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Akka HTTP Interview Questions and Answers
Akka HTTP is a high-performance, scalable, and modular HTTP library built on the Akka toolkit, which is part of the Lightbend Reactive Platform. It provides both client-side and server-side HTTP functionalities and is designed to create reactive, asynchronous, and non-blocking applications in Scala and Java.
Key Features of Akka HTTP :
  1. Reactive Programming:

    • Built on Akka, it follows the principles of reactive streams and enables asynchronous, non-blocking communication.
  2. Server-Side and Client-Side APIs:

    • Server-Side: Easily build RESTful HTTP APIs or services.
    • Client-Side: Interact with external HTTP-based services.
  3. High Scalability and Performance:

    • Uses actor-based concurrency from Akka, making it suitable for handling a high volume of requests efficiently.
  4. Streaming Support:

    • Fully supports streaming of large data (e.g., files or continuous data streams).
  5. Modular Design:

    • Provides flexible components that can be used independently, including routing, unmarshalling, marshalling, and connection handling.
  6. Routing DSL:

    • Includes a declarative routing DSL for defining API endpoints in a clear and concise way.
  7. Integration with Akka Ecosystem:

    • Seamlessly integrates with Akka actors, streams, and Akka Typed, enabling tight coupling with the rest of the Akka toolkit.
  8. Lightweight:

    • Unlike traditional HTTP frameworks, Akka HTTP doesn't impose a large framework structure and can be used as a library in applications.
  9. Pluggable Components:

    • Easily extendable with custom logic, such as custom directives, unmarshallers, and marshallers.
Core Components of Akka HTTP :

Akka HTTP is designed around a set of modular components that work together to provide flexible, reactive, and high-performance HTTP functionalities. Here are its core components:

1. HTTP Model
  • Description: A set of immutable classes and objects representing HTTP requests, responses, headers, and entities.
  • Purpose: Provides a type-safe and consistent way to work with HTTP messages.
  • Key Elements:
    • HttpRequest: Represents an HTTP request.
    • HttpResponse: Represents an HTTP response.
    • HttpEntity: Encapsulates the body of a request or response.
    • Headers: Standard and custom headers like Authorization, Content-Type, etc.

Example :
val request = HttpRequest(uri = "/api/data")
val response = HttpResponse(entity = "Hello, Akka HTTP!")?

 

2. Routing DSL :
  • Description: A high-level declarative API for defining HTTP endpoints and handling requests.
  • Purpose: Simplifies creating RESTful APIs by abstracting HTTP handling logic.
  • Key Features:
    • Match HTTP methods (e.g., GET, POST).
    • Match paths or query parameters.
    • Process requests and send responses.

Example :
val route =
  path("hello") {
    get {
      complete("Hello, World!")
    }
  }?

 

3. Directives :
  • Description: Building blocks for routing logic, encapsulating common operations like path matching, header extraction, and request processing.
  • Purpose: Provide composable components for building routes.
  • Types of Directives:
    • Path Directives: Match specific paths (path, pathPrefix).
    • Method Directives: Match HTTP methods (get, post).
    • Header Directives: Extract headers (optionalHeaderValueByName).
    • Entity Directives: Extract and process request bodies (entity).
Example :
val route =
  path("user" / IntNumber) { userId =>
    get {
      complete(s"Fetching user with ID: $userId")
    }
  }?
4. Marshalling and Unmarshalling :
  • Description: Converting objects into HTTP entities (marshalling) and vice versa (unmarshalling).
  • Purpose: Enables serialization and deserialization of data (e.g., JSON, XML).
  • Common Libraries:
    • Akka HTTP integrates well with libraries like Spray JSON or Jackson.

Example :
import spray.json._
import akka.http.scaladsl.marshallers.sprayjson.SprayJsonSupport._

case class User(name: String, age: Int)
object UserJsonProtocol extends DefaultJsonProtocol {
  implicit val userFormat = jsonFormat2(User)
}

import UserJsonProtocol._

val route =
  path("createUser") {
    post {
      entity(as[User]) { user =>
        complete(s"Received user: ${user.name}")
      }
    }
  }?

 

5. Akka Streams :
  • Description: A reactive streams-based toolkit used for processing data streams asynchronously and non-blockingly.
  • Purpose: Enables streaming data handling in Akka HTTP, such as processing large files or continuous data streams.
  • Key Features:
    • Backpressure handling.
    • Easy integration with HTTP entities.

