[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-656327-105":3,"detail-sidebar-cat-0-en-105":80,"doc-detail-656327-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","guidance-for-cloud-native-fast-turnaround-media-workflows-on-aws","Guidance for Cloud-Native Fast-Turnaround Media Workflows on AWS","","Guidance describes a cloud-native architecture for fast, near-real-time processing of live or live-like video and audio workflows using a Time Addressable Media Store (TAMS). It explains how chunked media is stored and linked through a TAMS API, how notifications trigger additional derived versions, and how asynchronous AI/ML content analysis enables rapid outputs such as live subtitling, highlights, and logging. It also covers playback into production galleries, proxy generation, clip editing, exports, and conversion to HLS manifests.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/technology/","Technology",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/guidance-for-cloud-native-fast-turnaround-media-workflows-on-aws/656327/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/guidance-for-cloud-native-fast-turnaround-media-workflows-on-aws/656327.png","ImageObject",300,407,{"name":42,"@type":43},"\tJames","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-30","2026-10-25",true,{"@type":52,"interactionType":53,"userInteractionCount":26},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"What is the Time Addressable Media Store (TAMS) used for in the workflow?","Question",{"text":62,"@type":63},"TAMS acts as the core store for chunked media and provides an API that links content to its media essence for fast, time-aware workflows.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"How are near-real-time derived versions generated and organized?",{"text":67,"@type":63},"Content can be processed in near real-time to create additional versions such as proxies, triggered through notifications from the storage system.",{"name":69,"@type":60,"acceptedAnswer":70},"Which AWS services are involved in the TAMSAPI reference architecture?",{"text":71,"@type":63},"The architecture uses Amazon Cognito for authentication, API Gateway for request entry and validation, Lambda for processing, Neptune for source/flow metadata, DynamoDB for segment metadata, SQS for asynchronous deletes, and EventBridge for event reuse.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},656327,1792967783,{"code":4,"msg":81,"data":82},"success",[83,87,91,95,100,104,109,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":102,"slug":103},6,50,"technology",{"id":105,"doc_module":4,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},7,"Healthcare",40,"healthcare",{"id":110,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},8,"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":81,"data":131},{"doc_id":78,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":101,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":26,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":33,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":79,"read_time":123},2336474466412,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Guidance for Cloud-Native Fast-Turnaround Media Workflows on AWS  \nTAMS concept overview  \nThis architecture diagram shows the concept about how a Time Addressable Media Store (TAMS) sits at the core of a fastturnaround workflow for processing live or near-live video and audio content.   \n11 Media Asset Management (MAM)  \n2  \n8  \nPlayback into  \nproduction gallery  \nLive and on-demand streaming  \n9  \nVideo files   \nMedia processing  \n5  \nMachine learning  \nanalysis  \nClips and file export  \nReviewed for technical accuracy March 6,© 2024, Amazon Web Services, Inc. or its  \n2025  \naffiliates. All rights reserved.  \nAWS  \nReference Architecture  \nAll media is stored within a Time Addressable Media Store (TAMS) . This holds chunked media on object storage with an API to provide the link between content and the media essence.  \nLive video feeds are uploaded as small chunks of media and registered with the TAMS to provide the effect of growing content.  \nFile-based content can be uploaded natively or chunked prior to import as required.  \nContent can be processed in near real-time, generating additional versions, such as proxies, triggered through notifications from the storage system.  \nContent analysis can occur asynchronously and in near real-time, enabling rapid access to the outputs of machine learning and artificial intelligence (AI/ML) models. Examples include live subtitling, highlights generation, and content logging.  \nSimple clip-based editing can be performed, and the resulting edits can be published back to the TAMS, referencing the original content.  \nCraft editing can access content from the TAMS and publish back only new segments.  \nContent from the store can be played back as a realtime video stream into production galleries of linear channel playout facilities.  \nTAMS API can be easily converted into [HTTP](HTTP) Live Streaming (HLS) manifests to enable live or ondemand content streaming from the TAMS.  \nClips and files can be exported from the store for alternative purposes, such as the rapid distribution of content onto social media platforms.  \nThe Media Asset Management (MAM) system maintains references to the content stored within the TAMS, along with the associated rich editorial and time-based metadata.  \nIn the TAMS data structure, the parent source is equal to the actual content that a user interacts with. This parent source could be an editorial version of the content or a clip.  \nThe secondary level source within the data structure allows for the aggregation of the various media types, such as video, audio, or data, into a cohesive collection.  \nThe \"flow\" represents the technical manifestation of the content. This construct contains all the technical metadata necessary to describe the underlying media segments, such as bitrate, resolution, and frame rate.  \nMultiple flows can exist for a single piece of content, enabling the representation of different formats, such as HD and proxy, to coexist.  \nFlow types include video, audio, and data, allowing the different content types to be referenced in the store.  \nSegments are held on object storage and referenced in the TAMS API. The only interaction between the store and the segments occurs during deletion management.  \nThe segments are linked to a flow and exist within the context of that flow's virtual timeline. A time range format, expressed as Epoch time plus nanoseconds, is used to represent the position of each segment along the timeline.  \nNotes  \nA segment can be referenced in one or more flows, allowing the reuse of segments between content without duplication at the storage layer.  \nThe TAMS maintains only the metadata required for the storage and referencing of the media content. The rich metadata should be managed within separate systems, such as the Media Asset Management system.  \nGuidance for Cloud-Native Fast-Turnaround Media Workflows on AWS  \nAWS open source TAMSAPI  \nThis architecture diagram shows the components and data flows within theA","cbCaikjXEII1B9uO","https://ap.wps.com/l/cbCaikjXEII1B9uO","pdf",232840,"English","# TAMS concept overview\n## Media asset management (MAM)\n## Core data model: parent sources, flows, and segments\n## Storage and segment referencing\n## Playback and streaming (HLS)\n## Machine learning and content analysis\n# AWS reference architecture (open source TAMSAPI)\n## AWS services and API request handling\n## Metadata storage across Neptune and DynamoDB\n## Asynchronous deletion pipeline\n## Event publishing with EventBridge\n## Optional webhooks","[{\"question\":\"What is the Time Addressable Media Store (TAMS) used for in the workflow?\",\"answer\":\"TAMS acts as the core store for chunked media and provides an API that links content to its media essence for fast, time-aware workflows.\"},{\"question\":\"How are near-real-time derived versions generated and organized?\",\"answer\":\"Content can be processed in near real-time to create additional versions such as proxies, triggered through notifications from the storage system.\"},{\"question\":\"Which AWS services are involved in the TAMSAPI reference architecture?\",\"answer\":\"The architecture uses Amazon Cognito for authentication, API Gateway for request entry and validation, Lambda for processing, Neptune for source/flow metadata, DynamoDB for segment metadata, SQS for asynchronous deletes, and EventBridge for event reuse.\"}]","Guidance for Cloud-Native Fast-Turnaround Media Workflows on AWS | PDF"]