Implementing type-safe dependency injection in a Hono backend with Effect-TS's Layer system

When working with NestJS long enough, decorator fatigue sets in — @Injectable(), @Module(), reflect-metadata. The DI container itself is a great idea, but the fact that dependency errors only surface at runtime always felt unsettling. It wasn't until I hit Nest can't resolve dependencies in production that I truly appreciated the value of compile-time validation.

Effect-TS's Layer system solves this problem at the type system level. If the dependency graph is composed incorrectly, tsc blocks the build. Error types are declared in function signatures, eliminating dark zones like catch (e: unknown). Combined with a lightweight framework like Hono, you can build a testable, structured backend architecture without any framework magic.

This article walks through the three type parameters of Effect<A, E, R>, the Service · Layer · Runtime pattern, using ManagedRuntime in Hono route handlers, and testing without mocks by swapping layers.

Core Concepts

Effect's Three Type Parameters — One Line Says It All

typescript

Effect<A, E, R>
//     │  │  └── Requirements: dependencies needed for execution
//     │  └───── Error: expected domain errors
//     └──────── Success: return value on success

The R parameter is the key that lifts dependency injection to the type level. If R = Database | Cache, the compiler knows that both Database and Cache must be provided to run this Effect. Without them, even runPromise won't compile.

E encodes expected domain errors. They're expressed as union types like UserNotFoundError | DatabaseError, and leaving them unhandled causes a type error. Unexpected faults (defects) are separated into a distinct Cause type, allowing domain errors and infrastructure failures to be handled independently.

Defining Services with Context.Tag

Where NestJS's @Injectable() relies on reflect-metadata, Effect's Context.Tag works through pure type inference.

First, define the domain types and error types used throughout the examples.

typescript

import { Context, Effect } from "effect"
 
// Domain types
interface User {
  id: string
  name: string
  email: string
}
 
interface UserProfile extends User {
  displayName: string
}
 
// Domain error types — a discriminated union via _tag
class UserNotFoundError {
  readonly _tag = "UserNotFoundError"
  constructor(readonly userId: string) {}
}
 
class DatabaseError {
  readonly _tag = "DatabaseError"
  constructor(readonly cause: unknown) {}
}
 
type AppError = UserNotFoundError | DatabaseError

Service interfaces are defined using a class pattern that extends Context.Tag.

typescript

// UserRepository service — the Tag itself is the identifier
class UserRepository extends Context.Tag("UserRepository")<
  UserRepository,
  {
    readonly findById: (id: string) => Effect.Effect<User, UserNotFoundError | DatabaseError>
    readonly findAll: () => Effect.Effect<User[], DatabaseError>
    readonly save: (user: User) => Effect.Effect<void, DatabaseError>
  }
>() {}
 
// Business logic that uses the service
const getUserProfile = (
  userId: string
): Effect.Effect<UserProfile, UserNotFoundError | DatabaseError, UserRepository> =>
  Effect.gen(function* () {
    const repo = yield* UserRepository
    const user = yield* repo.findById(userId)
    return { ...user, displayName: `${user.name} (${user.email})` }
  })

The yield* syntax in Effect.gen may look unfamiliar at first. Think of it as the functional equivalent of async/await — it clicks quickly. yield* UserRepository is a request to "pull out the UserRepository implementation from the runtime," and its type is automatically reflected in the R parameter of the function signature.

Layer — A Recipe for Composing Services

Layer<ROut, E, RIn> is a recipe that says "to build this service (ROut), you need this (RIn), and this error (E) may occur." The key insight is that it describes how to construct a service, not the implementation itself.