Example :
import akka.stream.scaladsl.Source
val numbers = Source(1 to 100)
val route =
  path("stream") {
    get {
      complete(numbers.map(_.toString))
    }
  }?
6. Connection Layer :
  • Description: The lower-level layer responsible for handling HTTP connections, requests, and responses.
  • Purpose: Provides direct control over the HTTP connection lifecycle.
  • Key Features:
    • Start an HTTP server.
    • Create HTTP clients for external API interactions.
  • Example: Starting a server.
import akka.http.scaladsl.Http
import akka.http.scaladsl.model._

val responseFuture = Http().singleRequest(HttpRequest(uri = "https://api.example.com/data"))?

 

7. Client-Side API :
  • Description: A high-level API for making HTTP requests to external services.
  • Purpose: Allows interaction with RESTful APIs or HTTP servers from Akka-based applications.
  • Key Features:
    • Send requests and receive responses.
    • Streaming and non-blocking support.

Example :
import akka.http.scaladsl.Http
import akka.http.scaladsl.model._

val responseFuture = Http().singleRequest(HttpRequest(uri = "https://api.example.com/data"))?
8. TestKit :
  • Description: Tools and utilities for testing Akka HTTP routes and applications.
  • Purpose: Simplifies writing unit tests for routes and APIs.
  • Key Features:
    • Simulate HTTP requests.
    • Validate responses and statuses.
Example :
import akka.http.scaladsl.testkit.ScalatestRouteTest
import org.scalatest.matchers.should.Matchers
import org.scalatest.wordspec.AnyWordSpec

class MyRouteTest extends AnyWordSpec with Matchers with ScalatestRouteTest {
  val route =
    path("test") {
      get {
        complete("Test successful")
      }
    }

  "The service" should {
    "return a successful response for GET /test" in {
      Get("/test") ~> route ~> check {
        responseAs[String] shouldEqual "Test successful"
      }
    }
  }
}?
Advantages of Akka HTTP :
  • Asynchronous and Non-Blocking: Handles a large number of requests with minimal resource usage.
  • High Performance: Suitable for real-time, high-throughput applications.
  • Scalable: Built on Akka's actor model, it easily scales horizontally and vertically.
  • Flexible and Modular: Offers components that can be used as needed, without a heavy framework overhead.
  • Streaming Support: Simplifies the handling of streaming data.
Disadvantages of Akka HTTP :
  • Steeper Learning Curve: Requires knowledge of Akka and functional programming concepts.
  • Verbose: Can be more verbose compared to some traditional HTTP frameworks.
  • Not a Full Framework: Unlike frameworks like Play or Spring, Akka HTTP is primarily a library, so additional setup may be required for larger projects.
Feature Akka HTTP Play Framework Spring Boot
Programming Model Reactive, modular library Full-stack reactive framework Full-stack MVC framework
Performance High (non-blocking I/O) High (non-blocking I/O) Moderate (blocking I/O)
Learning Curve Steep Moderate Easy
Streaming Built-in support (Akka Streams) Supported Limited
Reactive Streams is an initiative for asynchronous, non-blocking data streams with built-in backpressure. It defines a standard for processing and transferring data between components while ensuring that slower components don’t get overwhelmed by faster ones.

Akka HTTP uses Reactive Streams through Akka Streams, its implementation of the Reactive Streams API. In Akka HTTP, requests and responses are represented as streams of data. When a client sends a request to a server, it’s processed as a Source (producer) emitting elements to be consumed by a Sink (consumer). Backpressure is implemented by allowing the consumer to signal its demand for data to the producer. If the consumer can’t keep up, the producer slows down or buffers data until the consumer is ready.

This approach ensures efficient resource utilization and prevents system overloads, enabling high-performance and resilient applications.
Akka HTTP, Spray, and Play Framework are all Scala-based libraries for building web applications. Akka HTTP evolved from Spray, inheriting its core features while improving upon them. Play Framework is a full-stack framework, whereas Akka HTTP focuses on the server-side.

The main benefits of using Akka HTTP include :

1. Integration with Akka ecosystem : Akka HTTP seamlessly integrates with other Akka modules like Actors, Streams, and Clustering, enabling powerful concurrency and distribution capabilities.

2. Reactive streams : Akka HTTP implements reactive streams, allowing backpressure handling and non-blocking I/O operations, resulting in better resource utilization and performance.

3. Flexibility : Unlike Play Framework’s opinionated approach, Akka HTTP provides more flexibility in designing application architecture, making it suitable for various use cases.

4. Modularity : Akka HTTP offers a modular design, letting developers choose specific components needed for their projects without unnecessary overhead.

5. Testability : Built-in support for test-driven development simplifies testing of routes and services.

6. Lightweight : As a focused library, Akka HTTP has a smaller footprint compared to full-stack frameworks like Play, reducing complexity and startup time.
Akka HTTP is a toolkit for building REST APIs using Scala or Java. It provides an efficient, non-blocking I/O model and leverages the Actor system from Akka.

