{"id":2953448,"date":"2026-01-08T18:45:05","date_gmt":"2026-01-09T02:45:05","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2953448"},"modified":"2026-01-08T19:06:48","modified_gmt":"2026-01-09T03:06:48","slug":"arcgis-reality-server-project-distribution","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/imagery\/imagery\/arcgis-reality-server-project-distribution","title":{"rendered":"Understanding project distribution across ArcGIS Reality Server machines for optimal performance"},"author":339752,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22931],"tags":[42301,769422,780922,768972],"industry":[],"product":[36571],"class_list":["post-2953448","blog","type-blog","status-publish","format-standard","hentry","category-imagery","tag-arcgis-enterprise","tag-arcgis-reality","tag-arcgis-reality-server","tag-reality-mapping","product-arcgis-enterprise"],"acf":{"authors":[{"ID":339752,"user_firstname":"Naheem","user_lastname":"Adebisi","nickname":"Naheem Adebisi","user_nicename":"naheemadebisi","display_name":"Naheem Adebisi","user_email":"nadebisi@esri.com","user_url":"","user_registered":"2023-05-26 16:41:00","user_description":"Naheem is a Product Engineer on the Imagery and Remote Sensing team at Esri, specializing in Enterprise solutions for reality mapping. He holds a PhD in Geophysics and has keen interests in leveraging digital twin and artificial intelligence for environmental monitoring and resource management.","user_avatar":""}],"short_description":"Learn how to optimize ArcGIS Reality Server performance across multiple machines using Parallel Processing Factor and worker pool configuration.","flexible_content":[{"acf_fc_layout":"content","content":"

ArcGIS\u00a0Reality\u00a0Server<\/span>\u00a0was recently\u00a0released for public beta,\u00a0bringing\u00a0<\/span>scalable, self-hosted reality mapping\u00a0capabilities to ArcGIS Enterprise<\/span><\/a>. Reality server\u00a0tools\u00a0enable organizations to\u00a0optimize\u00a0reality mapping projects across multi-machine configurations. Since the release, one of the most\u00a0common questions\u00a0we\u00a0have\u00a0received is: “How do I optimize processing across multiple machines?” In this blog,\u00a0we’ll\u00a0explain how to control Reality Server project distribution for\u00a0optimal\u00a0performance.\u00a0<\/span>\u00a0<\/span><\/p>\n

Understanding Distributed Processing\u00a0in Reality Server<\/span>\u00a0<\/span><\/h2>\n

Reality Server distributes project processing in two key scenarios:<\/span>\u00a0<\/span><\/p>\n

    \n
  1. Large project subdivision<\/span><\/b>: A single large project can be broken into smaller sub-projects and distributed across multiple machines.<\/span>\u00a0<\/span><\/li>\n
  2. Concurrent multi-user processing<\/span><\/b>: Multiple jobs from different users can be distributed and run simultaneously across multiple machines.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

    These scenarios\u00a0can be\u00a0controlled\u00a0differently as\u00a0we’ll\u00a0explore below.<\/span>\u00a0<\/span><\/p>\n

    \u00a0<\/span><\/p>\n

    Controlling distributed processing using\u00a0Parallel Processing Factor\u00a0(PPF)<\/span>\u00a0<\/span><\/h2>\n

    Think of your multi-machine reality server configuration not as individual machines, but as a pool of available workers. Each machine in your cluster contributes service instances (workers) to this pool. The Parallel Processing Factor (PPF) controls how many worker services from this pool are allocated to process a reality mapping project. Setting PPF to 100% will use all the worker instances in your pool while 50% will use up to half of the total worker instances. More workers dedicated to a job means faster processing because when a project is split into subprojects, each worker can process a different subproject simultaneously\u2014 reducing overall processing time. However, the number of subprojects your project is subdivided or even if a project will be split at all is determined internally by the Reality Engine (RE). <\/span>\u00a0<\/span><\/p>\n

    Let\u2019s say you want to process a large project on a 10 machines reality server site and RE splits the project to nine subprojects. If you set the PPF to 60%, up to six available workers will be assigned a subproject, leaving three subprojects in a queue. Whenever a subproject is completed, the next one in the queue looks for a free worker which could be the one that just finished or any of the other four unused workers. This process continues until all the subprojects are complete. <\/span>\u00a0<\/span><\/p>\n

    If PPF was set to 100%,\u00a0there\u00a0will\u00a0be more than enough workers (10) to handle the\u00a0nine\u00a0subprojects concurrently,\u00a0so no subproject\u00a0waits\u00a0for a\u00a0worker\u00a0to be free.\u00a0Processing is faster because\u00a0there’s\u00a0no queuing.\u00a0However, high PPF might result in resource competition in multi-user shared environments.\u00a0With PPF at 100%, one user’s large project could occupy all available workers, forcing other users’ jobs to wait.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

    \u00a0<\/span><\/p>\n

    Configuration Best Practices<\/span>\u00a0<\/span><\/h2>\n

    The key to\u00a0optimal\u00a0performance is understanding your usage scenario. For\u00a0single\u00a0or limited user dedicated environment where there is no concern for competition, you can set the PPF to 100% to maximize processing speed. For\u00a0multi-user shared environment,\u00a0the PPF should be\u00a0based on expected concurrent users and number of machines in the cluster.\u00a0<\/span>\u00a0<\/span><\/p>\n

