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+++ title = "Cluster" description = "Guidance & requirements for running KEDA in your cluster" weight = 100 +++

Requirements

Kubernetes

KEDA is designed, tested and supported to be run on any Kubernetes cluster that runs Kubernetes v1.17.0 or above.

Cluster Capacity

The KEDA runtime require the following resources in a production-ready setup:

Deployment CPU Memory
Metrics Server Limit: 1, Request: 100m Limit: 1000Mi, Request: 100Mi
Operator Limit: 1, Request: 100m Limit: 1000Mi, Request: 100Mi

These are used by default when deploying through YAML.

💡 For more info on CPU and Memory resource units and their meaning, see this link.

Firewall

KEDA requires to be accessible inside the cluster to be able to autoscale.

Here is an overview of the required ports that need to be accessible for KEDA to work:

Port Why? Remarks
443 Used by Kubernetes API server to get metrics Required for all platforms because it uses Control Plane → port 443 on the Service IP range communication. This is not applicable for Google Cloud.
6443 Used by Kubernetes API server to get metrics Only required for Google Cloud because it uses Control Plane → port 6443 on the Pod IP range for communication

High Availability

KEDA does not provide full support for high-availability due to upstream limitations.

Here is an overview of all KEDA deployments and the HA notes:

Deployment Support Replicas Note
Metrics Server 1 You can run multiple replicas of our metrics sever, and it is recommended to add the --enable-aggregator-routing=true CLI flag to the kube-apiserver so that requests sent to our metrics servers are load balanced. However, you can only run one active metric server in a Kubernetes cluster serving external.metrics.k8s.io which has to be the KEDA metric server.
Operator 2 While you can run multiple replicas of our operator, only one operator instance will be active. The rest will be standing by, which may reduce downtime during a failure. Multiple replicas will not improve the performance of KEDA, it could only reduce a downtime during a failover.

HTTP Timeouts

Some scalers issue HTTP requests to external servers (i.e. cloud services). Each applicable scaler uses its own dedicated HTTP client with its own connection pool, and by default each client is set to time out any HTTP request after 3 seconds.

You can override this default by setting the KEDA_HTTP_DEFAULT_TIMEOUT environment variable to your desired timeout in milliseconds. For example, on Linux/Mac/Windows WSL2 operating systems, you'd use this command to set to 1 second:

export KEDA_HTTP_DEFAULT_TIMEOUT=1000

And on Windows Powershell, you'd use this command:

$env:KEDA_HTTP_DEFAULT_TIMEOUT=1000

All applicable scalers will use this timeout. Setting a per-scaler timeout is currently unsupported.

Kubernetes Client Parameters

The Kubernetes client config used within KEDA Metrics Adapter can be adjusted by passing the following command-line flags to the binary:

Adapter Flag Client Config Setting Default Value Description
kube-api-qps cfg.QPS 20.0 Set the QPS rate for throttling requests sent to the apiserver
kube-api-burst cfg.Burst 30 Set the burst for throttling requests sent to the apiserver

Configure MaxConcurrentReconciles for Controllers

To implement internal controllers KEDA uses controller-runtime project, that enables configuration of MaxConcurrentReconciles property, ie. the maximum number of concurrent reconciles which can be run for a controller.

KEDA Operator exposes properties for specifying MaxConcurrentReconciles for following controllers/reconcilers:

  • ScaledObjectReconciler - responsible for watching and managing ScaledObjects, ie. validates input trigger specification, starts scaling logic and manages dependent HPA.
  • ScaledJobReconciler - responsible for watching and managing ScaledJobs and dependent Kubernetes Jobs

KEDA Metrics Server exposes property for specifying MaxConcurrentReconciles for MetricsScaledObjectReconciler, that manages Metrics Names exposes by KEDA and which are being consumed by Kubernetes server and HPA controller.

To modify this properties you can set environment variables on both KEDA Operator and Metrics Server Deployments:

Environment variable name Deployment Default Value Affected reconciler
KEDA_SCALEDOBJECT_CTRL_MAX_RECONCILES Operator 5 ScaledObjectReconciler
KEDA_SCALEDJOB_CTRL_MAX_RECONCILES Operator 1 ScaledJobReconciler
KEDA_METRICS_CTRL_MAX_RECONCILES Metrics Server 1 MetricsScaledObjectReconciler