- Elastic Cloud Enterprise - Elastic Cloud on your Infrastructure: other versions:
- Introducing Elastic Cloud Enterprise
- Preparing your installation
- Installing Elastic Cloud Enterprise
- Identify the deployment scenario
- Install ECE on a public cloud
- Install ECE on your own premises
- Alternative: Install ECE with Ansible
- Log into the Cloud UI
- Install ECE on additional hosts
- Migrate ECE to Podman hosts
- Post-installation steps
- Configuring your installation
- System deployments configuration
- Configure deployment templates
- Tag your allocators
- Edit instance configurations
- Create instance configurations
- Create deployment templates
- Configure system deployment templates
- Configure index management for templates
- Updating custom templates to support
node_roles
and autoscaling - Updating custom templates to support Integrations Server
- Default instance configurations
- Include additional Kibana plugins
- Manage snapshot repositories
- Manage licenses
- Change the ECE API URL
- Change endpoint URLs
- Enable custom endpoint aliases
- Configure allocator affinity
- Change allocator disconnect timeout
- Migrate ECE on Podman hosts to SELinux in
enforcing
mode
- Securing your installation
- Monitoring your installation
- Administering your installation
- Working with deployments
- Create a deployment
- Access Kibana
- Adding data to Elasticsearch
- Migrating data
- Ingesting data from your application
- Ingest data with Node.js on Elastic Cloud Enterprise
- Ingest data with Python on Elastic Cloud Enterprise
- Ingest data from Beats to Elastic Cloud Enterprise with Logstash as a proxy
- Ingest data from a relational database into Elastic Cloud Enterprise
- Ingest logs from a Python application using Filebeat
- Ingest logs from a Node.js web application using Filebeat
- Manage data from the command line
- Administering deployments
- Change your deployment configuration
- Maintenance mode
- Terminate a deployment
- Restart a deployment
- Restore a deployment
- Delete a deployment
- Migrate to index lifecycle management
- Disable an Elasticsearch data tier
- Access the Elasticsearch API console
- Work with snapshots
- Restore a snapshot across clusters
- Upgrade versions
- Editing your user settings
- Deployment autoscaling
- Configure Beats and Logstash with Cloud ID
- Keep your clusters healthy
- Keep track of deployment activity
- Secure your clusters
- Deployment heap dumps
- Deployment thread dumps
- Traffic Filtering
- Connect to your cluster
- Manage your Kibana instance
- Manage your APM & Fleet Server (7.13+)
- Manage your APM Server (versions before 7.13)
- Manage your Integrations Server
- Switch from APM to Integrations Server payload
- Enable logging and monitoring
- Enable cross-cluster search and cross-cluster replication
- Access other deployments of the same Elastic Cloud Enterprise environment
- Access deployments of another Elastic Cloud Enterprise environment
- Access deployments of an Elasticsearch Service organization
- Access clusters of a self-managed environment
- Enabling CCS/R between Elastic Cloud Enterprise and ECK
- Edit or remove a trusted environment
- Migrate the cross-cluster search deployment template
- Enable App Search
- Enable Enterprise Search
- Enable Graph (versions before 5.0)
- Troubleshooting
- RESTful API
- Authentication
- API calls
- How to access the API
- API examples
- Setting up your environment
- A first API call: What deployments are there?
- Create a first Deployment: Elasticsearch and Kibana
- Applying a new plan: Resize and add high availability
- Updating a deployment: Checking on progress
- Applying a new deployment configuration: Upgrade
- Enable more stack features: Add Enterprise Search to a deployment
- Dipping a toe into platform automation: Generate a roles token
- Customize your deployment
- Remove unwanted deployment templates and instance configurations
- Secure your settings
- API reference
- Changes to index allocation and API
- Script reference
- Release notes
- Elastic Cloud Enterprise 3.7.3
- Elastic Cloud Enterprise 3.7.2
- Elastic Cloud Enterprise 3.7.1
- Elastic Cloud Enterprise 3.7.0
- Elastic Cloud Enterprise 3.6.2
- Elastic Cloud Enterprise 3.6.1
- Elastic Cloud Enterprise 3.6.0
- Elastic Cloud Enterprise 3.5.1
- Elastic Cloud Enterprise 3.5.0
- Elastic Cloud Enterprise 3.4.1
- Elastic Cloud Enterprise 3.4.0
- Elastic Cloud Enterprise 3.3.0
- Elastic Cloud Enterprise 3.2.1
- Elastic Cloud Enterprise 3.2.0
- Elastic Cloud Enterprise 3.1.1
- Elastic Cloud Enterprise 3.1.0
- Elastic Cloud Enterprise 3.0.0
- Elastic Cloud Enterprise 2.13.4
- Elastic Cloud Enterprise 2.13.3
- Elastic Cloud Enterprise 2.13.2
- Elastic Cloud Enterprise 2.13.1
- Elastic Cloud Enterprise 2.13.0
- Elastic Cloud Enterprise 2.12.4
- Elastic Cloud Enterprise 2.12.3
- Elastic Cloud Enterprise 2.12.2
- Elastic Cloud Enterprise 2.12.1
- Elastic Cloud Enterprise 2.12.0
- Elastic Cloud Enterprise 2.11.2
- Elastic Cloud Enterprise 2.11.1
- Elastic Cloud Enterprise 2.11.0
- Elastic Cloud Enterprise 2.10.1
- Elastic Cloud Enterprise 2.10.0
- Elastic Cloud Enterprise 2.9.2
- Elastic Cloud Enterprise 2.9.1
