{"id":112203,"date":"2025-07-22T09:05:00","date_gmt":"2025-07-22T16:05:00","guid":{"rendered":"https:\/\/www.backblaze.com\/blog\/?p=112203"},"modified":"2025-09-08T11:20:28","modified_gmt":"2025-09-08T18:20:28","slug":"architecting-your-ai-data-pipeline-using-b2-overdrive","status":"publish","type":"post","link":"https:\/\/www.backblaze.com\/blog\/architecting-your-ai-data-pipeline-using-b2-overdrive\/","title":{"rendered":"Architecting Your AI Data Pipeline Using B2 Overdrive"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1440\" height=\"820\" src=\"https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI.png\" alt=\"A decorative image showing cloud storage and AI icons. \" class=\"wp-image-112204\" srcset=\"https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI.png 1440w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI-300x171.png 300w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI-1024x583.png 1024w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI-768x437.png 768w\" sizes=\"auto, (max-width: 1440px) 100vw, 1440px\" \/><\/figure>\n\n\n\n<div style=\"height:15px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>When you think about cloud infrastructure for AI, you immediately think of GPUs and other high-performance compute resources, and how your cloud architecture should be optimized to make the most of these expensive compute plans. But compute isn\u2019t the only cloud product category you need to monitor to both scale your application and maintain a sustainable cloud infrastructure budget.<\/p>\n\n\n\n<p>What ultimately fuels AI? Data\u2014lots and lots of data. As part of a healthy AI pipeline, several versions of the same dataset need to be stored in a centralized repository, or multiple repositories if your strategy requires splitting data into cold vs. hot storage to reduce storage costs. For text-based LLMs, storage costs are minimal compared to compute resources. But as AI innovation increasingly relies on video and other media, both the base storage cost and data retrieval fees can make cloud bills spiral out of control.<\/p>\n\n\n\n<p>In this blog, we\u2019re taking a look at the AI data pipeline, <a href=\"https:\/\/www.backblaze.com\/blog\/5-cloud-storage-best-practices-for-ai-workloads\/\" target=\"_blank\" rel=\"noreferrer noopener\">where object storage sits<\/a> in each stage, and how leveraging both Backblaze B2 and B2 Overdrive helps both increase performance and reduce costs for AI applications.<\/p>\n\n\n\n<div class=\"abstract\" style=\"line-height: 1.8; margin: 24px 12px; padding: 24px 12px 10px 12px;\">\n<h4>Ebook: \u201cWhy Object Storage Is Ideal for AI Workflows\u201d<\/h4>\n<p>Want to take a deeper dive into the world of object storage? Check out our latest ebook, <a href=\"https:\/\/www.backblaze.com\/contact-sales\/why-object-storage-is-essential-for-ai?hsCtaTracking=e30875f9-5fe1-4064-977a-b964a6653512%7C967e9066-f6db-4be0-8c64-b780bc250d84\" rel=\u201dnoopener\u201d \u201cnofollow\u201d target=\u201d_blank\u201d>&#8220;Why Object Storage is Ideal for AI Workloads,&#8221;<\/a> and discover the advantages this architecture has to offer across the model lifecycle.<\/p>\n<!--HubSpot Call-to-Action Code --><span class=\"hs-cta-wrapper\" id=\"hs-cta-wrapper-e30875f9-5fe1-4064-977a-b964a6653512\"><span class=\"hs-cta-node hs-cta-e30875f9-5fe1-4064-977a-b964a6653512\" id=\"hs-cta-e30875f9-5fe1-4064-977a-b964a6653512\"><!--[if lte IE 8]><div id=\"hs-cta-ie-element\"><\/div><![endif]--><a href=\"https:\/\/cta-redirect.hubspot.com\/cta\/redirect\/2832298\/e30875f9-5fe1-4064-977a-b964a6653512\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" class=\"hs-cta-img\" id=\"hs-cta-img-e30875f9-5fe1-4064-977a-b964a6653512\" style=\"border-width:0px;\" src=\"https:\/\/no-cache.hubspot.com\/cta\/default\/2832298\/e30875f9-5fe1-4064-977a-b964a6653512.png\"  alt=\"Get the Ebook\"\/><\/a><\/span><script charset=\"utf-8\" src=\"https:\/\/js.hscta.net\/cta\/current.js\"><\/script><script type=\"text\/javascript\"> hbspt.cta.load(2832298, 'e30875f9-5fe1-4064-977a-b964a6653512', {\"useNewLoader\":\"true\",\"region\":\"na1\"}); <\/script><\/span><!-- end HubSpot Call-to-Action Code -->\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\">AI data pipeline stages<\/h2>\n\n\n\n<p>There are five key AI data pipeline stages where <a href=\"https:\/\/www.backblaze.com\/blog\/where-and-why-object-storage-excels-throughout-the-ai-model-lifecycle\/\">data retrieval and overall performance is critical<\/a>\u2014and this performance starts with your designated data storage backend.