1. Define routes : Use the high-level routing DSL to define your API’s endpoints, specifying HTTP methods (GET, POST, etc.), paths, and request handling logic.

Example :
val route =
  path("users" / IntNumber) { userId =>
    get {
      complete(getUser(userId))
    } ~
    put {
      entity(as[User]) { user =>
        complete(updateUser(userId, user))
      }
    }
  }


2. Handle requests : Implement request handling logic in separate functions, typically involving actors for processing and returning results asynchronously.

Example :
def getUser(userId: Int): Future[HttpResponse] = {
  // Interact with actor(s) to fetch data
}
def updateUser(userId: Int, user: User): Future[HttpResponse] = {
  // Interact with actor(s) to update data
}?

3. Generate responses : Convert results into appropriate HTTP responses, including status codes and JSON serialization.

Example :
implicit val userFormat = jsonFormat3(User)
val jsonResponse = HttpResponse(entity = HttpEntity(ContentTypes.`application/json`, user.toJson.toString()))?

4. Start server : Bind the defined routes to a specific interface and port, starting the HTTP server.

Example :
Http().newServerAt("localhost", 8080).bind(route)?
To implement exception handling and custom error messages in an Akka HTTP application, follow these steps:

1. Define custom exception classes extending RuntimeException or another suitable base class.
2. Create a trait with a ExceptionHandler method that pattern matches on exceptions thrown within routes and maps them to appropriate HTTP responses containing meaningful information for clients.
3. Mix the trait into your main server object or route definition.
4. Use handleExceptions directive in your route definition to apply the custom exception handler.
class CustomException(msg: String) extends RuntimeException(msg)

trait CustomExceptionHandler {
  implicit def myExceptionHandler: ExceptionHandler =
    ExceptionHandler {
      case e: CustomException =>
        extractUri { uri =>
          log.error(s"Request to $uri failed with ${e.getMessage}")
          complete(HttpResponse(StatusCodes.BadRequest, entity = e.getMessage))
        }
    }
}

object MyServer extends App with CustomExceptionHandler {
  val route = handleExceptions(myExceptionHandler) {
    path("example") {
      throw new CustomException("Custom error message")
    }
  }

  Http().bindAndHandle(route, "localhost", 8080)
}?
Akka HTTP and Play Framework are both popular libraries in the Scala ecosystem for building web applications and APIs. However, they cater to different needs and have distinct design philosophies. Below is a detailed comparison :
1. Architecture and Design Philosophy :

Aspect Akka HTTP Play Framework
Core Design Modular and lightweight, designed as a low-level HTTP toolkit. Full-stack web framework for building web applications and APIs.
Reactive Model Built on Akka Streams for fully reactive, non-blocking processing. Built on Akka, but abstracts away streams and concurrency details.
Flexibility Gives fine-grained control over routing, request handling, and streams. Provides higher-level abstractions for rapid development with less boilerplate.
Use Case Ideal for developers needing granular control or custom HTTP services. Suitable for building full-featured web applications with MVC architecture.