Before composing layers, define the Database and AppConfig services as well.

typescript

import { Context, Effect, Layer, Config } from "effect"
 
// AppConfig service definition
class AppConfig extends Context.Tag("AppConfig")<
  AppConfig,
  {
    readonly databaseUrl: string
    readonly jwtSecret: string
  }
>() {}
 
// Database service definition
class Database extends Context.Tag("Database")<
  Database,
  {
    readonly query: (query: string, params: unknown[]) => Effect.Effect<unknown[], DatabaseError>
  }
>() {}

Now define the layer (implementation) for each service.

typescript

import postgres from "postgres"
 
// Config layer — reads environment variables in a type-safe way
const ConfigLive = Layer.effect(
  AppConfig,
  Effect.gen(function* () {
    const databaseUrl = yield* Config.string("DATABASE_URL")
    const jwtSecret = yield* Config.string("JWT_SECRET")
    return { databaseUrl, jwtSecret }
  })
)
 
// Database layer — depends on AppConfig
const DatabaseLive = Layer.effect(
  Database,
  Effect.gen(function* () {
    const config = yield* AppConfig
    const sql = postgres(config.databaseUrl)
    return {
      query: (query: string, params: unknown[]) =>
        Effect.tryPromise({
          try: () => sql.unsafe(query, params as postgres.ParameterOrFragment<never>[]),
          catch: (e) => new DatabaseError(e),
        }),
    }
  })
)
 
// UserRepository layer — depends on Database
const UserRepositoryLive = Layer.effect(
  UserRepository,
  Effect.gen(function* () {
    const db = yield* Database
    return {
      findById: (id: string) =>
        Effect.gen(function* () {
          const rows = yield* db.query("SELECT * FROM users WHERE id = $1", [id])
          if (rows.length === 0) return yield* Effect.fail(new UserNotFoundError(id))
          return rows[0] as User
        }),
      findAll: () =>
        db.query("SELECT * FROM users", []).pipe(
          Effect.map((rows) => rows as User[])
        ),
      save: (user: User) =>
        db
          .query("INSERT INTO users VALUES ($1, $2, $3)", [user.id, user.name, user.email])
          .pipe(Effect.map(() => undefined)),
    }
  })
)

At the type level, Layer.provide(that) satisfies the portion of the current layer's RIn requirements that that provides. Through the chain, RIn is progressively eliminated until the final layer's RIn approaches never. Any type mismatch is caught immediately by the compiler.

typescript

// Declaratively compose the dependency graph
const AppLayer = UserRepositoryLive.pipe(
  Layer.provide(DatabaseLive),  // satisfies UserRepository's Database requirement
  Layer.provide(ConfigLive)     // satisfies Database's AppConfig requirement
)

In the diagram below, arrows indicate the "provide" direction. ConfigLive provides AppConfig to DatabaseLive, and DatabaseLive provides Database to UserRepositoryLive.

Diagram 1

ManagedRuntime — Making a Layer Executable

The "Managed" in ManagedRuntime means resource acquisition and release are managed as a lifecycle. When the layer initializes, a DB connection is opened; when dispose() is called, the connection is cleaned up. This is why AppRuntime.dispose() makes sense.

A Layer is just a recipe — it's ManagedRuntime's job to actually instantiate services and run Effects. The standard pattern is to create it once at app startup and reuse it for all requests.

typescript

import { ManagedRuntime } from "effect"
 
// Created once at app startup — reused for all subsequent requests
const AppRuntime = ManagedRuntime.make(AppLayer)
 
// Clean up resources on shutdown
process.on("SIGTERM", () => AppRuntime.dispose())

Practical Application

Integrating with Hono

Each Hono route handler is an async function, so it connects naturally with runPromiseExit. AppRuntime is declared in module scope and referenced via closure.

First, create a helper that maps errors to HTTP responses. Using Exit.match and Cause.failureOption is the idiomatic Effect pattern. Fixing the error parameter to the concrete type AppError makes the switch statement exhaustive, so the compiler catches any unhandled error cases.

typescript

import { Hono, type Context as HonoContext } from "hono"
import { Cause, Effect, Exit, ManagedRuntime, Option } from "effect"
 
// AppRuntime — created once in module scope
const AppRuntime = ManagedRuntime.make(AppLayer)
 
