The information on this page only applies if you use in0cluster storage. If you use an Azure storage account, AWS S3, or other S3 compatible storage, you do not need this.
An Automation Suite cluster uses the objectstore disks attached to its server nodes as storage resources available to all the products enabled on your cluster. Each product uses these resources differently.
To understand your storage needs and plan for them accordingly, refer to the following terminology and guidelines.
- Server node disk size – The size of all individual disks attached to each server node.
- Disks on each server may have different sizes as long as the sum of all the disk sizes is identical on all servers.
- Total cluster disk size – Server node disk size multiplied by the number of server nodes.
- Application available storage – The amount of storage available for applications to consume.
- Application available storage is lower than the total storage attached. This is to ensure we have a higher resiliency to fault tolerance and high availability.
The following table describes the multi-node HA-ready hardware requirements for the Complete product selection in the context of the previously introduced terms.
|Number of server nodes||Server node disk size||Total cluster disk size||Application available storage|
|3||512 GiB||1.5 TiB||512 GiB|
As you enable and use products on the cluster, they consume some storage from the application available storage. Products usually have a small enablement footprint as well as some usage-dependent footprint that varies depending on the use case, scale of use, and project. The storage consumption is evenly distributed across all the storage resources (data disks), and you can monitor the levels of storage utilization using the Automation Suite monitoring stack.
You will receive an alert with a warning when the storage consumption exceeds 75%. You will receive another critical alert when the storage consumption exceeds 85%; in this case, the storage will be read-only.
If your evaluated needs do not meet the recommended hardware requirements, you can add more storage capacity using either one or both of the following methods:
You have to add a new disk on all the server nodes of same size.
To configure the disk, see our docs.
You can estimate your storage consumption using the product-specific metric in the following tables. These tables describe how much content you can place on your cluster out of the box. For reference, they include the storage footprint of a typical usage scenario of each product.
|Product||Storage-driving metric||Storage per metric||Typical use case|
|Shared suite capabilities||Application logs||N/A||Typically, 7 days of application logs is around 25 GiB.|
|Orchestrator|| Size of the automation packages for deployed automations|
Size of the storage buckets of deployed automation
| Mb per package|
Mb per bucket
|Typically, a package is 5 Mb, and buckets, if any, are less than 1 Mb. A mature enterprise has 5 Gb of packages and 6 Gb of buckets deployed.|
|Action Center|| Number of documents stored by customer in document tasks|
Number of tasks created
| Gb per document in document tasks|
Number of tasks
|Typically, a document takes 0.15 Mb, and the forms to fill take an additional 0.15 Kb. In a mature enterprise this can roll up to 4Gb in total.|
|Test Manager||Number of attachments and screenshots stored by users||Mb of attachments and screenshots||Typically, all files and attachments add up to approximately 5 Gb.|
|Insights||Enablement footprint and the number of dashboards published||Gb per dashboard||2 Gb are required for enablement, with the storage footprint growing with the number. A well-established enterprise-scale deployment requires another few Gb for all the dashboards.|
|Automation Hub||N/A||N/A||2 Gb fixed footprint|
|Automation Ops||N/A||N/A||No storage footprint|
|Apps||Number of apps deployed and enablement footprint||Number of apps, size of apps, size of database supporting apps||Typically, the database takes approximately 5 Gb, and a typical complex app consumes approximately 15 Mb.|
|AI Center|| Number of uploaded ML packages|
Number of datasets for analysis
Number of published pipelines
| Gb per package|
Gb per dataset
Number of pipelines
|A typical and established installation will consume 8 Gb for 5 packages and an additional 1Gb for the datasets.|
A pipeline may consume an additional 50 Gb, but only when actively running.
|Document Understanding|| Size of ML model|
Size of OCR model
Number of stored documents
| Gb per ML model|
Gb per OCR model
Number of documents stored
|In a mature deployment, 12Gb will go to ML model, 17Gb to the OCR, and 50GB to all documents stored.|
|Task Mining||Hours of user activity analyzed to suggest automation patterns||Gb per hour||Typically, about 200Gb of activity log data should be analyzed to suggest meaningful automations. Highly repetitive tasks however, may require much less data.|
|Process Mining|| the number of events in millions|
the case and event fields
| ||Minimal footprint only used by users uploading data via the Process Mining portal. Approximately 10 GB of storage should be enough in the beginning.|
Updated about a month ago