    \u00a0<\/span><\/p>\n

    PPF and\u00a0RealityMappingTools\u00a0GP Service\u00a0Settings<\/span>\u00a0<\/span><\/h2>\n

    For\u00a0ArcGIS Pro,\u00a0you can set the\u00a0PPF value on the workspace configuration page during workspace creation.\u00a0When using ArcGIS API for python, you can set the PPF value through the context parameter of\u00a0the\u00a0appropriate\u00a0reality\u00a0mapping method.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2953457,"id":2953457,"title":"PPF_settings","filename":"PPF_settings.png","filesize":82262,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/imagery\/imagery\/arcgis-reality-server-project-distribution\/ppf_settings","alt":"PPF in ArcGIS Pro","author":"339752","description":"","caption":"Setting PPF in ArcGIS Pro","name":"ppf_settings","status":"inherit","uploaded_to":2953448,"date":"2026-01-08 02:34:21","modified":"2026-01-08 02:47:05","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":453,"height":658,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","medium-width":180,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","medium_large-width":453,"medium_large-height":658,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","large-width":453,"large-height":658,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","1536x1536-width":453,"1536x1536-height":658,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","2048x2048-width":453,"2048x2048-height":658,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings-320x465.png","card_image-width":320,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings.png","wide_image-width":453,"wide_image-height":658}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":2953455,"id":2953455,"title":"PPF_settings_Python_API","filename":"PPF_settings_Python_API.png","filesize":42938,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/imagery\/imagery\/arcgis-reality-server-project-distribution\/ppf_settings_python_api","alt":"PPF for ArcGIS API for Python Reality Mapping reconstruct surface mission method","author":"339752","description":"","caption":"Generating a DSM Mesh using a PPF of 100","name":"ppf_settings_python_api","status":"inherit","uploaded_to":2953448,"date":"2026-01-08 02:34:17","modified":"2026-01-08 02:47:05","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":624,"height":136,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API-213x136.png","thumbnail-width":213,"thumbnail-height":136,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","medium-width":464,"medium-height":101,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","medium_large-width":624,"medium_large-height":136,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","large-width":624,"large-height":136,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","1536x1536-width":624,"1536x1536-height":136,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","2048x2048-width":624,"2048x2048-height":136,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","card_image-width":624,"card_image-height":136,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/PPF_settings_Python_API.png","wide_image-width":624,"wide_image-height":136}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    The\u00a0support for\u00a0running multiple concurrent jobs from different users\u00a0is managed through the\u00a0RealityMappingTools\u00a0GP service’s instance configuration.\u00a0To support more\u00a0users processing simultaneously in your enterprise deployment, increase the maximum number of instances for the\u00a0RealityMappingTools\u00a0GP service:\u00a0<\/span>\u00a0<\/span><\/p>\n

      \n
    1. \u00a0Sign in to ArcGIS Server Manager as an administrator<\/span><\/li>\n
    2. Navigate to the\u00a0RealityMappingTools\u00a0service<\/span><\/li>\n
    3. On the Pooling page, set the maximum number of instances to match the number of concurrent users you expect<\/span>\u00a0<\/span><\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2953456,"id":2953456,"title":"RealityMappingTools","filename":"RealityMappingTools.png","filesize":65768,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/imagery\/imagery\/arcgis-reality-server-project-distribution\/realitymappingtools","alt":"RealityMappingTools GP service","author":"339752","description":"","caption":"RealityMappingTools GP service's instance configuration","name":"realitymappingtools","status":"inherit","uploaded_to":2953448,"date":"2026-01-08 02:34:19","modified":"2026-01-08 02:47:05","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":624,"height":250,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","medium-width":464,"medium-height":186,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","medium_large-width":624,"medium_large-height":250,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","large-width":624,"large-height":250,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","1536x1536-width":624,"1536x1536-height":250,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","2048x2048-width":624,"2048x2048-height":250,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","card_image-width":624,"card_image-height":250,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/01\/RealityMappingTools.png","wide_image-width":624,"wide_image-height":250}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

      Summary<\/span>\u00a0<\/span><\/h2>\n

      Optimizing\u00a0ArcGIS Reality Server performance across multiple machines requires\u00a0understanding usage\u00a0scenarios\u00a0to appropriately\u00a0balance\u00a0processing speed with resource management. For single-user environments, maximize PPF to\u00a0leverage\u00a0all available resources. For multi-user environments, configure PPF\u00a0appropriately\u00a0and ensure your\u00a0RealityMappingTools\u00a0GP service supports the\u00a0expected\u00a0number of concurrent instances.<\/span>\u00a0<\/span><\/p>\n"}],"related_articles":"","show_article_image":false,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/Reality_Server.png","wide_image":false},"yoast_head":"\nUnderstanding project distribution across ArcGIS Reality Server machines for optimal performance<\/title>\n<meta name=\"description\" content=\"Configure Parallel Processing Factor (PPF) for single and multi-user environments to optimize ArcGIS Reality Server performance across multiple machines.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/imagery\/imagery\/arcgis-reality-server-project-distribution\" \/>\n<meta property=\"og:locale\" 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