Need guidance with production monitoring?
Book FREE office hours and we'll help you out
Not sure how to approach production monitoring? Book FREE office hours and we'll help you out

You are viewing documentation for an outdated version. Do you wish to see documentation for the latest version?

Core Concepts/Foundations

Context #

A Context is an immutable set of key-value pairs that contain state specific to the execution of a particular request in your application. Each request should have its own Context and all instrumentation and manual Context manipulation must ensure that Contexts from different requests are never mixed together.

The most common use case for a Context is to store additional request information like a request ID, user ID, user language or correlation IDs. If there are pieces of information that you would typically store in a ThreadLocal or the MDC, those are good candidates to be moved to Kamon’s Context. Additionally, Kamon uses the Context propagation mechanisms to carry around the tracer’s current Span.

Most of the time Kamon’s instrumentation will take care of creating, propagating and manipulating a Context for each request.

Keys #

Context keys are used to create new Context instances and to retrieve items from the Context. All keys encode four pieces of information required for Context propagation to work:

  • The key name. Key names must be unique and they will be used on configuration settings.
  • The scope, be it local or broadcast. Local Context keys will only be propagated within the process running the service while broadcast Context keys will be automatically propagated across process boundaries.
  • The value type. The return value of .get(...) calls is tied to the Key.
  • The default value. This is the value to be returned when retrieving a key that doesn’t exist in the Context.

Keys are created by calling the appropriate methods on the Key companion object:

  // Propagated in-process only
  val UserID = Key.local[String]("userID", "undefined")

  // Propagated in-process and across processes.
  val SessionID = Key.broadcast[Option[Int]]("sessionID", None)
  val RequestID = Key.broadcastString("requestID")

There are three keys defined in the example above:

  • UserID as a local key, with type String and a default value of "undefined". This key will always be propagated with the context within the same process.
  • SessionID as a broadcast key, with type Option[Int] and a default value of None. This key will always be propagated within the same process and across processes.
  • RequestID uses a shorter syntax for the very common case of having a broadcast key with type Option[String].

It is recommended (although not necessary) to create Context keys as static members and reuse the key instance wherever it is needed.

Manipulating a Context #

As mentioned above, Context instances are immutable. Adding a key-value pair to a Context is achieved by actually creating a new Context that includes or overrides a given key. Values can be retrieved by calling .get(key) on any Context instance:

  // Creating a Context with two keys
  val context = Context()
    .withKey(UserID, "1234")
    .withKey(SessionID, Some(42))

  // Reading values from a Context
  val userID: String = context.get(UserID)
  val sessionID: Option[Int] = context.get(SessionID)

  // The default value is returned for non-existent keys
  val requestID: Option[String] = context.get(RequestID)

Current Context and Scopes #

The current Context always refers to the Context associated with the request currently being executed and it can be accessed using the Kamon.currentContext() method. Once a Context is created for a given request it will be set as the current Context for a finite period of time, controlled by a Scope. When a Scope is closed the previously current Context is restored, which by default is Context.Empty.

The context storage works similar to Stack; every time you store a Context it becomes current, doing it several times will make the most recently stored context be the current (like the top of a stack) but as the associated scopes get closed, the previous contexts will become current again until eventually the current Context is Context.Empty again.

Effectively, the current Context is stored in a ThreadLocal but depending on the threading model of the frameworks and libraries used to build your service a Context might need to be made current on several threads and for brief periods of time. It is very important to close all created scopes timely, otherwise you risk leaving “dirty threads” that might cause subsequent requests to see a previous and completely unrelated Context as the current Context.

A Context instance can become the current context by using any of the following methods:

  • Kamon.storeContext(context) which returns a Scope instance that must be manually closed.
  • Kamon.withContext(context) { ... } which takes a Context instance and makes it current while the code block executes.
  • Kamon.withContextKey(key, value) { ... } creates a new Context by adding the provided key to the current Context and makes it current while the code block executes.
  • Kamon.withSpan(span) { ... } is similar to the above but explicitly works with the Span context Key.
  // From this moment on there is a current context
  val scope = Kamon.storeContext(context)

  // Closing the Scope returns the previously active context

  Kamon.withContext(context) {
    // Our context instance is the current Context

    Kamon.withContextKey(UserID, "5678") {
      // The current context has a overridden UserID key

It is recommended to use the Kamon.withXxx() variants as they will ensure that Scopes will be closed appropriately.

Codecs #

Codecs are used to encode and decode broadcast Context keys when crossing the process boundaries. There are two supported mediums for the codecs:

  • HTTP Headers: Each entry codec is able to write any number of HTTP headers to encode its state and read any number of HTTP headers to decode it. This medium is used in all HTTP frameworks instrumentation like Akka HTTP, Play Framework, Http4s, etc.
  • Binary: Each entry codec must be able to encode and decode a value from and to a ByteBuffer. This medium is used when a binary representation is more appropriate, like when sending messages to remote actor systems via Akka remoting or storing the Context in a message broker.

The codecs are configurable under the kamon.context.codecs section. Here is an extract from the default configuration which sets the codecs for propagating the tracer’s Span:

kamon.context.codecs {

  # Codecs to be used when propagating a Context through a HTTP Headers transport.
  http-headers-keys {
    span = "kamon.trace.SpanCodec$B3"

  # Codecs to be used when propagating a Context through a Binary transport.
  binary-keys {
    span = "kamon.trace.SpanCodec$Colfer"

Broadcast String Codecs #

Since broadcast strings are so simple (just String values) Kamon can automatically provide codecs for them in the case of binary mediums, but one additional piece of configuration is required for HTTP Headers: defining the header name to be used:

kamon.context.codecs {

  # If the application must read any of these keys it is necessary to create a
  # broadcast string key with a matching name and read the value from the context:
  # val requestIDKey = Key.broadcastString("request-id") // Do this only once, keep a reference.
  # val requestID = Kamon.currentContext().get(requestIDKey)
  string-keys {
    request-id = "X-Request-ID"

Custom Codecs #

When in need to create a custom codec the Codecs.ForEntry[T] trait must be implemented and the fully qualified class name for the implementation must be provided via configuration. The trait looks like the following:

  object Codecs {
    trait ForEntry[T] {
      def encode(context: Context): T
      def decode(carrier: T, context: Context): Context

A few important details to know when creating custom codecs:

  • The implementation class must have a no-parameters constructor.
  • A codec is responsible of encoding/decoding only one Context entry.
  • There are only two allowed types for T: TextMap and ByteBuffer.
  • The encode function might return an empty TextMap or ByteBuffer if the provided Context doesn’t contain the key that a codec is responsible for.
  • The decode function is expected to use the provided Context instance as a base for its return value. Typically a codec will try to read a value from the medium and either return the result of context.withKey(key, readValue) with the decoded value or simply return the provided Context if no value could be read.
On this article
Kamon APM Logo
Monitor and fix issues in production without being an expert
Learn about APM
Try Kamon APM I know how Kamon APM can help with monitoring. Don't show this again.