"Serverless" refers to an architecture in which the infrastructure of your applications is managed by cloud providers. Contrary to its name, a serverless application does require a server but it doesn't require you to run and manage it on your own. Instead, you subscribe to a given cloud provider, such as AWS, Azure or GCP, and pay a subscription fee only for the resources you actually use. Since the resource allocation can be dynamic and depends on your current needs, the serverless model is particularly cost-effective when you want to implement a certain logic that is triggered on demand. Simply, you get your things done and don't pay for the infrastructure that sits idle.

Similarly to cloud providers, Kyma offers a service (known as "functions-as-a-service" or "FaaS") that provides a platform on which you can build, run, and manage serverless applications in Kubernetes. These applications are called Functions and are based on the Function CR objects. They are simple code snippets that implement the exact business logic you define in them. After you create a Function, you can:

  • Configure it to be triggered by events coming from external sources to which you subscribe.
  • Expose it to an external endpoint (HTTPS).


Serverless relies heavily on Kubernetes resources. It uses Deployments, Services and HorizontalPodAutoscalers to deploy and manage Functions, and Kubernetes Jobs to create Docker images. See how these and other resources process a Function within a Kyma cluster:

Serverless architecture

CAUTION: Serverless imposes some requirements on the setup of Namespaces. If you create a new Namespace, do not disable sidecar injection in it as Serverless requires Istio for other resources to communicate with Functions correctly. Also, if you apply custom LimitRanges for a new Namespace, they must be higher than or equal to the limits for building Jobs' resources.

  1. Create a Function either through the UI or by applying a Function custom resource (CR). This CR contains the Function definition (business logic that you want to execute) and information on the environment on which it should run.

    NOTE: Function Controller sets the Node.js 12 runtime by default.

  2. Before the Function can be saved or modified, it is first updated and then verified by the defaulting and validation webhooks respectively.

  3. Function Controller (FC) detects the new, validated Function CR.

  4. FC creates a ConfigMap with the Function definition.

  5. Based on the ConfigMap, FC creates a Kubernetes Job that triggers the creation of a Function image.

  6. The Job creates a Pod which builds the production Docker image based on the Function's definition. The Job then pushes this image to a Docker registry.

    NOTE: Serverless offers a built-in internal Docker registry that is suitable for local development. For production purposes, switch to an external Docker registry.

  7. FC monitors the Job status. When the image creation finishes successfully, FC creates a Deployment that uses the newly built image.

  8. FC creates a Service that points to the Deployment.

  9. FC creates a HorizontalPodAutoscaler that automatically scales the number of Pods in the Deployment based on the observed CPU utilization.

  10. FC waits for the Deployment to become ready.


Supported webhooks

A newly created or modified Function CR is first updated by the defaulting webhook and then verified by the validation webhook before the Function Controller starts to process it:

  1. Defaulting webhook sets the default values for CPU and memory requests and limits, and adds the maximum and the minimum number of replicas, if not specified already in the Function CR.

    ParameterDefault value
  2. Validation webhook checks if:

    • Minimum values requested for CPU, memory, and replicas are not lower than the required ones:
    ParameterRequired value
    • Requests are lower than or equal to limits, and the minimum number of replicas is lower than or equal to the maximum one.
    • The Function CR contains all the required parameters.
    • The format of deps, envs, labels, and the Function name (RFC 1035) is correct.
    • The Function CR contains any envs reserved for the Deployment: FUNC_RUNTIME, FUNC_HANDLER, FUNC_PORT, MOD_NAME, NODE_PATH.

Exposing Functions

To access a Function within the cluster, use the {function-name}.{namespace}.svc.cluster.local endpoint, such as test-function.default.svc.cluster.local. To expose a Function outside the cluster, you must create an APIRule custom resource (CR):

Expose a Function service

  1. Create the APIRule CR where you specify the Function to expose, define an Oathkeeper Access Rule to secure it, and list which HTTP request methods you want to enable for it.

  2. The API Gateway Controller detects a new APIRule CR and reads its definition.

  3. The API Gateway Controller creates an Istio Virtual Service and Access Rules according to details specified in the CR. Such a Function service is available under the {host-name}.{domain} endpoint, such as my-function.kyma.local.

This way you can specify multiple API Rules with different authentication methods for a single Function service.

TIP: See the tutorial for a detailed example.


To eliminate potential security risks when using Functions, bear in mind these few facts:

  • Kyma does not run any security scans against Functions and their images. Before you store any sensitive data in Functions, consider the potential risk of data leakage.

  • By default, JSON Web Tokens (JWTs) issued by Dex do not provide the scope parameter for Functions. This means that if you expose your Function and secure it with a JWT, you can use the token to validate access to all Functions within the cluster.

