[{"data":1,"prerenderedAt":261},["ShallowReactive",2],{"breadcrumb-blog-post":3,"community-coming-soon-en":175},{"id":4,"title":5,"author":6,"body":7,"category":160,"date":161,"description":162,"extension":163,"featured":164,"geo":6,"image":165,"manual_override":164,"meta":166,"navigation":167,"path":168,"readTime":169,"schema":6,"section_hashes":6,"seo":170,"sitemap":171,"source_hash":6,"source_locale":6,"stem":172,"tier":173,"tier_1_approved":164,"tier_1_approved_at":6,"tier_1_approved_by":6,"tier_1_deadline":6,"tier_1_reviewer":6,"translated_at":6,"translated_from_hash":6,"translation_model":6,"translation_provider":6,"translation_status":6,"__hash__":174},"blog/blog/2022-02-08-data-pressure.md","Dealing with data-pressure in message-based systems",null,{"type":8,"value":9,"toc":152},"minimark",[10,15,19,22,34,37,41,44,47,50,60,63,66,88,95,106,112,116,119,125,129],[11,12,14],"h2",{"id":13},"what-is-data-pressure","What is data-pressure?",[16,17,18],"p",{},"You hear a lot about data-pressure when it comes to non-stop systems. What is it and why is it so important?",[16,20,21],{},"Pressure in the physical sense describes an imbalance between gas or fluid between two confined compartments. It goes both ways until an equilibrium is reached. If you want to manage it, you usually put a valve between the two.",[16,23,24,25,29,30,33],{},"In data processing systems ",[26,27,28],"strong",{},"data-pressure",", or ",[26,31,32],{},"upstream-pressure"," describes the amount of data which is ready for processing. For file based (batch) solutions this simply describes the amount of files which are waiting to be processed (asynchronous). Processing speed is purely based on the processing power of the downstream actors and is demand based. Data-pressure in batch usually is no threat to system overload because it is implicit. The batch processing system will always only process as much as it can.",[16,35,36],{},"It's a very different story in modern, message-driven, real-time processing environments, however, where data-pressure is explicit because data needs to be processed as it arrives.",[11,38,40],{"id":39},"importance-of-back-pressure-in-non-stop-real-time-systems","Importance of back-pressure in non-stop real-time systems",[16,42,43],{},"Message-driven use-cases usually require that data should be handled in real-time, at all times. Therefore, systems have to be able to scale elastically in order to handle peak loads, or free up unneeded resources during low data-pressure windows.",[16,45,46],{},"There are countless examples of architectures which clog-up when dealing with large data loads. This often results in a vicious-cycle which typically leads to cardiac-arrest of such an architecture. The main conundrum is a missing negative demand-signal (or high data back-pressure-signal) to upstream actors upon which they can react. If there were such a signal, appropriate actions could be taken.",[16,48,49],{},"Such actions could be:",[51,52,53,57],"ul",{},[54,55,56],"li",{},"slowing processing down overall up the data stream, or",[54,58,59],{},"spawning more processing power to handle the added pressure",[16,61,62],{},"Once upstream data-pressure decreases, the counter-measures can be reversed. More data can again be delivered, or previously activated processing power can be decommissioned.",[16,64,65],{},"So to summarize, we have:",[67,68,69,79],"ol",{},[54,70,71,72,75,76,78],{},"a ",[26,73,74],{},"data-signal"," or ",[26,77,32],{}," which signals that data is available for processing, and we have",[54,80,71,81,75,84,87],{},[26,82,83],{},"demand-signal",[26,85,86],{},"back-pressure"," which signals how loaded the downstream actors are, and whether pressure from upstream actors can be relieved on to downstream actors.",[16,89,90],{},[91,92],"img",{"alt":93,"src":94},"Data-pressure Reactivity","/images/blog/2022-02-08/e436ddd5.png",[16,96,97,98,105],{},"Using these signals, the system is able to negotiate an equilibrium between all participants which ensures that processing never stops, but rather slows down (or additional capacity is automatically made available). This problem is well recognized and defined in the ",[99,100,104],"a",{"href":101,"rel":102},"https://www.reactivemanifesto.org/",[103],"nofollow","Reactive Manifesto"," which requires systems to be message-driven, elastic and resilient, and therefore responsive to load. Systems which cater to these requirements are called \"Reactive\".",[16,107,108],{},[91,109],{"alt":110,"src":111},"Reactive Manifesto: Means - Form - Value","/images/blog/2022-02-08/f8cdb1ba.png",[11,113,115],{"id":114},"how-laylineio-handles-it","How layline.io handles it",[16,117,118],{},"It sounds like the solution to the back-pressure challenge is simple. But it's actually hard to solve since all participants in this dance need to be data-pressure aware, both ways. Reactive stream management has solved this problem which is why layline.io takes full advantage it under the hood. It's