2. Routing :
Aspect Akka HTTP Play Framework
Style Uses a declarative DSL for defining routes and HTTP behavior. Routes are defined in a configuration file (routes) or through controllers.
Flexibility Highly flexible, allowing dynamic and complex routing. Simpler, more structured routing with predefined conventions.
Example (Route) ```scala ```scala
```scala ```scala  
path("example") { GET /example controllers.Example.get  
Comparison Table: Akka HTTP vs. Play Framework :

Feature Akka HTTP Play Framework
Purpose Lightweight HTTP server and toolkit for building APIs and microservices. Full-stack web application framework for building large-scale web applications.
Architecture Modular and reactive, built on Akka Streams for fine-grained control. MVC-based, designed for rapid development with high-level abstractions.
Routing Declarative, code-based routing using a flexible DSL. Configuration-based routing using a routes file, integrated with controllers.
Ease of Use Requires more boilerplate and lower-level setup. Easier for beginners with predefined structure and conventions.
Learning Curve Steeper due to its low-level nature and fine-grained control. Moderate, as it provides higher-level abstractions and hides complexities.
Performance Optimized for high-performance, non-blocking HTTP processing. Performance is good but slightly less fine-tuned for low-level HTTP handling.
Streaming Support Built-in streaming capabilities using Akka Streams. Limited streaming support but sufficient for most standard use cases.
Integration Works well in microservices or as part of custom architectures. Strongly suited for web apps and systems with a defined MVC structure.
Flexibility Highly flexible, allowing developers to build from the ground up. Less flexible, but provides a well-defined structure for rapid development.
View Rendering No built-in view rendering; focuses only on HTTP handling. Provides support for templating engines like Twirl for server-side rendering.
Asynchronous Model Fully asynchronous and non-blocking, leveraging Akka Streams. Asynchronous by default, using Akka under the hood but abstracted for developers.
WebSocket Support Robust WebSocket support with fine-grained control. Provides WebSocket support but with less customization compared to Akka HTTP.
Dependency Injection No built-in DI; developers must integrate libraries like Guice or MacWire. Built-in support for dependency injection (Guice is the default).
Testing Offers ScalatestRouteTest for fine-grained testing of HTTP routes. Provides built-in testing tools for controllers, routes, and forms.
Community and Ecosystem Smaller but focused community with emphasis on Akka-based solutions. Larger community with plugins and tools for web application development.
Use Cases - Microservices

The role of Akka Streams in Akka HTTP is fundamental, as Akka HTTP leverages Akka Streams to handle and process HTTP requests and responses in a reactive, non-blocking, and backpressure-aware manner. Here's an overview of its role:

1. Reactive Data Processing :

Akka HTTP relies on Akka Streams to manage the flow of data through HTTP connections. This ensures:

  • Non-blocking behavior: Data is processed asynchronously without threads waiting for operations to complete.
  • Backpressure support: When a consumer (e.g., a client) cannot process data quickly, Akka Streams ensures the producer (e.g., the server) slows down to avoid overwhelming the consumer.
  •  
2. Handling HTTP Request/Response Entities :

HTTP entities (like request bodies and response payloads) are modeled as Akka Streams Source. This allows streaming large data efficiently:

  • Request Entity: HttpRequest bodies are exposed as a Source[ByteString, Any], enabling streaming and processing large payloads without loading the entire content into memory.
  • Response Entity: HttpResponse bodies can be constructed using a Source[ByteString, Any], allowing you to stream data directly to clients.
val route = path("stream") {
  get {
    val dataStream = Source(1 to 100).map(num => ByteString(s"$num\n"))
    complete(HttpResponse(entity = HttpEntity(ContentTypes.`text/plain(UTF-8)`, dataStream)))
  }
}?

3. Streaming WebSockets :

Akka Streams powers WebSocket support in Akka HTTP, allowing for bi-directional streaming communication between the server and clients. WebSocket messages are modeled as Akka Streams Flow objects, enabling real-time data exchange with backpressure handling.

Example :

val webSocketFlow: Flow[Message, Message, Any] = Flow[Message].map {
  case TextMessage.Strict(text) => TextMessage(s"Echo: $text")
  case _ => TextMessage("Unsupported message type")
}

val route = path("ws") {
  handleWebSocketMessages(webSocketFlow)
}
4. Composition of Directives :

Akka HTTP directives (e.g., mapAsync, entity, extractDataBytes) work seamlessly with Akka Streams to compose reactive pipelines for processing requests and responses.

Example :

val route = path("upload") {
  post {
    entity(asSourceOf[ByteString]) { byteSource =>
      val lineCountFuture = byteSource
        .via(Framing.delimiter(ByteString("\n"), maximumFrameLength = 256, allowTruncation = true))
        .runFold(0)((count, _) => count + 1)

      onSuccess(lineCountFuture) { lineCount =>
        complete(s"Uploaded file contains $lineCount lines")
      }
    }
  }
}

5. Efficient Connection Management :

Akka Streams provides efficient handling of TCP connections, which is vital for HTTP server and client operations:

  • Manages concurrent connections without blocking.
  • Ensures scalability by leveraging Akka’s actor model and stream processing.

6. Transformations and Pipelines :

With Akka Streams, you can apply transformations to the data as it flows through the HTTP pipeline:

  • Filtering: Removing unwanted data.