  • Kyma does not define any authorization policies that would restrict Functions' access to other resources within the Namespace. If you deploy a Function in a given Namespace, it can freely access all events and APIs of services within this Namespace.

  • All administrators and regular users who have access to a specific Namespace in a cluster can also access:

    • Source code of all Functions within this Namespace
    • Internal Docker registry that contains Function images

Function processing

From the moment you create a Function (Function CR) until the time it is ready, it goes through three processing stages that are defined as these condition types:

  1. ConfigurationReady (PrinterColumn CONFIGURED)
  2. BuildReady (PrinterColumn BUILT)
  3. Running (PrinterColumn RUNNING)

For a Function to be considered ready, the status of all three conditions must be True:

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test-function True True True 1 18m

When you update an existing Function, conditions change asynchronously depending on the change type.

The diagrams illustrate all three core status changes in the Function processing circle that the Function Controller handles. They also list all custom resources involved in this process and specify in which cases their update is required.

NOTE: Before you start reading, see the Function CR document for the custom resource detailed definition, the list of all Function's condition types and reasons for their success or failure.


This initial phase starts when you create a Function CR with configuration specifying the Function's setup. It ends with creating a ConfigMap that is used as a building block for a Function image.

Function configured


This phase involves creating and processing the Job CR. It ends successfully when the Function image is built and sent to the Docker registry. If the image already exists and only an update is required, the Docker image receives a new tag.

Updating an existing Function requires an image rebuild only if you change the Function's body (source) or dependencies (deps). An update of Function's other configuration details, such as environment variables, replicas, resources, or labels, does not require image rebuild as it only affects the Deployment.

NOTE: Each time you update Function's configuration, the Function Controller deletes all previous Job CRs for the given Function's UID.

Function built


This stage revolves around creating a Deployment, Service and HorizontalPodAutoscaler or updating them when configuration changes were made in the Function CR or the Function image was rebuilt.

In general, the Deployment is considered updated when both configuration and the image tag in the Deployment are up to date. Service and HorizontalPodAutoscaler are considered updated when there are proper labels set and configuration is up to date.

Thanks to the implemented reconciliation loop, the Function Controller constantly observes all newly created or updated resources. If it detects changes, it fetches the appropriate resource's status and only then updates the Function's status.

Function running


Environment variables

To configure the Serverless Function, override the default values of these environment variables:

Environment variableDescriptionUnitDefault value
FUNC_TIMEOUTSpecifies the number of seconds in which a runtime must execute the code.Number180
REQ_MB_LIMITSpecifies the payload body size limit in megabytes.Number1

See kubeless.js to get a deeper understanding of how the Express server, that acts as a runtime, uses these values internally to run Functions.

See the example of a Function with these environment variables set:

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kind: Function
name: sample-fn-with-envs
namespace: default
value: "2"
- name: REQ_MB_LIMIT
value: "10"
source: |
module.exports = {
main: function (event, context) {
return "Hello World!";

Serverless chart

To configure the Serverless chart, override the default values of its values.yaml file. This document describes parameters that you can configure.

TIP: To learn more about how to use overrides in Kyma, see the following documents:

Configurable parameters

This table lists the configurable parameters, their descriptions, and default values for both cluster and local installations.

ParameterDescriptionDefault valueMinikube override
containers.manager.envs.buildRequestsCPUNumber of CPUs requested by the image-building Pod to operate.700m100m
containers.manager.envs.buildRequestsMemoryAmount of memory requested by the image-building Pod to operate.700Mi200Mi
containers.manager.envs.buildLimitsCPUMaximum number of CPUs available for the image-building Pod to use.1100m200m
containers.manager.envs.buildLimitsMemoryMaximum amount of memory available for the image-building Pod to use.1100Mi400Mi

Custom Resource


The CustomResourceDefinition (CRD) is a detailed description of the kind of data and the format used to manage Functions within Kyma. To get the up-to-date CRD and show the output in the YAML format, run this command:

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kubectl get crd -o yaml

Sample custom resource

The following Function object creates a Function which responds to HTTP requests with the "Hello John" message.