not for the faint-of-heart, however, and comes with a steep learning and experience curve attached. layline.io shields its users from this complexity in an easy-to-use platform, which provides all production necessary features like UI-driven low-code configurability, one-click deployment, monitoring and much more.",[16,120,121],{},[91,122],{"alt":123,"src":124},"layline.io Project Configuration","/images/blog/2022-02-08/project_workflow_04.webp",[11,126,128],{"id":127},"resources","Resources",[51,130,131,136,145],{},[54,132,133],{},[99,134,104],{"href":101,"rel":135},[103],[54,137,138,139,144],{},"Read more about layline.io ",[99,140,143],{"href":141,"rel":142},"https://layline.io/",[103],"here",".",[54,146,147,148,144],{},"Contact us at ",[99,149,151],{"href":150},"mailto:hello@layline.io","hello@layline.io",{"title":153,"searchDepth":154,"depth":154,"links":155},"",2,[156,157,158,159],{"id":13,"depth":154,"text":14},{"id":39,"depth":154,"text":40},{"id":114,"depth":154,"text":115},{"id":127,"depth":154,"text":128},"Article","2022-02-08","How to deal with data pressure in non-stop message-driven solutions and ensure non-stop uptime under load.","md",false,"/images/blog/2022-02-08/lucas-van-oort-_FjIWDrtfmU-unsplash.webp",{},true,"/blog/2022-02-08-data-pressure","4 min",{"title":5,"description":162},{"loc":168},"blog/2022-02-08-data-pressure","2","x0f2ib8nEa9ZPX713ZxgzY6LLnFGIWWB6pktWteME5k",{"doc":176,"isFallback":164,"effectiveLocale":260},{"title":177,"description":178,"ogTitle":177,"ogDescription":179,"hero":180,"included":197,"status":224,"cta":247,"errors":258,"body":153},"Community Edition Coming Soon | layline.io","The layline.io Community Edition will be released to the public soon. Sign up to be notified when it launches.","Get notified when the layline.io Community Edition launches on GitHub.",{"backLabel":181,"badgeLabel":182,"titleLabel":183,"launchLabel":184,"description":185,"successTitle":186,"successDescription":187,"errorTitle":188,"emailPlaceholder":189,"submittingLabel":190,"notifyLabel":191,"secondaryCtaLabel":192,"trustPoints":193},"Back to Home","Coming Soon","Community Edition","Launching Soon","We're putting the finishing touches on the open-source release of layline.io. The full Community Edition will be available on GitHub very soon.","Check your inbox!","We've sent you a confirmation email. Click the link to complete your signup.","Something went wrong","Enter your email","Submitting...","Notify Me","Or contact us directly",[194,195,196],"Open Source License","Free Forever","Full Documentation",{"titlePrefix":198,"titleHighlight":183,"description":199,"features":200},"What's Included in the","Everything you need to build production-ready data pipelines, completely free and open source.",[201,205,209,213,217,220],{"icon":202,"title":203,"description":204},"i-ph-code","Full Source Code","Complete access to the layline.io codebase under an open-source license.",{"icon":206,"title":207,"description":208},"i-ph-flow-arrow","Visual Workflow Editor","Design data pipelines with our intuitive drag-and-drop interface.",{"icon":210,"title":211,"description":212},"i-ph-lightning","High-Performance Engine","Apache Pekko-powered reactive streaming with sub-millisecond latency.",{"icon":214,"title":215,"description":216},"i-ph-plug","Extensible Connectors","Connect to databases, APIs, message queues, and build custom integrations.",{"icon":202,"title":218,"description":219},"JavaScript & Python","Write custom transformations in your preferred language.",{"icon":221,"title":222,"description":223},"i-ph-users","Community Support","Join our growing community of data engineers and contributors.",{"title":225,"description":226,"steps":227},"Release Status","Track our progress towards the public release",[228,234,236,242],{"title":229,"statusLabel":230,"statusTone":231,"description":232,"icon":233},"Core Engine Development","Complete","complete","High-performance reactive streaming engine built on Apache Pekko.","i-ph-check",{"title":207,"statusLabel":230,"statusTone":231,"description":235,"icon":233},"Intuitive drag-and-drop interface for designing data pipelines.",{"title":237,"statusLabel":238,"statusTone":239,"description":240,"icon":241},"Documentation & Examples","In Progress","progress","Comprehensive guides, tutorials, and example workflows.","i-ph-spinner",{"title":243,"statusLabel":182,"statusTone":244,"description":245,"icon":246},"Public GitHub Release","upcoming","Full source code available under open-source license.","i-ph-circle",{"title":248,"description":249,"primary":250,"secondary":254},"Can't Wait?","Get early access today or talk to our team about the Enterprise Edition with additional features and support.",{"label":251,"to":252,"icon":253},"Get Early Access","/get-started","i-ph-rocket",{"label":255,"to":256,"icon":257},"Compare Editions","/editions/comparison","i-ph-arrow-right",{"unknownSubmitError":259},"Something went wrong. Please try again.","en",1787332365277]