completed").Get(ctx, nil) if err != nil { return err } logger.Info("OrderWorkflow completed", "OrderID", order.ID) return nil } func UpdateOrderStatus(ctx workflow.Context, orderID int64, status string) error { // TODO: Implement database update return nil }
This basic workflow simulates order processing by waiting for 5 seconds and then updating the order status to “completed”.
Update the internal/api/handler.go file to include Temporal client and start the workflow:
package api import ( "context" "net/http" "github.com/gin-gonic/gin" "go.temporal.io/sdk/client" "github.com/yourusername/order-processing-system/internal/db" "github.com/yourusername/order-processing-system/internal/workflow" ) type Handler struct { queries *db.Queries temporalClient client.Client } func NewHandler(queries *db.Queries, temporalClient client.Client) *Handler { return &Handler{ queries: queries, temporalClient: temporalClient, } } // ... (previous handler methods) func (h *Handler) CreateOrder(c *gin.Context) { var req CreateOrderRequest if err := c.ShouldBindJSON(&req); err != nil { c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()}) return } order, err := h.queries.CreateOrder(c, db.CreateOrderParams{ CustomerID: req.CustomerId, Status: "pending", TotalAmount: req.TotalAmount, }) if err != nil { c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()}) return } // Start Temporal workflow workflowOptions := client.StartWorkflowOptions{ ID: "order-" order.ID, TaskQueue: "order-processing", } _, err = h.temporalClient.ExecuteWorkflow(context.Background(), workflowOptions, workflow.OrderWorkflow, order) if err != nil { c.JSON(http.StatusInternalServerError, gin.H{"error": "Failed to start workflow"}) return } c.JSON(http.StatusCreated, order) } // ... (implement other handler methods)
Create a new file internal/service/service.go:
package service import ( "database/sql" "github.com/yourusername/order-processing-system/internal/api" "github.com/yourusername/order-processing-system/internal/db" "go.temporal.io/sdk/client" ) type Service struct { DB *sql.DB Queries *db.Queries TemporalClient client.Client Handler *api.Handler } func NewService() (*Service, error) { // Initialize database connection db, err := sql.Open("postgres", "postgresql://orderuser:orderpass@localhost:5432/orderdb?sslmode=disable") if err != nil { return nil, err } // Initialize Temporal client temporalClient, err := client.NewClient(client.Options{ HostPort: "localhost:7233", }) if err != nil { return nil, err } // Initialize queries queries := db.New(db) // Initialize handler handler := api.NewHandler(queries, temporalClient) return &Service{ DB: db, Queries: queries, TemporalClient: temporalClient, Handler: handler, }, nil } func (s *Service) Close() { s.DB.Close() s.TemporalClient.Close() }
Update the cmd/api/main.go file:
package main import ( "log" "github.com/gin-gonic/gin" _ "github.com/lib/pq" "github.com/yourusername/order-processing-system/internal/service" ) func main() { svc, err := service.NewService() if err != nil { log.Fatalf("Failed to initialize service: %v", err) } defer svc.Close() r := gin.Default() svc.Handler.RegisterRoutes(r) if err := r.Run(":8080"); err != nil { log.Fatalf("Failed to run server: %v", err) } }
Create a Dockerfile in the project root:
# Build stage FROM golang:1.17-alpine AS build WORKDIR /app COPY go.mod go.sum ./ RUN go mod download COPY . . RUN CGO_ENABLED=0 GOOS=linux go build -o /order-processing-system ./cmd/api # Run stage FROM alpine:latest WORKDIR / COPY --from=build /order-processing-system /order-processing-system EXPOSE 8080 ENTRYPOINT ["/order-processing-system"]
Update the docker-compose.yml file to include our application:
version: '3.8' services: postgres: # ... (previous postgres configuration) temporal: # ... (previous temporal configuration) temporal-admin-tools: # ... (previous temporal-admin-tools configuration) app: build: . ports: - "8080:8080" depends_on: - postgres - temporal environment: - DB_HOST=postgres - DB_USER=orderuser - DB_PASSWORD=orderpass - DB_NAME=orderdb - TEMPORAL_HOST=temporal:7233
Throughout the implementation guide, we’ve provided code snippets with explanations. Here’s a more detailed look at a key part of our system: the Order Workflow.
package workflow import ( "time" "go.temporal.io/sdk/workflow" "github.com/yourusername/order-processing-system/internal/db" ) // OrderWorkflow defines the workflow for processing an order func OrderWorkflow(ctx workflow.Context, order db.Order) error { logger := workflow.GetLogger(ctx) logger.Info("OrderWorkflow started", "OrderID", order.ID) // Simulate order processing // In a real-world scenario, this could involve multiple activities such as // inventory check, payment processing, shipping arrangement, etc. err := workflow.Sleep(ctx, 5*time.Second) if err != nil { return err } // Update order status // We use ExecuteActivity to run the status update as an activity // This allows for automatic retries and error handling err = workflow.ExecuteActivity(ctx, UpdateOrderStatus, workflow.ActivityOptions{ StartToCloseTimeout: time.Minute, }, order.ID, "completed").Get(ctx, nil) if err != nil { return err } logger.Info("OrderWorkflow completed", "OrderID", order.ID) return nil } // UpdateOrderStatus is an activity that updates the status of an order func UpdateOrderStatus(ctx workflow.Context, orderID int64, status string) error { // TODO: Implement database update // In a real implementation, this would use the db.Queries to update the order status return nil }
This workflow demonstrates several key concepts:
For this initial setup, we’ll focus on manual testing to ensure our system is working as expected. In future posts, we’ll dive into unit testing, integration testing, and end-to-end testing strategies.
To manually test our system:
docker-compose up
Use a tool like cURL or Postman to send requests to our API:
Check the logs to ensure the Temporal workflow is being triggered and completed successfully.
While setting up this initial version of our order processing system, we encountered several challenges and considerations:
Database Schema Design : Designing a flexible yet efficient schema for orders is crucial. We kept it simple for now, but in a real-world scenario, we might need to consider additional tables for order items, customer information, etc.
Error Handling : Our current implementation has basic error handling. In a production system, we’d need more robust error handling and logging, especially for the Temporal workflows.
Configuration Management : We hardcoded configuration values for simplicity. In a real-world scenario, we’d use environment variables or a configuration management system.
Security : Our current setup doesn’t include any authentication or authorization. In a production system, we’d need to implement proper security measures.
Scalability : While Temporal helps with workflow scalability, we’d need to consider database scalability and API performance for a high-traffic system.
Monitoring and Observability : We haven’t implemented any monitoring or observability tools yet. In a production system, these would be crucial for maintaining and troubleshooting the application.
In this first part of our series, we’ve set up the foundation for our order processing system. We have a basic CRUD API, database integration, and a simple Temporal workflow.
In the next part, we’ll dive deeper into Temporal workflows and activities. We’ll explore:
We’ll also start to flesh out our API with more realistic order processing logic and explore patterns for maintaining clean, maintainable code as our system grows in complexity.
Stay tuned for Part 2, where we’ll take our order processing system to the next level!
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