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kind: Function
name: my-test-function
value: "John"
deps: |
"name": "hellowithdeps",
"version": "0.0.1",
"dependencies": {
"end-of-stream": "^1.4.1",
"from2": "^2.3.0",
"lodash": "^4.17.5"
app: my-test-function
minReplicas: 3
maxReplicas: 3
cpu: 1
memory: 1Gi
cpu: 500m
memory: 500Mi
source: |
module.exports = {
main: function(event, context) {
const name = process.env.PERSON_NAME;
return 'Hello ' + name;
- lastTransitionTime: "2020-04-14T08:17:11Z"
message: "Deployment my-test-function-nxjdp is ready"
reason: DeploymentReady
status: "True"
type: Running
- lastTransitionTime: "2020-04-14T08:16:55Z"
message: "Job my-test-function-build-552ft finished"
reason: JobFinished
status: "True"
type: BuildReady
- lastTransitionTime: "2020-04-14T08:16:16Z"
message: "ConfigMap my-test-function-xv6pc created"
reason: ConfigMapCreated
status: "True"
type: ConfigurationReady

CAUTION: When you create a Function, the exported object in the Function's body must have main as the handler name.

Custom resource properties

This table lists all the possible properties of a given resource together with their descriptions:

metadata.nameYesSpecifies the name of the CR.
metadata.namespaceNoDefines the Namespace in which the CR is available. It is set to default unless you specify otherwise.
spec.envNoSpecifies environment variables you need to export for the Function.
spec.depsNoSpecifies the Function's dependencies.
spec.labelsNoSpecifies the Function's Pod labels.
spec.minReplicasNoDefines the minimum number of Function's Pods to run at a time.
spec.maxReplicasNoDefines the maximum number of Function's Pods to run at a time.
spec.resources.limits.cpuNoDefines the maximum number of CPUs available for the Function's Pod to use.
spec.resources.limits.memoryNoDefines the maximum amount of memory available for the Function's Pod to use.
spec.resources.requests.cpuNoSpecifies the number of CPUs requested by the Function's Pod to operate.
spec.resources.requests.memoryNoSpecifies the amount of memory requested by the Function's Pod to operate.
spec.sourceYesProvides the Function's source code.
status.conditions.lastTransitionTimeNot applicableProvides a timestamp for the last time the Function's condition status changed from one to another.
status.conditions.messageNot applicableDescribes a human-readable message on the CR processing progress, success, or failure.
status.conditions.reasonNot applicableProvides information on the Function CR processing success or failure. See the Reasons section for the full list of possible status reasons and their descriptions. All status reasons are in camelCase.
status.conditions.statusNot applicableDescribes the status of processing the Function CR by the Function Controller. It can be True for success, False for failure, or Unknown if the CR processing is still in progress. If the status of all conditions is True, the overall status of the Function CR is ready.
status.conditions.typeNot applicableDescribes a substage of the Function CR processing. There are three condition types that a Function has to meet to be ready: ConfigurationReady, BuildReady, and Running. When displaying the Function status in the terminal, these types are shown under CONFIGURED, BUILT, and RUNNING columns respectively. All condition types can change asynchronously depending on the type of Function modification, but all three need to be in the True status for the Function to be considered successfully processed.

Status reasons

Processing of a Function CR can succeed, continue, or fail for one of these reasons:

ConfigMapCreatedConfigurationReadyA new ConfigMap was created based on the Function CR definition.
ConfigMapUpdatedConfigurationReadyThe existing ConfigMap was updated after changes in the Function CR name, its source code or dependencies.
JobFailedBuildReadyThe image with the Function's configuration could not be created due to an error.
JobCreatedBuildReadyThe Kubernetes Job resource that builds the Function image was created.
JobUpdatedBuildReadyThe existing Job was updated after changing the Function's metadata or spec fields that do not affect the way of building the Function image, such as labels.
JobRunningBuildReadyThe Job is in progress.
JobsDeletedBuildReadyPrevious Jobs responsible for building Function images were deleted.
JobFinishedBuildReadyThe Job was finished and the Function's image was uploaded to the Docker Registry.
DeploymentCreatedRunningA new Deployment referencing the Function's image was created.
DeploymentUpdatedRunningThe existing Deployment was updated after changing the Function's image, scaling parameters, variables, or labels.
DeploymentFailedRunningThe Function's Pod crashed or could not start due to an error.
DeploymentWaitingRunningThe Function was deployed and is waiting for the Deployment to be ready.
DeploymentReadyRunningThe Function was deployed and is ready.
ServiceCreatedRunningA new Service referencing the Function's Deployment was created.
ServiceUpdatedRunningThe existing Service was updated after applying required changes.
HorizontalPodAutoscalerCreatedRunningA new HorizontalPodScaler referencing the Function's Deployment was created.
HorizontalPodAutoscalerUpdatedRunningThe existing HorizontalPodScaler was updated after applying required changes.

The Function custom resource relies on these Kubernetes resources:

ConfigMapStores the Function's source code and dependencies.
JobBuilds an image with the Function's code in a runtime.
DeploymentServes the Function's image as a microservice.
ServiceExposes the Function's Deployment as a network service inside the Kubernetes cluster.
HorizontalPodAutoscalerAutomatically scales the number of Function's Pods.

