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Systems design
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<h2 id="product-development">Product Development</h2> <p>If the broader topic of product development "blends the perspective of marketing, design, and manufacturing into a single approach to product development,"<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> then design is the act of taking the marketing information and creating the design of the product to be manufactured. </p><p>Thus in product development, systems design involves the process of defining and developing systems, such as interfaces and <a href="/facts/Data/AUBFN97o">data</a>, for an electronic <a href="/facts/Control_system/8CEjIDlS">control system</a> to satisfy specified <a href="/facts/Requirement/bxKc7tgQ">requirements</a>. Systems design could be seen as the application of <a href="/facts/Systems_theory/C56Ck7DQ">systems theory</a> to <a href="/facts/Product_development/ogcXTIco">product development</a>. There is some overlap with the disciplines of <a href="/facts/Systems_analysis/2NwqATNQ">systems analysis</a>, <a href="/facts/Systems_architecture/fDbXSn3s">systems architecture</a> and <a href="/facts/Systems_engineering/gFwRmkDp">systems engineering</a>.<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a><a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a> </p> <h3>Physical design</h3> <p>The physical design relates to the actual input and output processes of the system. This is explained in terms of how data is input into a system, how it is verified/authenticated, how it is processed, and how it is displayed. In physical design, the following requirements about the system are decided. </p> <ol><li>Input requirement,</li> <li>Output requirements,</li> <li>Storage requirements,</li> <li>Processing requirements,</li> <li>System control and backup or recovery.<a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a></li></ol> <p>Put another way, the physical portion of system design can generally be broken down into three sub-tasks: </p> <ol><li>User Interface Design</li> <li>Data Design</li> <li>Process Design</li></ol> <h3>Architecture design</h3> <p>Designing the overall structure of a system focuses on creating a scalable, reliable, and efficient system. For example, services like Google, Twitter, Facebook, Amazon, and Netflix exemplify large-scale distributed systems. Here are key considerations: </p> <ol><li><a href="/facts/Functional_requirement/RrllnLMa">Functional</a> and <a href="/facts/Non-functional_requirement/HQSfMlH2">non-functional</a> requirements</li> <li>Capacity estimation</li> <li>Usage of <a href="/facts/Relational_database/pEKGmJLy">relational</a> and/or <a href="/facts/NoSQL/vvynRKfd">NoSQL</a> databases</li> <li>Vertical scaling, horizontal scaling, <a href="/facts/Shard_(database_architecture)/YSE3YS0M">sharding</a></li> <li><a href="/facts/Load_balancing_(computing)/jddk6ang">Load balancing</a></li> <li>Primary-secondary <a href="/facts/Replication_(computing)/QIaooMjL">replication</a></li> <li>Cache and CDN</li> <li>Stateless and Stateful servers</li> <li>Datacenter <a href="/facts/Geographic_routing/oGBKCwD3">georouting</a></li> <li>Message Queue, Publish-Subscribe Architecture</li> <li>Performance Metrics Monitoring and Logging</li> <li>Build, test, configure deploy automation</li> <li>Finding single point of failure</li> <li><a href="/facts/API/GMlN4vUr">API</a> Rate Limiting</li> <li>Service Level Agreement</li></ol> <h3>Machine Learning Systems Design</h3> <p>Machine learning systems design focuses on building scalable, reliable, and efficient systems that integrate <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> (ML) models to solve real-world problems. ML systems require careful consideration of data pipelines, model training, and deployment infrastructure. ML systems are often used in applications such as <a href="/facts/Recommender_system/HjodW6nS">recommendation engines</a>, <a href="/facts/Artificial_intelligence_in_fraud_detection/pNlHcJbR">fraud detection</a>, and <a href="/facts/Natural_language_processing/1hjMKsSN">natural language processing</a>. </p><p>Key components to consider when designing ML systems include: </p> <ol><li>Problem Definition: Clearly define the problem, data requirements, and evaluation metrics. Success criteria often involve accuracy, latency, and scalability.