// Error parameter fixed to concrete type — guarantees exhaustive switch
const handleEffect = async <A>(
  c: HonoContext,
  effect: Effect.Effect<A, AppError>
) => {
  const exit = await AppRuntime.runPromiseExit(effect)
  return Exit.match(exit, {
    onSuccess: (value) => c.json(value),
    onFailure: (cause) => {
      const maybeError = Cause.failureOption(cause)
      if (Option.isNone(maybeError)) {
        return c.json({ error: "Internal Server Error" }, 500)
      }
      const error = maybeError.value
      // AppError = UserNotFoundError | DatabaseError
      // Both cases are covered, so no default branch is needed
      switch (error._tag) {
        case "UserNotFoundError":
          return c.json({ error: `User ${error.userId} not found` }, 404)
        case "DatabaseError":
          return c.json({ error: "Database error" }, 500)
      }
    },
  })
}
 
const app = new Hono()
 
app.get("/users/:id", async (c) => {
  const userId = c.req.param("id")
  return handleEffect(c, getUserProfile(userId))
})
 
app.get("/users", async (c) => {
  const effect = Effect.gen(function* () {
    const repo = yield* UserRepository
    return yield* repo.findAll()
  })
  return handleEffect(c, effect)
})
 
app.post("/users", async (c) => {
  // In real implementations, validate the body with @hono/effect-validator or zod first.
  const body = await c.req.json<{ name: string; email: string }>()
  const effect = Effect.gen(function* () {
    const repo = yield* UserRepository
    const user: User = { id: crypto.randomUUID(), name: body.name, email: body.email }
    yield* repo.save(user)
    return user
  })
  return handleEffect(c, effect)
})
 
export default app

Below is the full flow of a GET /users/:id request.

Diagram 2

Test Isolation via Layer Swapping — No Mocking Required

Creating a test layer eliminates the need for any mocking library. The same business logic can run without a real database.

typescript

import { it, expect } from "@effect/vitest"
import { Effect, Layer } from "effect"
 
// In-memory implementation — same interface, different implementation
const UserRepositoryTest = Layer.succeed(UserRepository, {
  findById: (id: string) =>
    id === "existing-user"
      ? Effect.succeed({ id, name: "Test User", email: "test@example.com" })
      : Effect.fail(new UserNotFoundError(id)),
  findAll: () =>
    Effect.succeed([
      { id: "1", name: "Alice", email: "alice@example.com" },
      { id: "2", name: "Bob", email: "bob@example.com" },
    ]),
  save: (_user: User) => Effect.succeed(undefined),
})
 
// Just as you compose multiple services in the real app, combine test layers with Layer.mergeAll.
// Here we only have UserRepository, but EmailService, CacheService, etc. can be added the same way.
const TestLayer = Layer.mergeAll(UserRepositoryTest)
 
it.effect("returns a profile for an existing user", () =>
  Effect.gen(function* () {
    const profile = yield* getUserProfile("existing-user")
    expect(profile.displayName).toBe("Test User (test@example.com)")
  }).pipe(Effect.provide(TestLayer))
)
 
it.effect("returns UserNotFoundError for a non-existent user", () =>
  Effect.gen(function* () {
    // Effect.either wraps errors as Left and successes as Right, treating them as values.
    // Similar to Rust's Result or Go's (value, error) tuple.
    const result = yield* getUserProfile("unknown-user").pipe(Effect.either)
    expect(result._tag).toBe("Left")
    if (result._tag === "Left") {
      expect(result.left._tag).toBe("UserNotFoundError")
      expect(result.left.userId).toBe("unknown-user")
    }
  }).pipe(Effect.provide(TestLayer))
)

Integrating with Drizzle ORM — An Alternative Implementation

In production, raw SQL is often replaced with Drizzle ORM. @effect/sql-drizzle lets you use Drizzle's type-safe query builder on top of an Effect connection pool. This section is an alternative implementation of UserRepositoryLive. The rest — ConfigLive and the layer composition approach — remains the same.

typescript

import { PgClient } from "@effect/sql-pg"
import { DrizzlePgClient } from "@effect/sql-drizzle/Pg"
import { eq } from "drizzle-orm"
import { pgTable, text, varchar } from "drizzle-orm/pg-core"
import { Config, Effect, Layer } from "effect"
 
const usersTable = pgTable("users", {
  id: varchar("id", { length: 36 }).primaryKey(),
  name: text("name").notNull(),
  email: text("email").notNull(),
})
 
const PgLive = PgClient.layerConfig({
  url: Config.string("DATABASE_URL"),
})
 
const DrizzleLive = DrizzlePgClient.layer.pipe(Layer.provide(PgLive))
 