- Elastic Cloud Enterprise 2.9.0
- Elastic Cloud Enterprise 2.8.1
- Elastic Cloud Enterprise 2.8.0
- Elastic Cloud Enterprise 2.7.2
- Elastic Cloud Enterprise 2.7.1
- Elastic Cloud Enterprise 2.7.0
- Elastic Cloud Enterprise 2.6.2
- Elastic Cloud Enterprise 2.6.1
- Elastic Cloud Enterprise 2.6.0
- Elastic Cloud Enterprise 2.5.1
- Elastic Cloud Enterprise 2.5.0
- Elastic Cloud Enterprise 2.4.3
- Elastic Cloud Enterprise 2.4.2
- Elastic Cloud Enterprise 2.4.1
- Elastic Cloud Enterprise 2.4.0
- Elastic Cloud Enterprise 2.3.2
- Elastic Cloud Enterprise 2.3.1
- Elastic Cloud Enterprise 2.3.0
- Elastic Cloud Enterprise 2.2.3
- Elastic Cloud Enterprise 2.2.2
- Elastic Cloud Enterprise 2.2.1
- Elastic Cloud Enterprise 2.2.0
- Elastic Cloud Enterprise 2.1.1
- Elastic Cloud Enterprise 2.1.0
- Elastic Cloud Enterprise 2.0.1
- Elastic Cloud Enterprise 2.0.0
- Elastic Cloud Enterprise 1.1.5
- Elastic Cloud Enterprise 1.1.4
- Elastic Cloud Enterprise 1.1.3
- Elastic Cloud Enterprise 1.1.2
- Elastic Cloud Enterprise 1.1.1
- Elastic Cloud Enterprise 1.1.0
- Elastic Cloud Enterprise 1.0.2
- Elastic Cloud Enterprise 1.0.1
- Elastic Cloud Enterprise 1.0.0
- What’s new with the Elastic Stack
- About this product
Autoscaling example
editAutoscaling example
editTo help you better understand the available autoscaling settings, this example describes a typical autoscaling workflow on sample Elastic Cloud Enterprise deployment.
-
Enable autoscaling:
- When you upgrade a deployment from a stack version in which autoscaling is not supported (prior to version 7.11) to a version in which it is supported (version 7.11 or higher), after the upgrade completes a message indicates that autoscaling is available. You can enable it simply using the button in the message.
- On a newly created deployment with stack version 7.11 or higher, open the deployment Edit page to find the option to turn on autoscaling.
-
When you create a new deployment, you can find the autoscaling option under Advanced settings.
Once you confirm your changes or create a new deployment, autoscaling is activated with system default settings that you can adjust as needed (though for most use cases the default settings will likely suffice).
-
View and adjust autoscaling settings on data tiers:
-
Open the Edit page for your deployment to get the current and maximum size per zone of each Elasticsearch data tier. In this example, the hot data and content tier has the following settings:
Current size per zone
Maximum size per zone
45GB storage
1.41TB storage
1GB RAM
32GB RAM
Up to 2.5 vCPU
5 vCPU
The fault tolerance for the data tier is set to 2 availability zones.
- Use the dropdown boxes to adjust the current and/or the maximum size of the data tier. Capacity will be added to the hot content and data tier when required, based on its past and present storage usage, until it reaches the maximum size per zone. Any scaling events are applied simultaneously across availability zones. In this example, the tier has plenty of room to scale relative to its current size, and it will not scale above the maximum size setting. There is no minimum size setting since downward scaling is currently not supported on data tiers.
-
-
View and adjust autoscaling settings on a machine learning instance:
-
From the deployment Edit page you can check the minimum and maximum size of your deployment’s machine learning instances. In this example, the machine learning instance has the following settings:
Minimum size per zone
Maximum size per zone
1GB RAM
64GB RAM
0.5 vCPU up to 8 vCPU
32 vCPU
The fault tolerance for the machine learning instance is set to 1 availability zone.
- Use the dropdown boxes to adjust the minimum and/or the maximum size of the data tier. Capacity will be added to or removed from the machine learning instances as needed. The need for a scaling event is determined by the expected memory and vCPU requirements for the currently configured machine learning job. Any scaling events are applied simultaneously across availability zones. Note that unlike data tiers, machine learning nodes do not have a Current size per zone setting. That setting is not needed since machine learning nodes support both upward and downward scaling.
-
- Over time, the volume of data and the size of any machine learning jobs in your deployment are likely to grow. Let’s assume that to meet storage requirements your hot data tier has scaled up to its maximum allowed size of 64GB RAM and 32 vCPU. At this point, a notification appears on the deployment overview page indicating that the tier has scaled to capacity.
- If you expect a continued increase in either storage, memory, or vCPU requirements, you can use the Maximum size per zone dropdown box to adjust the maximum capacity settings for your data tiers and machine learning instances, as appropriate. And, you can always re-adjust these levels downward if the requirements change.
As you can see, autoscaling greatly reduces the manual work involved to manage a deployment. The deployment capacity adjusts automatically as demands change, within the boundaries that you define. Check our main Deployment autoscaling page for more information.