These components use this CR:

Function ControllerUses the Function CR for the detailed Function definition, including the environment on which it should run.


Create a Function

This tutorial shows how you can create a simple "Hello World!" Function.


Follows these steps:

  • CLI
  • Console UI

Expose a Function with an API Rule

This tutorial shows how you can expose a Function to access it outside the cluster, through an HTTP proxy. To expose it, use an APIRule custom resource (CR) managed by the in-house API Gateway Controller. This controller reacts to an instance of the APIRule CR and, based on its details, it creates an Istio Virtual Service and Oathkeeper Access Rules that specify your permissions for the exposed Function.

When you complete this tutorial, you get a Function that:

  • Is available under an unsecured endpoint (handler set to noop in the APIRule CR).
  • Accepts GET, POST, PUT, and DELETE methods.

NOTE: To learn more about securing your Function, see the tutorial.


This tutorial is based on an existing Function. To create one, follow the Create a Function tutorial.


Follows these steps:

  • CLI
  • Console UI

Bind a Service Instance to a Function

This tutorial shows how you can bind a sample instance of the Redis service to a Function. After completing all steps, you will get the Function with encoded Secrets to the service. You can use them for authentication when you connect to the service to implement custom business logic of your Function.

To create the binding, you will use ServiceBinding and ServiceBindingUsage custom resources (CRs) managed by the Service Catalog.

NOTE: See the document on provisioning and binding to learn more about binding Service Instances to applications in Kyma.


This tutorial is based on an existing Function. To create one, follow the Create a Function tutorial.


Follows these steps:

  • CLI
  • Console UI

Test the Function

To test if the Secret has been properly connected to the Function:

  1. Change the Function's code to:​

    Click to copy
    module.exports = {
    main: function (event, context) {
    return "Redis port: " + process.env.REDIS_PORT;
  2. Expose the Function through an API Rule, and access the Function's external address. You should get this result:

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    Redis port: 6379

Trigger a Function with an event

This tutorial shows how to trigger a Function with an event from an Application connected to Kyma.

NOTE: To learn more about events flow in Kyma, read the eventing documentation.


This tutorial is based on an existing Function. To create one, follow the Create a Function tutorial.

You must also have:

  • An Application bound to a specific Namespace. Read the tutorials to learn how to create an Application and bind it to a Namespace.
  • An event service (an API of AsyncAPI type) registered in the desired Application. Read the tutorial to learn how to do it.
  • A Service Instance created for the registered service to expose events in a specific Namespace. Read the tutorial for details.


Follows these steps:

  • CLI
  • Console UI

Test the trigger

CAUTION: Before you follow steps in this section and send a sample event, bear in mind that it will be propagated to all services subscribed to this event type.

To test if the Trigger CR is properly connected to the Function:

  1. Change the Function's code to:​

    Click to copy
    module.exports = {
    main: function (event, context) {
    console.log("User created: ",;
  2. Send an event manually to trigger the function. The first example shows the implementation introduced with the Kyma 1.11 release where a CloudEvent is sent directly to the Event Mesh. In the second example, an event also reaches the Event Mesh, but it is first modified by the compatibility layer to the format compliant with the CloudEvents specification. This solution ensures compatibility if your events follow a format other than CloudEvents, or you use the Event Bus available before 1.11.

    TIP: For details on CloudEvents, exposed endpoints, and the compatibility layer, read about event processing and delivery.

    • Send CloudEvents directly to Event Mesh
    • Send events to Event Mesh through compatibility layer
    • CLUSTER_DOMAIN is the domain of your cluster, such as kyma.local.

    • CERT_FILE_NAME and KEY_FILE_NAME are client certificates for a given Application. You can get them by completing steps in the tutorial.

  3. After sending an event, you should get this result from logs of your Function's latest Pod:

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    User created: 123456789

Set an external Docker registry

By default, you install Kyma with Serverless that uses the internal Docker registry running on a cluster. This tutorial shows how to switch to an external Docker registry from one of these cloud providers using an override:


  • Docker Hub
  • GCR
  • ACR


Create required cloud resources

  • Docker Hub
  • GCR
  • ACR

Override Serverless configuration

Apply the following Secret with an override to a cluster or Minikube. Run:

  • Docker Hub
  • GCR
  • ACR

CAUTION: If you want to set an external Docker registry before you install Kyma, manually apply the Secret to the cluster before you run the installation script.

Trigger installation

Trigger Kyma installation or update it by labeling the Installation custom resource. Run:

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kubectl -n default label installation/kyma-installation action=install