--- title: Scale your InfluxDB cluster description: > InfluxDB Clustered lets you scale individual components of your cluster both vertically and horizontally to match your specific workload. menu: influxdb3_clustered: parent: Administer InfluxDB Clustered name: Scale your cluster weight: 207 influxdb3/clustered/tags: [scale] related: - /influxdb3/clustered/reference/internals/storage-engine/ - https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#requests-and-limits, Kubernetes resource requests and limits --- InfluxDB Clustered lets you scale individual components of your cluster both vertically and horizontally to match your specific workload. Use the `AppInstance` resource defined in your `influxdb.yml` to manage resources available to each component. - [Scaling strategies](#scaling-strategies) - [Vertical scaling](#vertical-scaling) - [Horizontal scaling](#horizontal-scaling) - [Scale components in your cluster](#scale-components-in-your-cluster) - [Horizontally scale a component](#horizontally-scale-a-component) - [Vertically scale a component](#vertically-scale-a-component) - [Apply your changes](#apply-your-changes) - [Scale your cluster as a whole](#scale-your-cluster-as-a-whole) - [Recommended scaling strategies per component](#recommended-scaling-strategies-per-component) - [Ingester](#ingester) - [Querier](#querier) - [Router](#router) - [Compactor](#compactor) - [Garbage collector](#garbage-collector) - [Catalog](#catalog) - [Object store](#object-store) ## Scaling strategies The following scaling strategies can be applied to components in your InfluxDB cluster. ### Vertical scaling Vertical scaling (also known as "scaling up") involves increasing the resources (such as RAM or CPU) available to a process or system. Vertical scaling is typically used to handle resource-intensive tasks that require more processing power. {{< html-diagram/scaling-strategy "vertical" >}} ### Horizontal scaling Horizontal scaling (also known as "scaling out") involves increasing the number of nodes or processes available to perform a given task. Horizontal scaling is typically used to increase the amount of workload or throughput a system can manage, but also provides additional redundancy and failover. {{< html-diagram/scaling-strategy "horizontal" >}} ## Scale components in your cluster The following components of your InfluxDB cluster are scaled by modifying properties in your `AppInstance` resource: - Ingester - Querier - Compactor - Router - Garbage collector {{% note %}} #### Scale your Catalog and Object store Your InfluxDB [Catalog](/influxdb3/clustered/reference/internals/storage-engine/#catalog) and [Object store](/influxdb3/clustered/reference/internals/storage-engine/#object-store) are managed outside of your `AppInstance` resource. Scaling mechanisms for these components depend on the technology and underlying provider used for each. {{% /note %}} {{< tabs-wrapper >}} {{% tabs "small" %}} [AppInstance](#) [Helm](#) {{% /tabs %}} {{% tab-content %}} Use the `spec.package.spec.resources` property in your `AppInstance` resource defined in your `influxdb.yml` to define system resource minimums and limits for each pod and the number of replicas per component. `requests` are the minimum that the Kubernetes scheduler should reserve for a pod. `limits` are the maximum that a pod should be allowed to use. Your `AppInstance` resource can include the following properties to define resource minimums and limits per pod and replicas per component: - `spec.package.spec.resources` - `ingester` - `requests` - `cpu`: Minimum CPU resource units to assign to ingesters - `memory`: Minimum memory resource units to assign to ingesters - `replicas`: Number of ingester replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to ingesters - `memory`: Maximum memory resource units to assign to ingesters - `compactor` - `requests` - `cpu`: Minimum CPU resource units to assign to compactors - `memory`: Minimum memory resource units to assign to compactors - `replicas`: Number of compactor replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to compactors - `memory`: Maximum memory resource units to assign to compactors - `querier` - `requests` - `cpu`: Minimum CPU resource units to assign