{"id":1173692,"date":"2024-10-03T09:51:44","date_gmt":"2024-10-03T16:51:44","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1173692"},"modified":"2025-07-10T13:19:13","modified_gmt":"2025-07-10T20:19:13","slug":"tracking-your-premium-feature-data-store-key-health-indicators","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators","title":{"rendered":"Tracking your ArcGIS Online Feature Data Store Key Health Indicators"},"author":100342,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[37501,23851,37141],"tags":[759472],"industry":[],"product":[36551],"class_list":["post-1173692","blog","type-blog","status-publish","format-standard","hentry","category-administration","category-data-management","category-decision-support","tag-premium-feature-data-store","product-arcgis-online"],"acf":{"short_description":"Learn to track your ArcGIS Online Feature Data Store's health using the Resource Chart.","flexible_content":[{"acf_fc_layout":"content","content":"

This article was originally published on June 14, 2023, and has been updated.<\/em><\/p>\n

Every time you visit the doctor, a familiar routine takes place. Temperature, heart rate, blood pressure\u2014information collected and retained.<\/p>\n

Why do we do this? You might be there for a sore pinkie toe. Surely heart rate doesn\u2019t impact that.<\/em><\/p>\n

I Am Not A Doctor\u2014but I know these measurements are done in part to establish a baseline, a collection of data points representing the range of values considered healthy or normal for your body.<\/p>\n

Variation from this baseline can be a more revealing health indicator than the number on its own.<\/p>\n

The Feature Data Store resource usage chart displays your feature data store\u2019s key health indicators over time, offering administrators precise insight into its typical range of values. Early awareness of changes in resource use patterns offers administrators the opportunity to take corrective action before problems arise.<\/p>\n

In this blog article, we\u2019ll first learn how to access the usage chart, and then we\u2019ll discuss how getting to know your feature data store baseline will help you keep it in good health!<\/p>\n

For more information about Standard and Premium Feature Data Store, including pricing and capabilities, please visit our ArcGIS Online FAQ.<\/p>\n

Accessing the usage chart<\/strong><\/h2>\n

To begin, log into your organization with an Administrator role, then navigate to your Organization Overview page.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1173702,"id":1173702,"title":"OrganizationOverviewPage","filename":"OrganizationOverviewPage-e1616774048331.png","filesize":33707,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/organizationoverviewpage","alt":"","author":"100342","description":"","caption":"","name":"organizationoverviewpage","status":"inherit","uploaded_to":1173692,"date":"2021-03-25 23:19:43","modified":"2021-03-25 23:19:43","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":702,"height":91,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-213x126.png","thumbnail-width":213,"thumbnail-height":126,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","medium-width":464,"medium-height":60,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","medium_large-width":702,"medium_large-height":91,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","large-width":702,"large-height":91,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","1536x1536-width":702,"1536x1536-height":91,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","2048x2048-width":702,"2048x2048-height":91,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-826x107.png","card_image-width":826,"card_image-height":107,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/OrganizationOverviewPage-e1616774048331.png","wide_image-width":702,"wide_image-height":91}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

From here, you can see the size of feature data store that your organization is using, and the percentage of feature data storage that has already been used.<\/p>\n

Click the Feature Data Store<\/strong> hyperlink to access the usage chart.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1961622,"id":1961622,"title":"Org Settings Data Store Type and Storage","filename":"Org-Settings-Data-Store-Type-w-Block.png","filesize":53926,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/org-settings-data-store-type-w-block","alt":"Org Settings Data Store Type and Storage","author":"100342","description":"Org Settings Data Store Type and Storage","caption":"","name":"org-settings-data-store-type-w-block","status":"inherit","uploaded_to":1173692,"date":"2023-06-09 18:12:08","modified":"2023-06-09 18:12:45","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":684,"height":356,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","medium-width":464,"medium-height":241,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","medium_large-width":684,"medium_large-height":356,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","large-width":684,"large-height":356,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","1536x1536-width":684,"1536x1536-height":356,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","2048x2048-width":684,"2048x2048-height":356,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","card_image-width":684,"card_image-height":356,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Org-Settings-Data-Store-Type-w-Block.png","wide_image-width":684,"wide_image-height":356}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

The usage chart expands the administrator’s insight into the organization’s feature data store and its two key values: feature data storage and feature data compute\u2014<\/span><\/span>which I like to call “horsepower.”<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1963032,"id":1963032,"title":"Storage and Compute","filename":"Chart-and-Storage.png","filesize":114526,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/chart-and-storage","alt":"Storage and Compute","author":"100342","description":"","caption":"Feature Data Storage and Feature Data Compute","name":"chart-and-storage","status":"inherit","uploaded_to":1173692,"date":"2023-06-10 00:46:59","modified":"2023-06-10 00:47:36","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":827,"height":688,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","medium-width":314,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","medium_large-width":768,"medium_large-height":639,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","large-width":827,"large-height":688,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","1536x1536-width":827,"1536x1536-height":688,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","2048x2048-width":827,"2048x2048-height":688,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage-559x465.png","card_image-width":559,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Chart-and-Storage.png","wide_image-width":827,"wide_image-height":688}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Getting to know your feature data store\u2019s baseline <\/strong><\/h2>\n

Our heart rates and blood pressure fluctuate throughout the day, based on exertion, food intake, ambient temperature, and sometimes for no reason we can discern.<\/p>\n

Similarly, the storage and computational use of your organization’s feature data store will fluctuate. Healthy systems perform various self-care routines and recycle their processes periodically\u2014these can result in some visible and normal movement in computational resources.<\/p>\n