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Data ingest and active archive: <\/strong>Data is gathered from multiple designated sources (including APIs, internet of things (IoT) sensors, relational databases, etc.) and ingested into a centralized repository or multiple repositories.<\/li>\n\n\n\n<li><strong>Data processing: <\/strong>The raw data is transformed and enriched based on the model\u2019s data parameters. This can range from relatively simple text cleanup to adding annotations and metadata. Feature engineering is performed to extract or construct meaningful attributes. All data is then converted into numerical representations (e.g., embeddings, vectors) suitable for model training and inference.<\/li>\n\n\n\n<li><strong>Model experimentation and training: <\/strong>Processed data is used to train models by learning underlying patterns. Iterative experiments in a test environment evaluate, tune, and improve model performance and accuracy.<\/li>\n\n\n\n<li><strong>Model deployment and inference: <\/strong>New data is prepared in the same way as during training and sent to the deployed model to generate predictions, support decision-making, and deliver personalized outputs.<\/li>\n\n\n\n<li><strong>Monitoring: <\/strong>Continuous monitoring tracks model performance, detects data drift, and flags potential bias, ensuring the model remains accurate and reliable over time.<\/li>\n<\/ul>\n\n\n\n<p>Keep in mind that data ingestion and processing isn&#8217;t always sequential, such as when data is collected and ingested, but corruption is detected during processing. Ideally, your pipeline is configured with validation gates so that corrupt data is identified and handled before proceeding to downstream steps like testing, training, and production deployment.<\/p>\n\n\n\n<p>When using cloud object storage as your data repository, one factor of selecting a plan (like cold versus hot storage) is the specific type of data ingestion that\u2019s being utilized based on both the data source and AI model\u2019s specific needs.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Batch ingestion<\/strong> is better suited for mid to lower performance storage, as this is typically used for historical datasets or a set schedule of pre-determined data updates, such as jobs pulling from relational databases or CSV uploads once a day or once per week.<\/li>\n\n\n\n<li><strong>Streaming ingestion<\/strong> is well-suited for hot storage to support a continuous stream of real-time (or near-real-time) data processing, such as from social media feeds and high-volume e-commerce AI helper agents.<\/li>\n\n\n\n<li><strong>Hybrid ingestion <\/strong>uses a combination of batch and streaming ingestion to handle both historical and real-time data requirements for AI models.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Where does cloud object storage sit in the AI data pipeline?<\/h2>\n\n\n\n<p><strong>Everywhere. <\/strong>All scalable data pipelines lead to object storage.<\/p>\n\n\n\n<p>Why?<strong> <\/strong>Data ingestion and active archive are the major areas where object storage fulfills an important purpose. When training AI models, especially in production, data scalability for multiple and diverse data types is a hard requirement. But object storage plays a key role in the other pipeline stages:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Data processing: <\/strong>Stores versioned outputs from data labeling, feature engineering, and cleaning processes.<\/li>\n\n\n\n<li><strong>Model experimentation and training:<\/strong> Provides high-throughput access to training datasets and stores model checkpoints.<\/li>\n\n\n\n<li><strong>Model deployment and inference:<\/strong> Stores serialized model artifacts with API-based retrieval for serving predictions at scale.<\/li>\n\n\n\n<li><strong>Monitoring:<\/strong> Stores synthetic outputs from generative models, logs, feedback, and performance metrics for analysis and reuse.<\/li>\n<\/ul>\n\n\n\n<p>For both AI data performance and cost optimization, selecting an object storage product or tier is far from one-size-fits-all. You can strategically allocate your data to B2 Cloud Storage or B2 Overdrive, with your most essential model data stored in B2 Overdrive.&nbsp; Here\u2019s a high-level diagram of what Backblaze B2 product to use for each stage, including examples of the data stored at each stage.