to queriers - `memory`: Minimum memory resource units to assign to queriers - `replicas`: Number of querier replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to queriers - `memory`: Maximum memory resource units to assign to queriers - `router` - `requests` - `cpu`: Minimum CPU resource units to assign to routers - `memory`: Minimum memory resource units to assign to routers - `replicas`: Number of router replicas to provision - `limits` - `cpu`: Maximum CPU Resource units to assign to routers - `memory`: Maximum memory resource units to assign to routers - `garbage-collector` - `requests` - `cpu`: Minimum CPU resource units to assign to the garbage collector - `memory`: Minimum memory resource units to assign to the garbage collector - `limits` - `cpu`: Maximum CPU Resource units to assign to the garbage collector - `memory`: Maximum memory resource units to assign to the garbage collector {{< expand-wrapper >}} {{% expand "View example `AppInstance` with resource requests and limits" %}} {{% code-placeholders "(INGESTER|COMPACTOR|QUERIER|ROUTER|GC)_(CPU_(MAX|MIN)|MEMORY_(MAX|MIN)|REPLICAS)" %}} ```yml apiVersion: kubecfg.dev/v1alpha1 kind: AppInstance # ... spec: package: spec: # The following settings tune the various pods for their cpu/memory/replicas # based on workload needs. Only uncomment the specific resources you want # to change. Anything left commented will use the package default. resources: ingester: requests: cpu: INGESTER_CPU_MIN memory: INGESTER_MEMORY_MIN replicas: INGESTER_REPLICAS # Default is 3 limits: cpu: INGESTER_CPU_MAX memory: INGESTER_MEMORY_MAX compactor: requests: cpu: COMPACTOR_CPU_MIN memory: COMPACTOR_MEMORY_MIN replicas: COMPACTOR_REPLICAS # Default is 1 limits: cpu: COMPACTOR_CPU_MAX memory: COMPACTOR_MEMORY_MAX querier: requests: cpu: QUERIER_CPU_MIN memory: QUERIER_MEMORY_MIN replicas: QUERIER_REPLICAS # Default is 1 limits: cpu: QUERIER_CPU_MAX memory: QUERIER_MEMORY_MAX router: requests: cpu: ROUTER_CPU_MIN memory: ROUTER_MEMORY_MIN replicas: ROUTER_REPLICAS # Default is 1 limits: cpu: ROUTER_CPU_MAX memory: ROUTER_MEMORY_MAX garbage-collector: requests: cpu: GC_CPU_MIN memory: GC_MEMORY_MIN limits: cpu: GC_CPU_MAX memory: GC_MEMORY_MAX ``` {{% /code-placeholders %}} {{% /expand %}} {{< /expand-wrapper >}} {{% /tab-content %}} {{% tab-content %}} Use the `resources` property in your `values.yaml` to define system resource minimums and limits for each pod and the number of replicas per component. `requests` are the minimum that the Kubernetes scheduler should reserve for a pod. `limits` are the maximum that a pod should be allowed to use. Use the following properties to define resource minimums and limits per pod and replicas per component: - `resources` - `ingester` - `requests` - `cpu`: Minimum CPU resource units to assign to ingesters - `memory`: Minimum memory resource units to assign to ingesters - `replicas`: Number of ingester replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to ingesters - `memory`: Maximum memory resource units to assign to ingesters - `compactor` - `requests` - `cpu`: Minimum CPU resource units to assign to compactors - `memory`: Minimum memory resource units to assign to compactors - `replicas`: Number of compactor replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to compactors - `memory`: Maximum memory resource units to assign to compactors - `querier` - `requests` - `cpu`: Minimum CPU resource units to assign to queriers - `memory`: Minimum memory resource units to assign to queriers - `replicas`: Number of querier replicas to provision - `limits` - `cpu`: Maximum CPU resource units to assign to queriers - `memory`: Maximum memory resource units to assign to queriers - `router` - `requests` - `cpu`: Minimum CPU resource units to assign to routers - `memory`: Minimum memory resource units to assign to routers - `replicas`: Number of router replicas to provision - `limits` - `cpu`: Maximum CPU Resource units to assign to routers - `memory`: Maximum memory resource units to assign to routers - `garbage-collector` - `requests` - `cpu`: Minimum CPU resource units to assign to the garbage collector - `memory`: Minimum memory resource units to assign to the garbage collector - `limits` - `cpu`: Maximum CPU Resource units to assign to the garbage collector - `memory`: Maximum memory resource units to assign to the garbage collector {{< expand-wrapper >}} {{% expand "View example `values.yaml` with resource requests and limits" %}} {{% code-placeholders "(INGESTER|COMPACTOR|QUERIER|ROUTER|GC)_(CPU_(MAX|MIN)|MEMORY_(MAX|MIN)|REPLICAS)" %}} ```yml # ... resources: ingester: requests: cpu: INGESTER_CPU_MIN memory: INGESTER_MEMORY_MIN replicas: INGESTER_REPLICAS # Default is 3 limits: cpu: INGESTER_CPU_MAX memory: INGESTER_MEMORY_MAX compactor: requests: cpu: COMPACTOR_CPU_MIN memory: COMPACTOR_MEMORY_MIN replicas: COMPACTOR_REPLICAS # Default is 1 limits: cpu: COMPACTOR_CPU_MAX memory: COMPACTOR_MEMORY_MAX querier: requests: cpu: QUERIER_CPU_MIN memory: QUERIER_MEMORY_MIN replicas: QUERIER_REPLICAS # Default is 1 limits: cpu: QUERIER_CPU_MAX memory: QUERIER_MEMORY_MAX router: requests: cpu: ROUTER_CPU_MIN memory: ROUTER_MEMORY_MIN replicas: ROUTER_REPLICAS # Default is 1 limits: cpu: ROUTER_CPU_MAX memory: ROUTER_MEMORY_MAX garbage-collector: requests: cpu: GC_CPU_MIN memory: GC_MEMORY_MIN limits: cpu: GC_CPU_MAX memory: GC_MEMORY_MAX ``` {{% /code-placeholders %}} {{% /expand %}} {{< /expand-wrapper >}} {{% /tab-content %}} {{< /tabs-wrapper >}} {{% note %}} Applying resource limits to pods is optional, but provides better resource isolation and protects against pods using more resources than intended. For information, see [Kubernetes resource requests and limits](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#requests-and-limits). {{% /note %}} ##### Related Kubernetes documentation - [CPU resource units](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#meaning-of-cpu) - [Memory resource units](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#meaning-of-memory) ### Horizontally scale a component To horizontally scale a component in your InfluxDB cluster, increase or decrease the number of replicas for the component and [apply the change](#apply-your-changes). {{% warn %}} #### Only use the AppInstance to scale component replicas Only use the `AppInstance` resource to scale component replicas. Manually scaling replicas may cause errors. {{% /warn %}} For example--to horizontally scale your [Ingester](/influxdb3/clustered/reference/internals/storage-engine/#ingester): {{< code-tabs-wrapper >}} {{% code-tabs %}} [AppInstance](#) [Helm](#) {{% /code-tabs %}} {{% code-tab-content %}} ```yaml apiVersion: kubecfg.dev/v1alpha1 kind: AppInstance # ... spec: package: spec: resources: ingester: requests: # ... replicas: 6 ``` {{% /code-tab-content %}} {{% code-tab-content %}} ```yaml # ... resources: ingester: requests: # ... replicas: 6 ``` {{% /code-tab-content %}} {{< /code-tabs-wrapper >}} ### Vertically scale a component To vertically scale a component in your InfluxDB cluster, increase or decrease the CPU and memory resource units to assign to component pods and [apply the change](#apply-your-changes). {{< code-tabs-wrapper >}} {{% code-tabs %}} [AppInstance](#) [Helm](#) {{% /code-tabs %}} {{% code-tab-content %}} ```yaml apiVersion: kubecfg.dev/v1alpha1 kind: AppInstance # ... spec: package: spec: resources: ingester: requests: cpu: "500m" memory: "512MiB" # ... limits: cpu: "1000m" memory: "1024MiB" ``` {{% /code-tab-content %}} {{% code-tab-content %}} ```yaml # ... resources: ingester: requests: cpu: "500m" memory: "512MiB" # ... limits: cpu: "1000m" memory: "1024MiB" ``` {{% /code-tab-content %}} {{< /code-tabs-wrapper >}} ### Apply your changes After modifying the `AppInstance` resource, use `kubectl apply` to apply the configuration changes to your cluster and scale the updated components. {{< code-tabs-wrapper >}} {{% code-tabs %}} [AppInstance](#) [Helm](#) {{% /code-tabs %}} {{% code-tab-content %}} ```bash kubectl apply \ --filename myinfluxdb.yml \ --namespace influxdb ``` {{% /code-tab-content %}} {{% code-tab-content %}} ```bash helm upgrade \ influxdata/influxdb3-clustered \ -f ./values.yml \ --namespace influxdb ``` {{% /code-tab-content %}} {{< /code-tabs-wrapper >}} ## Scale your cluster as a whole Scaling your entire InfluxDB Cluster is done by scaling your Kubernetes cluster and is managed outside of InfluxDB. The process of