  • Mapping: Transforming data (e.g., decoding JSON or processing text).
  • Aggregation: Combining multiple data elements into one (e.g., counting or reducing).

 

Akka Streams provides a declarative, compositional API for working with streaming data. Its integration into Akka HTTP makes it a powerful choice for:

  1. Scalability: Handle a large number of concurrent requests.
  2. Resource Efficiency: Avoid overloading resources with backpressure.
  3. Streaming Applications: Ideal for real-time applications like data feeds, video/audio streaming, or analytics pipelines.
When implementing authentication and authorization in Akka HTTP, consider the following best practices:

1. Use built-in directives : Leverage Akka HTTP’s built-in directives like authenticateBasic, authenticateOAuth2, or authorize to handle common scenarios.

2. Separate concerns : Keep authentication and authorization logic separate from business logic for maintainability and testability.

3. Stateless approach : Prefer stateless mechanisms like JWT tokens to avoid server-side session management overhead.

4. Secure communication : Ensure secure transport using HTTPS to prevent credentials interception.

5. Validate input : Sanitize user inputs to protect against injection attacks.

6. Error handling : Provide clear error messages without revealing sensitive information about the system.

7. Scalability : Design with scalability in mind, considering token revocation and distributed systems.

In Akka HTTP, routes define how incoming HTTP requests are handled by your application. A route maps an HTTP request (based on its method, URI, headers, or body) to a specific action, such as returning a response or invoking application logic. Routes form the backbone of an Akka HTTP application, enabling the definition of endpoints and their associated behavior.

Key Features of Routes :
  1. Declarative DSL: Routes in Akka HTTP are defined using a concise, declarative Domain-Specific Language (DSL) provided by the library.

  2. Composability: Routes can be combined hierarchically, allowing for reusable and modular definitions of complex routing logic.

  3. Pattern Matching: Routes support pattern matching for HTTP methods (e.g., GET, POST), paths, query parameters, headers, and even request entities.

  4. Integration with Directives: Akka HTTP provides powerful directives, which are building blocks used to create routes by defining how requests are processed.

Directives in Routes :

Routes rely on directives, which are composable building blocks used to define behavior. Examples include:

  • path: Matches a specific URI path.
  • get, post, etc.: Matches HTTP methods.
  • parameter: Extracts query parameters.
  • headerValueByName: Extracts headers.
  • entity: Extracts and processes the request body.

In Akka HTTP, the path and pathPrefix directives are used to match and handle parts of the request URI. While both are involved in routing based on the path, they differ in how they match and handle the URI. Here's a detailed comparison:

1. path Directive :

The path directive is used to match exact path segments in the URI. It requires the entire remaining path to match exactly, with no additional segments allowed unless explicitly defined.

Key Characteristics:

  • Matches the exact path specified.
  • Does not allow additional segments after the match.
  • Commonly used for specific, well-defined routes.

Example :

val route = path("users") {
  complete("Users endpoint")
}
?
2. pathPrefix Directive :

The pathPrefix directive is used to match the beginning (prefix) of a path. It allows additional segments in the URI after the matched prefix, which can be handled by nested routes.

Key Characteristics:

  • Matches the specified prefix and allows the remaining path to be processed by child directives or routes.
  • Ideal for grouping routes under a common base path.

Example :

val route = pathPrefix("users") {
  path("create") {
    complete("Create user")
  } ~
  path(IntNumber) { userId =>
    complete(s"Details for user $userId")
  }
}?
Akka HTTP’s Media Types define the format of data exchanged between client and server, while Content Negotiation allows clients to request specific media types. The server selects the best matching response based on available formats.

Media Types are represented as objects with a main type (e.g., “application”) and a subtype (e.g., “json”). They can have parameters like charset for text-based types. Akka HTTP provides predefined media types and supports custom ones.

Content Negotiation involves two headers : Accept from the client, indicating desired media types, and Content-Type from the server, specifying the chosen format. Clients may provide multiple acceptable types with quality factors (q-values) to indicate preference.

Use case – Media Types : An API returns JSON or XML depending on the endpoint. Define custom media types for each:
val jsonType = MediaType.applicationWithFixedCharset("custom-json", HttpCharsets.`UTF-8`)
val xmlType = MediaType.applicationWithFixedCharset("custom-xml", HttpCharsets.`UTF-8`)?


Use case – Content Negotiation : A client requests an image in JPEG or PNG format, preferring JPEG. Server responds with the appropriate format:
Client header : Accept: image/jpeg;q=0.9, image/png;q=0.8

Server code :

import akka.http.scaladsl.model._
import MediaTypes._
val imageData: Array[Byte] = ...
val contentType = if (request.header[headers.Accept].exists(_.mediaRanges.exists(_.matches(`image/jpeg`)))) {
  ContentType(`image/jpeg`)
} else {
  ContentType(`image/png`)
}
HttpResponse(entity = HttpEntity(contentType, imageData))?
Akka HTTP utilizes a connection pool to manage multiple concurrent connections, improving performance and resource utilization. The host-level API manages the pool, automatically reusing idle connections or creating new ones as needed.