// Drizzle implementation of UserRepository — an alternative to UserRepositoryLive
const UserRepositoryDrizzleLive = Layer.effect(
  UserRepository,
  Effect.gen(function* () {
    const db = yield* DrizzlePgClient
    return {
      findById: (id: string) =>
        Effect.gen(function* () {
          const rows = yield* db.select().from(usersTable).where(eq(usersTable.id, id))
          if (rows.length === 0) return yield* Effect.fail(new UserNotFoundError(id))
          return rows[0]
        }),
      findAll: () => db.select().from(usersTable),
      save: (user: User) =>
        db.insert(usersTable).values(user).pipe(Effect.map(() => undefined)),
    }
  })
)
 
// Final Drizzle-based layer — an alternative to AppLayer (the raw SQL version)
const AppLayerDrizzle = UserRepositoryDrizzleLive.pipe(Layer.provide(DrizzleLive))

Trade-off Analysis

When Is Effect-TS Worth Considering

Diagram 3

Area	Pros	Cons
Dependency validation	Missing dependencies caught at compile time	Layer composition has a learning curve
Error typing	Domain errors are explicit in function signatures	You must design error types yourself
Testability	Layer swapping eliminates the need for mocks	Initial cost of writing test layers
Concurrency	Fiber-based structured concurrency	Stack traces can be awkward to debug
Bundle size	`@effect/micro` available for edge environments	The core `effect` package itself has size
Learning curve	Consistent functional API, patterns repeat	Fiber, Layer, Cause, Schedule all at once

Common Mistakes in Practice

1. Creating ManagedRuntime on Every Request

typescript

// Wrong pattern — a new DB connection pool is created per request
app.get("/users", async (c) => {
  const runtime = ManagedRuntime.make(AppLayer) // ❌
  return c.json(await runtime.runPromise(getAllUsers))
})
 
// Correct pattern — created once in module scope
const AppRuntime = ManagedRuntime.make(AppLayer) // ✅
app.get("/users", async (c) => {
  return c.json(await AppRuntime.runPromise(getAllUsers))
})

2. Handling Promises Directly Inside an Effect Chain

The callback in Effect.gen is a plain function*, not an async function*. This means await is a syntax error inside it. Promises must be wrapped with Effect.tryPromise (with error handling) or Effect.promise (when no errors are guaranteed), and the result must be received with yield*.

typescript

// Compile error — await is a syntax error inside function*
const fetchUser = (id: string) =>
  Effect.gen(function* () {
    const user = await fetch(`/api/users/${id}`).then((r) => r.json()) // ❌ SyntaxError
    return user
  })
 
// Correct — lift the Promise into an Effect, then run it with yield*
const fetchUser = (id: string) =>
  Effect.tryPromise({
    try: () => fetch(`/api/users/${id}`).then((r) => r.json()),
    catch: (e) => new FetchError(e),
  })

Note that Effect.tryPromise is for async work that returns a Promise, while Effect.try is for synchronous work that may throw. They are separate APIs.

3. Overusing runSync When Partially Adopting Effect in an Existing Codebase

Effect has an "infectious" quality similar to async/await. Just as calling an async function requires the caller to also be async, calling a function that returns an Effect naturally requires the caller to return an Effect as well. Forcing a break in this propagation with runSync will throw an exception when encountering an async Effect.

typescript

// Using runSync on an async Effect throws at runtime
const result = Effect.runSync(someAsyncEffect) // ❌
 
// Progressively convert the call stack to Effect, or define a clear boundary and escape with runPromise
const result = await Effect.runPromise(someAsyncEffect) // ✅

Closing Thoughts

Effect-TS's Layer system realizes the principle — "dependency errors at compile time, error handling enforced by the type system" — within TypeScript. Without NestJS's IoC container, you can build a structured, testable backend on a lightweight framework like Hono.