scaling your entire Kubernetes cluster depends on your underlying Kubernetes provider. You can also use [Kubernetes autoscaling](https://kubernetes.io/docs/concepts/cluster-administration/cluster-autoscaling/) to automatically scale your cluster as needed. ## Recommended scaling strategies per component - [Router](#router) - [Ingester](#ingester) - [Querier](#querier) - [Compactor](#compactor) - [Garbage collector](#garbage-collector) - [Catalog](#catalog) - [Object store](#object-store) ### Router The Router can be scaled both [vertically](#vertical-scaling) and [horizontally](#horizontal-scaling). Horizontal scaling increases write throughput and is typically the most effective scaling strategy for the Router. Vertical scaling (specifically increased CPU) improves the Router's ability to parse incoming line protocol with lower latency. ### Ingester The Ingester can be scaled both [vertically](#vertical-scaling) and [horizontally](#horizontal-scaling). Vertical scaling increases write throughput and is typically the most effective scaling strategy for the Ingester. #### Ingester storage volume Ingesters use an attached storage volume to store the [Write-Ahead Log (WAL)](/influxdb3/clustered/reference/glossary/#wal-write-ahead-log). With more storage available, Ingesters can keep bigger WAL buffers, which improves query performance and reduces pressure on the Compactor. Storage speed also helps with query performance. Configure the storage volume attached to Ingester pods in the `spec.package.spec.ingesterStorage` property of your `AppInstance` resource or, if using Helm, the `ingesterStorage` property of your `values.yaml`. {{< expand-wrapper >}} {{% expand "View example Ingester storage configuration" %}} {{% code-placeholders "STORAGE_(CLASS|SIZE)" %}} {{< code-tabs-wrapper >}} {{% code-tabs %}} [AppInstance](#) [Helm](#) {{% /code-tabs %}} {{% code-tab-content %}} ```yml apiVersion: kubecfg.dev/v1alpha1 kind: AppInstance # ... spec: package: spec: # ... ingesterStorage: # (Optional) Set the storage class. This will differ based on the K8s #environment and desired storage characteristics. # If not set, the default storage class is used. storageClassName: STORAGE_CLASS # Set the storage size (minimum 2Gi recommended) storage: STORAGE_SIZE ``` {{% /code-tab-content %}} {{% code-tab-content %}} ```yml # ... ingesterStorage: # (Optional) Set the storage class. This will differ based on the K8s #environment and desired storage characteristics. # If not set, the default storage class is used. storageClassName: STORAGE_CLASS # Set the storage size (minimum 2Gi recommended) storage: STORAGE_SIZE ``` {{% /code-tab-content %}} {{< /code-tabs-wrapper >}} {{% /code-placeholders %}} {{% /expand %}} {{< /expand-wrapper >}} ### Querier The Querier can be scaled both [vertically](#vertical-scaling) and [horizontally](#horizontal-scaling). Horizontal scaling increases query throughput to handle more concurrent queries. Vertical scaling improves the Querier’s ability to process computationally intensive queries. ### Compactor The Compactor can be scaled both [vertically](#vertical-scaling) and [horizontally](#horizontal-scaling). Because compaction is a compute-heavy process, vertical scaling (especially increasing the available CPU) is the most effective scaling strategy for the Compactor. Horizontal scaling increases compaction throughput, but not as efficiently as vertical scaling. ### Garbage collector The Garbage collector can be scaled [vertically](#vertical-scaling). It is a light-weight process that typically doesn't require many system resources, but if you begin to see high resource consumption on the garbage collector, you can scale it vertically to address the added workload. ### Catalog Scaling strategies available for the Catalog depend on the PostgreSQL-compatible database used to run the catalog. All support [vertical scaling](#vertical-scaling). Most support [horizontal scaling](#horizontal-scaling) for redundancy and failover. ### Object store Scaling strategies available for the Object store depend on the underlying object storage services used to run the object store. Most support [horizontal scaling](#horizontal-scaling) for redundancy, failover, and increased capacity.