To optimize performance, configure client connection settings in the application.conf file or programmatically using ConnectionPoolSettings. Key parameters include:

1. max-connections : Maximum number of connections per target endpoint; increase for high concurrency.

2. min-connections : Minimum number of connections kept alive; adjust based on expected load.

3. max-retries : Number of retries for failed requests; balance between resilience and response time.

4. idle-timeout : Duration before closing idle connections; decrease to free resources faster or increase to reduce connection overhead.

5. pipelining-limit : Maximum number of requests sent over a single connection concurrently; set higher if server supports HTTP pipelining.

6. response-entity-subscription-timeout : Timeout for consuming response entities; tune according to expected response times.
Example :
akka.http.host-connection-pool {
  max-connections = 50
  min-connections = 10
  max-retries = 3
  idle-timeout = 30s
  pipelining-limit = 2
  response-entity-subscription-timeout = 15s
}?
When developing an Akka HTTP-based microservice, consider these performance tuning and optimization techniques :

1. Connection Pooling : Utilize connection pools to manage multiple connections efficiently, reducing overhead and improving throughput.

2. Pipelining : Enable request pipelining to send multiple requests without waiting for responses, increasing concurrency.

3. Tuning Dispatcher : Configure the dispatcher thread pool size based on available resources and workload requirements.

4. Stream Processing : Use Akka Streams for backpressure control and efficient resource utilization during data processing.

5. Caching : Implement caching strategies to reduce latency and avoid redundant computations or network calls.

6. Monitoring and Metrics : Collect metrics using tools like Kamon or Lightbend Telemetry to identify bottlenecks and optimize accordingly.
To create unit tests and integration tests for a server-side application using Akka HTTP’s testing facilities, follow these steps :

1. Add dependencies : Include “akka-http-testkit” in your build configuration to access the required libraries.

2. Unit Testing : For testing individual routes, use the RouteTest trait which provides methods like Get, Post, etc., to send requests to the route. Use assertions with the check method to verify responses.

Example :
class MyRoutesSpec extends WordSpec with Matchers with ScalatestRouteTest {
  val myRoutes = new MyRoutes().routes
  "MyRoutes" should {
    "return a greeting" in {
      Get("/greet") ~> myRoutes ~> check {
        responseAs[String] shouldEqual "Hello!"
      }
    }
  }
}?

3. Integration Testing : To test the entire server, use HttpApp or HttpServerTest. Start the server before tests and stop it after completion. Send requests using an HTTP client like Http() and validate responses.

Example :
class MyServerSpec extends WordSpec with Matchers with BeforeAndAfterAll {
  val server = new MyServer()
  implicit val system = ActorSystem("test-system")
  override def beforeAll(): Unit = server.start()
  override def afterAll(): Unit = server.stop()
  "MyServer" should {
    "return a greeting" in {
      Http().singleRequest(HttpRequest(uri = "http://localhost:8080/greet")).map { response =>
        response.status shouldEqual StatusCodes.OK
        Unmarshal(response.entity).to[String].map(_ shouldEqual "Hello!")
      }
    }
  }
}?
Akka HTTP supports asynchronous processing through its non-blocking, event-driven architecture. It utilizes the Actor model and Akka Streams to handle concurrent requests efficiently without blocking threads. This approach enables high throughput and low latency, as opposed to traditional blocking I/O processing where each request occupies a thread until completion, leading to limited scalability and potential performance bottlenecks.

In Akka HTTP, Actors process incoming requests by exchanging messages with other Actors, allowing for parallelism and fault tolerance. Akka Streams provide backpressure mechanisms to prevent overwhelming downstream components, ensuring smooth data flow and resource management.

The main difference between Akka HTTP’s asynchronous processing and traditional blocking I/O lies in their handling of concurrency. While blocking I/O relies on thread-per-request model, consuming resources and limiting scalability, Akka HTTP leverages the Actor model and reactive streams to achieve efficient, non-blocking processing that scales well under heavy loads.
In Akka HTTP, directives and routes are essential components for building web services. Directives define reusable pieces of route logic, encapsulating request handling and response generation. Routes are tree-like structures composed of directives that match incoming requests to appropriate handlers.

Directives can be nested and combined using combinators, allowing complex routing logic with minimal code. Custom directives can be created by extending existing ones or implementing new functionality. To implement a custom directive, define a function that takes necessary parameters and returns a Directive instance.

Example : A custom directive to validate an API key :
import akka.http.scaladsl.server.Directive1
import akka.http.scaladsl.server.directives._
def apiKeyValidation(apiKey: String): Directive1[String] = {
  val validApiKey = "my-secret-key"
  if (apiKey == validApiKey) provide(apiKey)
  else reject(AuthorizationFailedRejection)
}
val route =
  path("secure") {
    headerValueByName("api-key") { apiKey =>
      apiKeyValidation(apiKey) { _ =>
        complete("Authorized access")
      }
    }
  }?