Key takeaways:

Effect<A, E, R>: Encodes success value, error, and dependencies in a single type
Context.Tag: Identifies services in pure TypeScript without decorators
Layer: A recipe for composing services; Layer.provide progressively eliminates RIn to assemble the dependency graph
ManagedRuntime: An execution context that manages resource lifecycles — created once at the app level and reused
Layer-swap testing: Run the same logic in two environments without any mocking library

When you first encounter Effect, yield* and Layer.provide chains feel unfamiliar. Once the patterns click, they feel far more intuitive than the @Module and @Inject dance in NestJS.

If you're starting today, this is the recommended order:

Start with Effect.gen and Context.Tag: Rewrite one piece of existing business logic in Effect to get comfortable with yield* syntax and the three type parameters.
Write a test layer with Layer.succeed: Running the same logic without a real database immediately demonstrates the value of Layers.
Wire it into Hono with ManagedRuntime: Build a helper that maps errors to HTTP status codes using runPromiseExit, and the architecture is complete.

The Effect ecosystem is maturing rapidly, and the official Discord community responds quickly to technically serious questions. If you're feeling the fatigue of catch (e: unknown) in a long-lived production backend, the Layer system may be a meaningful alternative worth exploring.

References

#Effect-TS#TypeScript#의존성 주입#Hono#Layer#Backend

Effect-TS의 Layer 시스템으로 Hono 백엔드에 타입 안전한 의존성 주입 구현하기 | DEV BAK - 기술블로그

Backend

Implementing type-safe dependency injection in a Hono backend with Effect-TS's Layer system

Core Concepts

Effect's Three Type Parameters — One Line Says It All

typescript

Effect<A, E, R>
//     │  │  └── Requirements: dependencies needed for execution
//     │  └───── Error: expected domain errors
//     └──────── Success: return value on success

Defining Services with Context.Tag

Where NestJS's @Injectable() relies on reflect-metadata, Effect's Context.Tag works through pure type inference.

First, define the domain types and error types used throughout the examples.

typescript

import { Context, Effect } from "effect"
 
// Domain types
interface User {
  id: string
  name: string
  email: string
}
 
interface UserProfile extends User {
  displayName: string
}
 
// Domain error types — a discriminated union via _tag
class UserNotFoundError {
  readonly _tag = "UserNotFoundError"
  constructor(readonly userId: string) {}
}
 
class DatabaseError {
  readonly _tag = "DatabaseError"
  constructor(readonly cause: unknown) {}
}
 
type AppError = UserNotFoundError | DatabaseError

Service interfaces are defined using a class pattern that extends Context.Tag.

typescript

// UserRepository service — the Tag itself is the identifier
class UserRepository extends Context.Tag("UserRepository")<
  UserRepository,
  {
    readonly findById: (id: string) => Effect.Effect<User, UserNotFoundError | DatabaseError>
    readonly findAll: () => Effect.Effect<User[], DatabaseError>
    readonly save: (user: User) => Effect.Effect<void, DatabaseError>
  }
>() {}
 
// Business logic that uses the service
const getUserProfile = (
  userId: string
): Effect.Effect<UserProfile, UserNotFoundError | DatabaseError, UserRepository> =>
  Effect.gen(function* () {
    const repo = yield* UserRepository
    const user = yield* repo.findById(userId)
    return { ...user, displayName: `${user.name} (${user.email})` }
  })

Layer — A Recipe for Composing Services

Before composing layers, define the Database and AppConfig services as well.

typescript

import { Context, Effect, Layer, Config } from "effect"
 
// AppConfig service definition
class AppConfig extends Context.Tag("AppConfig")<
  AppConfig,
  {
    readonly databaseUrl: string
    readonly jwtSecret: string
  }
>() {}
 
// Database service definition
class Database extends Context.Tag("Database")<
  Database,
  {
    readonly query: (query: string, params: unknown[]) => Effect.Effect<unknown[], DatabaseError>
  }
>() {}

Now define the layer (implementation) for each service.

typescript

import postgres from "postgres"
 
// Config layer — reads environment variables in a type-safe way
const ConfigLive = Layer.effect(
  AppConfig,
  Effect.gen(function* () {
    const databaseUrl = yield* Config.string("DATABASE_URL")
    const jwtSecret = yield* Config.string("JWT_SECRET")
    return { databaseUrl, jwtSecret }
  })
)
 