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a3c84f8d4f7f&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a3c84f8d4f7f\" class=\"aligncenter size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"2400\" height=\"1254\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1.png\" alt=\"A diagram summarizing recommendations about using B2 Overdrive or Backblaze B2 based on MLOps use case. \" class=\"wp-image-112205\" srcset=\"https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1.png 2400w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-300x157.png 300w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-1024x535.png 1024w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-768x401.png 768w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-1536x803.png 1536w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-2048x1070.png 2048w, https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/B2-In-the-Data-Pipeline-LinkedIn-1200x627-1-1568x819.png 1568w\" sizes=\"auto, (max-width: 2400px) 100vw, 2400px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n<\/div>\n\n\n<div style=\"height:15px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Learn more at Ai4 in August<\/h2>\n\n\n\n<p>Want to learn more? Backblaze is heading to Las Vegas for Ai4 August 11\u201313! In addition to <a href=\"http:\/\/info.backblaze.com\/ai4-lv-2025\" target=\"_blank\" rel=\"noreferrer noopener\">booking a meeting<\/a> to speak with our storage experts and stopping by our booth to pick up some swag, I\u2019m excited to talk more about the AI data pipeline during my talk. If you\u2019re attending Ai4, add <a href=\"https:\/\/app.swapcard.com\/widget\/event\/ai4-2025\/planning\/UGxhbm5pbmdfMjY0NTg2Ng==\" target=\"_blank\" rel=\"noreferrer noopener\">The AI Pipeline Starts with Storage: Architecting Scalable Data Foundations<\/a> to your conference agenda.<\/p>\n\n\n\n<p>Can\u2019t attend live in Vegas? <a href=\"https:\/\/www.backblaze.com\/contact-sales\/b2-overdrive\" target=\"_blank\" rel=\"noreferrer noopener\">Reach out to our Sales team<\/a> to talk about your specific use case and how B2 Overdrive can help propel your data.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cloud infrastructure for AI isn&#8217;t just about compute; it&#8217;s also about optimizing data storage and retrieval. Learn how Backblaze B2 and B2 Overdrive can reduce costs and increase performance throughout the five key stages of your AI data pipeline.<\/p>\n","protected":false},"author":220,"featured_media":112204,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","jetpack_post_was_ever_published":false},"categories":[7,434,438,482],"tags":[489,468],"class_list":["post-112203","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cloud-storage","category-featured-1","category-featured-cloud-storage","category-hybrid-cloud","tag-ai-ml","tag-b2cloud","entry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Architecting Your AI Data Pipeline Using B2 Overdrive<\/title>\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.backblaze.com\/blog\/architecting-your-ai-data-pipeline-using-b2-overdrive\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Architecting Your AI Data Pipeline Using B2 Overdrive\" \/>\n<meta property=\"og:description\" content=\"Cloud infrastructure for AI isn&#039;t just about compute; it&#039;s also about optimizing data storage and retrieval. Learn how Backblaze B2 and B2 Overdrive can reduce costs and increase performance throughout the five key stages of your AI data pipeline.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.backblaze.com\/blog\/architecting-your-ai-data-pipeline-using-b2-overdrive\/\" \/>\n<meta property=\"og:site_name\" content=\"Backblaze Blog | Cloud Storage &amp; Cloud Backup\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/backblaze\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-22T16:05:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-09-08T18:20:28+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/backblazeprod.wpenginepowered.com\/wp-content\/uploads\/2025\/07\/Backblaze-Architecting-Storage-AI.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1440\" \/>\n\t<meta property=\"og:image:height\" content=\"820\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Jeronimo De Leon\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@backblaze\" \/>\n<meta name=\"twitter:site\" content=\"@backblaze\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Jeronimo De Leon\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Architecting Your AI Data Pipeline Using B2 Overdrive","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.backblaze.com\/blog\/architecting-your-ai-data-pipeline-using-b2-overdrive\/","og_locale":"en_US","og_type":"article","og_title":"Architecting Your AI Data Pipeline Using B2 Overdrive","og_description":"Cloud infrastructure for AI isn't just about compute; it's also about optimizing data storage and retrieval. 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