This custom directive checks if the provided API key matches the valid one and either provides it downstream or rejects the request with an AuthorizationFailedRejection.
To create and consume WebSocket APIs using Akka HTTP, follow these steps :

1. Define routes : Create a route that handles WebSocket requests using the handleWebSocketMessages directive.

2. Implement message handling : Use actors or flows to process incoming messages and generate responses.

3. Establish connection : Clients connect to the WebSocket API by sending an HTTP request with an “Upgrade” header.

Example use case : A real-time chat application can utilize Akka HTTP WebSockets for efficient communication between clients and server. The server defines a route for WebSocket connections, processes incoming text messages from clients, broadcasts them to all connected users, and sends acknowledgements back to the sender.
In Akka HTTP, file uploads and streaming are handled using the “fileUpload” directive and reactive streams. To handle a file upload, extract the uploaded file’s metadata and data bytestring from the request entity. Then, use Sink to write the bytestring into a local file or another storage system.

For large file transfers, implement support for chunked transfer encoding and multipart file uploads. This allows splitting files into smaller parts, enabling efficient memory usage and parallel processing.

Challenges faced when implementing large file transfers include :

1. Memory consumption : Large files can consume significant memory if not properly managed.

2. Timeouts : Long-running connections may lead to timeouts, requiring proper configuration of idle-timeout settings.

3. Backpressure : Ensure backpressure is correctly implemented to prevent overwhelming the server with incoming data.

4. Error handling : Robust error handling is necessary to recover from failures during file transfer.

5. Security : Protect against malicious attacks such as denial-of-service or uploading harmful content.

6. Scalability : Design the system to scale horizontally to accommodate increasing load.
To secure an Akka HTTP application beyond basic authentication and session management, consider the following options :

1. HTTPS : Enable SSL/TLS encryption for data transmission to protect sensitive information from eavesdropping or tampering.

2. CORS : Implement Cross-Origin Resource Sharing policies to control which domains can access your API, preventing unauthorized cross-domain requests.

3. CSRF Protection : Add anti-CSRF tokens to forms and validate them server-side to prevent Cross-Site Request Forgery attacks.

4. Content Security Policy (CSP) : Define a CSP header to restrict sources of content like scripts, images, and styles, mitigating XSS vulnerabilities.

5. Rate Limiting : Apply rate limiting on API endpoints to prevent abuse and denial-of-service attacks.

6. Input Validation : Validate user input on both client and server sides to avoid injection attacks and ensure data integrity.

7. Dependency Management : Regularly update dependencies and use tools like Snyk or OWASP Dependency-Check to identify known security vulnerabilities.
To automatically convert between domain models and JSON using Akka HTTP’s marshalling capabilities, follow these steps:

1. Add necessary dependencies : Include “akka-http-spray-json” and “spray-json” in your build configuration.

2. Import required packages : Import “akka.http.scaladsl.marshallers.sprayjson.SprayJsonSupport” and “spray.json.DefaultJsonProtocol”.

3. Define case classes : Create case classes representing your domain model.

4. Implement JsonFormat instances : Extend “DefaultJsonProtocol” and define implicit values for each case class using “jsonFormatX” methods, where X is the number of fields in the case class.

5. Mixin SprayJsonSupport : In the route definition or marshaller/unmarshaller scope, mixin “SprayJsonSupport” to enable automatic conversion.

6. Use directives : Utilize “entity(as[T])” directive for unmarshalling (JSON to domain model) and “complete()” directive with a case class instance for marshalling (domain model to JSON).

Example :
import akka.http.scaladsl.marshallers.sprayjson.SprayJsonSupport._
import spray.json.DefaultJsonProtocol._
case class User(name: String, age: Int)
object UserJsonProtocol extends DefaultJsonProtocol {
  implicit val userFormat = jsonFormat2(User)
}
import UserJsonProtocol._
val route =
  path("users") {
    post {
      entity(as[User]) { user =>
        complete(user)
      }
    }
  }?
Akka HTTP supports server-sent events (SSE) through its streaming capabilities and the akka.http.scaladsl.model.sse.ServerSentEvent class. SSE enables efficient real-time communication between a server and clients by pushing updates to clients over a single, long-lived connection.

A use case for employing SSE with Akka HTTP is a live sports score update system. In this scenario, the server continuously sends updated scores and game information to connected clients without requiring them to repeatedly request updates. This reduces latency and improves user experience while minimizing server load.

Example code snippet :
import akka.http.scaladsl.Http
import akka.http.scaladsl.model.StatusCodes
import akka.http.scaladsl.model.sse.ServerSentEvent
import akka.http.scaladsl.server.Directives._
import akka.stream.scaladsl.Source
val route =
  path("scores") {
    get {
      complete {
        HttpEntity(
          ContentTypes.`text/event-stream`,
          Source.fromPublisher(scoreUpdates)
            .map(ServerSentEvent(_))
            .keepAlive(1.second, () => ServerSentEvent.heartbeat)
        )
      }
    }
  }
Http().bindAndHandle(route, "localhost", 8080)?
To deploy an Akka HTTP application using containerization, follow these steps:

1. Create a Dockerfile : Define the base image (e.g., openjdk), copy your application’s JAR file into the image, and set the entry point to run the application.
FROM openjdk:8-jre
COPY target/scala-2.12/my-akka-http-app.jar /app/
CMD ["java", "-jar", "/app/my-akka-http-app.jar"]?

2. Build the Docker image : Run docker build -t my-akka-http-app . in the terminal.

3. Push the image to a container registry : Tag the image with the registry URL (e.g., docker tag my-akka-http-app myregistry.com/my-akka-http-app) and push it (docker push myregistry.com/my-akka-http-app).

4. Deploy using Kubernetes : Create a deployment YAML file defining the desired number of replicas, the container image, and any necessary environment variables or configurations.
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-akka-http-app
spec:
  replicas: 3
  template:
    metadata:
      labels:
        app: my-akka-http-app
    spec:
      containers:
      - name: my-akka-http-app
        image: myregistry.com/my-akka-http-app
        ports:
        - containerPort: 8080?

5. Apply the deployment : Use kubectl apply -f my-akka-http-app-deployment.yaml.

6. Expose the service : Create a service YAML file to expose the deployment externally, then use kubectl apply -f my-akka-http-app-service.yaml.
apiVersion: v1
kind: Service
metadata:
  name: my-akka-http-app
spec:
  selector:
    app: my-akka-http-app
  ports:
    - protocol: TCP
      port: 80
      targetPort: 8080
  type: LoadBalancer?
Akka HTTP manages timeouts using various configurations. For request timeouts, it uses akka.http.server.request-timeout setting, which defines the maximum duration a request can take before being automatically rejected. Connection timeouts are managed by akka.http.client.connecting-timeout, determining how long to wait for establishing a connection.

For long-lived or streaming connections, Akka HTTP provides support through its reactive streams implementation. To handle these connections, you can use Source and Sink components from Akka Streams API, allowing backpressure control and efficient resource management. Additionally, you can disable request timeout for specific routes using withoutRequestTimeout directive or increase idle timeout settings (akka.http.[server/client].idle-timeout) to accommodate longer durations.
When choosing between connection-level and host-level APIs in Akka HTTP for clients, consider the following factors :

1. Connection Pooling : Host-level API provides built-in connection pooling, efficiently managing multiple connections to a single target endpoint. For high-throughput scenarios or when targeting multiple endpoints, use host-level API.

2. Request Routing : Connection-level API requires manual management of connections, making it suitable for simple use cases with direct control over request routing.

3. Connection Lifecycle : With connection-level API, you have more control over connection lifecycle, allowing precise handling of connection establishment, termination, and timeouts.

4. Load Balancing : Host-level API automatically handles load balancing across multiple connections, while connection-level API requires custom implementation for distributing requests.

5. Failure Handling : Host-level API offers better failure handling by retrying requests on different connections if one fails. Connection-level API needs explicit error handling strategies.

6. Complexity : Connection-level API is simpler and easier to understand but lacks advanced features provided by host-level API. Choose based on your application’s requirements and desired level of abstraction.
30 .
What is the purpose of complete in Akka HTTP?

The complete directive in Akka HTTP is used to terminate the processing of a route and generate an HTTP response that is sent back to the client. It is a core directive that allows you to specify the content of the response, including the status code, headers, and the response entity (body).

Key Purposes of complete :
  1. Send HTTP Responses

    • The complete directive provides a way to return a response to the client, whether it's a simple string, a JSON object, or a full HttpResponse object.
  2. Terminate Route Handling

    • Once the complete directive is executed, no further processing is done for that route.
  3. Flexible Response Generation

    • It supports a wide variety of response types, including plain strings, custom status codes, objects (like JSON), and even streamed responses.
In Akka Streams, parallelism and concurrency can be achieved through various methods such as asynchronous boundaries, mapAsync, and substreams.

1. Asynchronous Boundaries : Introduce async boundaries using .async() to allow different stages of the stream to run concurrently on separate threads. Applicable when independent stages have significant processing time.

2. MapAsync : Use mapAsync or mapAsyncUnordered for concurrent execution of a function with multiple input elements. Suitable when applying an expensive operation to each element in the stream.

3. Substreams : Partition the main stream into smaller streams (substreams) using groupBy or splitWhen/After, process them concurrently, and merge back using mergeSubstreams or concatSubstreams. Ideal for scenarios where data can be processed independently within partitions.

4. Balancing workload : Utilize balance and merge components to distribute work evenly across multiple workers and combine their results. Useful when dealing with varying processing times for different elements.

5. Throttling : Control the rate of processing by limiting the number of elements processed per unit of time using throttle. Helps prevent overwhelming downstream systems.

6. Buffering : Manage backpressure by buffering elements between stages using buffer or conflate. Can improve performance when there’s a mismatch in processing speeds between stages.