// Database layer — depends on AppConfig
const DatabaseLive = Layer.effect(
  Database,
  Effect.gen(function* () {
    const config = yield* AppConfig
    const sql = postgres(config.databaseUrl)
    return {
      query: (query: string, params: unknown[]) =>
        Effect.tryPromise({
          try: () => sql.unsafe(query, params as postgres.ParameterOrFragment<never>[]),
          catch: (e) => new DatabaseError(e),
        }),
    }
  })
)
 
// UserRepository layer — depends on Database
const UserRepositoryLive = Layer.effect(
  UserRepository,
  Effect.gen(function* () {
    const db = yield* Database
    return {
      findById: (id: string) =>
        Effect.gen(function* () {
          const rows = yield* db.query("SELECT * FROM users WHERE id = $1", [id])
          if (rows.length === 0) return yield* Effect.fail(new UserNotFoundError(id))
          return rows[0] as User
        }),
      findAll: () =>
        db.query("SELECT * FROM users", []).pipe(
          Effect.map((rows) => rows as User[])
        ),
      save: (user: User) =>
        db
          .query("INSERT INTO users VALUES ($1, $2, $3)", [user.id, user.name, user.email])
          .pipe(Effect.map(() => undefined)),
    }
  })
)

typescript

// Declaratively compose the dependency graph
const AppLayer = UserRepositoryLive.pipe(
  Layer.provide(DatabaseLive),  // satisfies UserRepository's Database requirement
  Layer.provide(ConfigLive)     // satisfies Database's AppConfig requirement
)

In the diagram below, arrows indicate the "provide" direction. ConfigLive provides AppConfig to DatabaseLive, and DatabaseLive provides Database to UserRepositoryLive.

Diagram 1

ManagedRuntime — Making a Layer Executable

A Layer is just a recipe — it's ManagedRuntime's job to actually instantiate services and run Effects. The standard pattern is to create it once at app startup and reuse it for all requests.

typescript

import { ManagedRuntime } from "effect"
 
// Created once at app startup — reused for all subsequent requests
const AppRuntime = ManagedRuntime.make(AppLayer)
 
// Clean up resources on shutdown
process.on("SIGTERM", () => AppRuntime.dispose())

Practical Application

Integrating with Hono

Each Hono route handler is an async function, so it connects naturally with runPromiseExit. AppRuntime is declared in module scope and referenced via closure.

typescript

import { Hono, type Context as HonoContext } from "hono"
import { Cause, Effect, Exit, ManagedRuntime, Option } from "effect"
 
// AppRuntime — created once in module scope
const AppRuntime = ManagedRuntime.make(AppLayer)
 
// Error parameter fixed to concrete type — guarantees exhaustive switch
const handleEffect = async <A>(
  c: HonoContext,
  effect: Effect.Effect<A, AppError>
) => {
  const exit = await AppRuntime.runPromiseExit(effect)
  return Exit.match(exit, {
    onSuccess: (value) => c.json(value),
    onFailure: (cause) => {
      const maybeError = Cause.failureOption(cause)
      if (Option.isNone(maybeError)) {
        return c.json({ error: "Internal Server Error" }, 500)
      }
      const error = maybeError.value
      // AppError = UserNotFoundError | DatabaseError
      // Both cases are covered, so no default branch is needed
      switch (error._tag) {
        case "UserNotFoundError":
          return c.json({ error: `User ${error.userId} not found` }, 404)
        case "DatabaseError":
          return c.json({ error: "Database error" }, 500)
      }
    },
  })
}
 
const app = new Hono()
 
app.get("/users/:id", async (c) => {
  const userId = c.req.param("id")
  return handleEffect(c, getUserProfile(userId))
})
 
app.get("/users", async (c) => {
  const effect = Effect.gen(function* () {
    const repo = yield* UserRepository
    return yield* repo.findAll()
  })
  return handleEffect(c, effect)
})
 
app.post("/users", async (c) => {
  // In real implementations, validate the body with @hono/effect-validator or zod first.
  const body = await c.req.json<{ name: string; email: string }>()
  const effect = Effect.gen(function* () {
    const repo = yield* UserRepository
    const user: User = { id: crypto.randomUUID(), name: body.name, email: body.email }
    yield* repo.save(user)
    return user
  })
  return handleEffect(c, effect)
})
 
export default app

Below is the full flow of a GET /users/:id request.