In addition to these minor variations, our organization\u2019s workflows vary. On some days, your data store may be running a marathon and on others, it may be enjoying a lazy Sunday. If 350 mobile workers return from the field and sync their offline edits simultaneously, we\u2019ll likely observe a corresponding increase in computational load. And at night (or lazy Sundays) your feature data store may register little or even no activity.<\/p>\n

The key to managing your resources is recognizing what range of data points lie within your Feature Data Store\u2019s normal use patterns, and what to do if you see unusual variation.<\/p>\n

Storage<\/strong><\/h3>\n"},{"acf_fc_layout":"image","image":{"ID":1963042,"id":1963042,"title":"Storage","filename":"Storage-1.png","filesize":71785,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/storage-3","alt":"Storage","author":"100342","description":"Storage","caption":"","name":"storage-3","status":"inherit","uploaded_to":1173692,"date":"2023-06-10 00:52:36","modified":"2023-06-10 00:52:49","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1184,"height":262,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","medium-width":464,"medium-height":103,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","medium_large-width":768,"medium_large-height":170,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","large-width":1184,"large-height":262,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","1536x1536-width":1184,"1536x1536-height":262,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","2048x2048-width":1184,"2048x2048-height":262,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1-826x183.png","card_image-width":826,"card_image-height":183,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Storage-1.png","wide_image-width":1184,"wide_image-height":262}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Storage includes three metrics. Your feature data store\u2019s total, or allocated<\/em> storage space is represented by the horizontal line. Used storage space is shown in dark grey. And remaining storage space, or available<\/em> storage is shown in light grey.<\/p>\n

In the above example, the feature data store is allocated 1 terabyte (TB) of total storage space. Of that space, there are 933.48 gigabytes (GB) remaining. At a glance, I can see my organization has plenty of room available for additional feature data.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1963052,"id":1963052,"title":"Used and Available","filename":"Used-and-Available.png","filesize":23622,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/used-and-available","alt":"Used and Available","author":"100342","description":"Used and Available","caption":"","name":"used-and-available","status":"inherit","uploaded_to":1173692,"date":"2023-06-10 00:57:51","modified":"2023-06-10 00:58:00","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1146,"height":170,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available-213x170.png","thumbnail-width":213,"thumbnail-height":170,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","medium-width":464,"medium-height":69,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","medium_large-width":768,"medium_large-height":114,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","large-width":1146,"large-height":170,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","1536x1536-width":1146,"1536x1536-height":170,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","2048x2048-width":1146,"2048x2048-height":170,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available-826x123.png","card_image-width":826,"card_image-height":123,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2021\/03\/Used-and-Available.png","wide_image-width":1146,"wide_image-height":170}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

This information helps you maintain an awareness of your organization\u2019s storage use. If you observe increasing storage consumption, you can run organization reports<\/a> to find large items or items you and your team can identify as being stale or otherwise unnecessary. And if you hear widespread user reports of consistently failing attempts to add new features or upload data, check your storage use–these could be symptoms of running out of space.<\/p>\n

But if you and your team validate that all of the content is necessary, it may be time to consider upgrading to a larger Feature Data Store.<\/p>\n

Upgrade your Standard Feature Data Store to a Premium Feature Data Store online<\/a>, or move between Premium Feature Data Store levels by contacting your Account Manager. Upgrading and downgrading between ArcGIS Online Feature Data Store levels requires no work from your team, and all content and URLs are unaffected. Upgrading from Standard to Premium or to a higher Premium level can happen at any time with a minimum billing period of 30 days.<\/p>\n

Computational resources<\/strong><\/h3>\n

Computation is essentially: the work being done by the database engine powering ArcGIS Online Feature Data Store. Think of this like a vehicle\u2014<\/span><\/span>if you need to move a ton of gravel, a pickup truck with a lot of torque will move much more quickly uphill than a passenger car carrying the same weight.<\/p>\n

To apply this reasoning to ArcGIS Online, we must understand what work is done by the feature data store. In the graphic below, common workflows are listed in order of most power used to least power used, and some of the “multipliers” that can increase work done at the database level\u2014<\/span><\/span>for example, concurrency, multipart features, and so on.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2423472,"id":2423472,"title":"Workflows by intensity","filename":"Updated-multiplier-consumption-chart.png","filesize":117423,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/data-management\/tracking-your-premium-feature-data-store-key-health-indicators\/updated-multiplier-consumption-chart","alt":"","author":"100342","description":"","caption":"","name":"updated-multiplier-consumption-chart","status":"inherit","uploaded_to":1173692,"date":"2024-07-04 00:44:02","modified":"2024-07-04 00:45:01","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1784,"height":1180,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart.png","medium-width":395,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart.png","medium_large-width":768,"medium_large-height":508,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart.png","large-width":1633,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart-1536x1016.png","1536x1536-width":1536,"1536x1536-height":1016,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart.png","2048x2048-width":1784,"2048x2048-height":1180,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart-703x465.png","card_image-width":703,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/06\/Updated-multiplier-consumption-chart-1633x1080.png","wide_image-width":1633,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

This provides a general idea of which workflows rely on the feature data store\u2014<\/span><\/span>operations performed on hosted feature layers. Anti-pattern workflows are those that do not follow best practices\u2014<\/span><\/span>for example, enabling editing on a public feature layer in a web map. Best practices are blueprints for configurations that use feature data store resources optimally. Without best practices (described later in this article, the feature data store must work harder. Frequent bulk edits and ETL can require more horsepower; I generally consider this effect when getting into 100K record territory and when data is updated more frequently than every 15 minutes. There are no fixed rules\u2014<\/span><\/span>and the multipliers add much potential variation\u2014<\/span><\/span>but these are good ideas to keep in mind as you build awareness of your team’s workflows and your organization behaviors via the usage chart.<\/p>\n

The usage chart tracks an aggregate computational metric comprised of the following:<\/p>\n