Diagram 2

Test Isolation via Layer Swapping — No Mocking Required

Creating a test layer eliminates the need for any mocking library. The same business logic can run without a real database.

typescript

import { it, expect } from "@effect/vitest"
import { Effect, Layer } from "effect"
 
// In-memory implementation — same interface, different implementation
const UserRepositoryTest = Layer.succeed(UserRepository, {
  findById: (id: string) =>
    id === "existing-user"
      ? Effect.succeed({ id, name: "Test User", email: "test@example.com" })
      : Effect.fail(new UserNotFoundError(id)),
  findAll: () =>
    Effect.succeed([
      { id: "1", name: "Alice", email: "alice@example.com" },
      { id: "2", name: "Bob", email: "bob@example.com" },
    ]),
  save: (_user: User) => Effect.succeed(undefined),
})
 
// Just as you compose multiple services in the real app, combine test layers with Layer.mergeAll.
// Here we only have UserRepository, but EmailService, CacheService, etc. can be added the same way.
const TestLayer = Layer.mergeAll(UserRepositoryTest)
 
it.effect("returns a profile for an existing user", () =>
  Effect.gen(function* () {
    const profile = yield* getUserProfile("existing-user")
    expect(profile.displayName).toBe("Test User (test@example.com)")
  }).pipe(Effect.provide(TestLayer))
)
 
it.effect("returns UserNotFoundError for a non-existent user", () =>
  Effect.gen(function* () {
    // Effect.either wraps errors as Left and successes as Right, treating them as values.
    // Similar to Rust's Result or Go's (value, error) tuple.
    const result = yield* getUserProfile("unknown-user").pipe(Effect.either)
    expect(result._tag).toBe("Left")
    if (result._tag === "Left") {
      expect(result.left._tag).toBe("UserNotFoundError")
      expect(result.left.userId).toBe("unknown-user")
    }
  }).pipe(Effect.provide(TestLayer))
)

Integrating with Drizzle ORM — An Alternative Implementation

typescript

import { PgClient } from "@effect/sql-pg"
import { DrizzlePgClient } from "@effect/sql-drizzle/Pg"
import { eq } from "drizzle-orm"
import { pgTable, text, varchar } from "drizzle-orm/pg-core"
import { Config, Effect, Layer } from "effect"
 
const usersTable = pgTable("users", {
  id: varchar("id", { length: 36 }).primaryKey(),
  name: text("name").notNull(),
  email: text("email").notNull(),
})
 
const PgLive = PgClient.layerConfig({
  url: Config.string("DATABASE_URL"),
})
 
const DrizzleLive = DrizzlePgClient.layer.pipe(Layer.provide(PgLive))
 
// Drizzle implementation of UserRepository — an alternative to UserRepositoryLive
const UserRepositoryDrizzleLive = Layer.effect(
  UserRepository,
  Effect.gen(function* () {
    const db = yield* DrizzlePgClient
    return {
      findById: (id: string) =>
        Effect.gen(function* () {
          const rows = yield* db.select().from(usersTable).where(eq(usersTable.id, id))
          if (rows.length === 0) return yield* Effect.fail(new UserNotFoundError(id))
          return rows[0]
        }),
      findAll: () => db.select().from(usersTable),
      save: (user: User) =>
        db.insert(usersTable).values(user).pipe(Effect.map(() => undefined)),
    }
  })
)
 
// Final Drizzle-based layer — an alternative to AppLayer (the raw SQL version)
const AppLayerDrizzle = UserRepositoryDrizzleLive.pipe(Layer.provide(DrizzleLive))

Trade-off Analysis

When Is Effect-TS Worth Considering

Diagram 3

Area	Pros	Cons
Dependency validation	Missing dependencies caught at compile time	Layer composition has a learning curve
Error typing	Domain errors are explicit in function signatures	You must design error types yourself
Testability	Layer swapping eliminates the need for mocks	Initial cost of writing test layers
Concurrency	Fiber-based structured concurrency	Stack traces can be awkward to debug
Bundle size	`@effect/micro` available for edge environments	The core `effect` package itself has size
Learning curve	Consistent functional API, patterns repeat	Fiber, Layer, Cause, Schedule all at once

Common Mistakes in Practice

1. Creating ManagedRuntime on Every Request

typescript

// Wrong pattern — a new DB connection pool is created per request
app.get("/users", async (c) => {
  const runtime = ManagedRuntime.make(AppLayer) // ❌
  return c.json(await runtime.runPromise(getAllUsers))
})
 
// Correct pattern — created once in module scope
const AppRuntime = ManagedRuntime.make(AppLayer) // ✅
app.get("/users", async (c) => {
  return c.json(await AppRuntime.runPromise(getAllUsers))
})

2. Handling Promises Directly Inside an Effect Chain

typescript

// Compile error — await is a syntax error inside function*
const fetchUser = (id: string) =>
  Effect.gen(function* () {
    const user = await fetch(`/api/users/${id}`).then((r) => r.json()) // ❌ SyntaxError
    return user
  })
 
// Correct — lift the Promise into an Effect, then run it with yield*
const fetchUser = (id: string) =>
  Effect.tryPromise({
    try: () => fetch(`/api/users/${id}`).then((r) => r.json()),
    catch: (e) => new FetchError(e),
  })

Note that Effect.tryPromise is for async work that returns a Promise, while Effect.try is for synchronous work that may throw. They are separate APIs.

3. Overusing runSync When Partially Adopting Effect in an Existing Codebase

typescript

// Using runSync on an async Effect throws at runtime
const result = Effect.runSync(someAsyncEffect) // ❌
 
// Progressively convert the call stack to Effect, or define a clear boundary and escape with runPromise
const result = await Effect.runPromise(someAsyncEffect) // ✅

Closing Thoughts

Key takeaways:

Effect<A, E, R>: Encodes success value, error, and dependencies in a single type
Context.Tag: Identifies services in pure TypeScript without decorators
Layer: A recipe for composing services; Layer.provide progressively eliminates RIn to assemble the dependency graph
ManagedRuntime: An execution context that manages resource lifecycles — created once at the app level and reused
Layer-swap testing: Run the same logic in two environments without any mocking library

When you first encounter Effect, yield* and Layer.provide chains feel unfamiliar. Once the patterns click, they feel far more intuitive than the @Module and @Inject dance in NestJS.

If you're starting today, this is the recommended order:

Start with Effect.gen and Context.Tag: Rewrite one piece of existing business logic in Effect to get comfortable with yield* syntax and the three type parameters.
Write a test layer with Layer.succeed: Running the same logic without a real database immediately demonstrates the value of Layers.
Wire it into Hono with ManagedRuntime: Build a helper that maps errors to HTTP status codes using runPromiseExit, and the architecture is complete.

References

#Effect-TS#TypeScript#의존성 주입#Hono#Layer#Backend

Core Concepts

Effect's Three Type Parameters — One Line Says It All

Defining Services with Context.Tag

Layer — A Recipe for Composing Services

ManagedRuntime — Making a Layer Executable

Practical Application

Integrating with Hono

Test Isolation via Layer Swapping — No Mocking Required

Integrating with Drizzle ORM — An Alternative Implementation

Trade-off Analysis

When Is Effect-TS Worth Considering

Common Mistakes in Practice

Closing Thoughts

References

Core Concepts

Effect's Three Type Parameters — One Line Says It All

Defining Services with Context.Tag

Layer — A Recipe for Composing Services

ManagedRuntime — Making a Layer Executable

Practical Application

Integrating with Hono

Test Isolation via Layer Swapping — No Mocking Required

Integrating with Drizzle ORM — An Alternative Implementation

Trade-off Analysis

When Is Effect-TS Worth Considering

Common Mistakes in Practice

Closing Thoughts

References

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