<a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a></li> <li>Data Pipeline: Build automated pipelines to collect, clean, transform, and validate data.<a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a></li> <li>Model Selection and Training: Choose appropriate algorithms (e.g., <a href="/facts/Linear_regression/5n998IhK">linear regression</a>, <a href="/facts/Decision_trees/XDVeGlkJ">decision trees</a>, <a href="/facts/Neural_networks/DDhJTfMc">neural networks</a>) and train models using frameworks like <a href="/facts/TensorFlow/kDwfBeNd">TensorFlow</a> or <a href="/facts/PyTorch/4Gv1t13B">PyTorch</a>.</li> <li>Deployment and Serving: Deploy trained models to production environments using scalable architectures such as containerized services (e.g., <a href="/facts/Docker_(software)/7IvvsMug">Docker</a> and <a href="/facts/Kubernetes/CI61Msu0">Kubernetes</a>).<a class="footnote-ref" id="fnref:11" href="#fn:11"><sup>11</sup></a></li> <li>Monitoring and Maintenance: Continuously monitor model performance, retrain as necessary, and ensure <a href="/facts/Concept_drift/gLQmz1Rc">data drift</a> is addressed.<a class="footnote-ref" id="fnref:12" href="#fn:12"><sup>12</sup></a></li></ol> <p>Designing an ML system involves balancing trade-offs between accuracy, latency, cost, and maintainability, while ensuring system scalability and reliability. The discipline overlaps with <a href="/facts/MLOps/y8prRtqW">MLOps</a>, a set of practices that unifies machine learning development and operations to ensure smooth deployment and lifecycle management of ML systems. </p> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/Arcadia_(engineering)/HT604VMX">Arcadia (engineering)</a></li> <li><a href="/facts/Architectural_pattern_(computer_science)/GnN0z06K">Architectural pattern (computer science)</a></li> <li><a href="/facts/Configuration_design/DYa4gIuS">Configuration design</a></li> <li><a href="/facts/Electronic_design_automation/o4la3fmX">Electronic design automation</a> (EDA)</li> <li><a href="/facts/Electronic_system-level/vPsKmRR4">Electronic system-level</a> (ESL)</li> <li><a href="/facts/Embedded_system/a4muX1wU">Embedded system</a></li> <li><a href="/facts/Graphical_system_design/QVHv5LEV">Graphical system design</a></li> <li><a href="/facts/Kristo_Ivanov/RVJXbECd">Hypersystems</a></li> <li><a href="/facts/Modular_design/uRrYMyqp">Modular design</a></li> <li><a href="/facts/Morphological_analysis_(problem-solving)/1rUCcp7I">Morphological analysis (problem-solving)</a></li> <li><a href="/facts/Systems_analysis_and_design_(disambiguation)/C8tR8Vmq">Systems analysis and design</a></li> <li><a href="/facts/SCSD_(School_Construction_Systems_Development)_project/PGpwe9bM">SCSD (School Construction Systems Development) project</a></li> <li><a href="/facts/System_information_modelling/4jm3TQuk">System information modelling</a></li> <li><a href="/facts/System_development_life_cycle/qo6p4j6Y">System development life cycle</a> (SDLC)</li> <li><a href="/facts/System_engineering/gFwRmkDp">System engineering</a></li> <li><a href="/facts/System_thinking/C56Ck7DQ">System thinking</a></li> <li><a href="/facts/TRIZ/6Lw9YjMK">TRIZ</a></li></ul> <h2 id="further-reading">Further reading</h2> <ul><li><a href="/facts/Lonnie_D._Bentley/cWAutet0">Bentley, Lonnie D.</a>; <a href="/facts/Kevin_C._Dittman/wotb7U6n">Dittman, Kevin C.</a>; <a href="/facts/Jeffrey_L._Whitten/50SLnMRx">Whitten, Jeffrey L.</a> (2004) [1986]. <i>System analysis and design methods</i>.</li> <li><a href="/facts/C._West_Churchman/ARJFIpQ5">Churchman, C. West</a> (1971). <i>The Design of Inquiring Systems: Basic Concepts of Systems and Organization</i>. New York: Basic Books. <a href="/facts/ISBN_(identifier)/15AdSPa9">ISBN</a> 0-465-01608-1.</li> <li><a href="/facts/William_Gosling_(engineer)/vkU4kKtY">Gosling, William</a> (1962). <a href="https://archive.org/details/designofengineer00gosl"><i>The design of engineering systems</i></a>. New York: Wiley.</li> <li>Hawryszkiewycz, Igor T. (1994). <i>Introduction to system analysis and design</i>. Prentice Hall PTR.</li> <li>Levin, Mark S. (2015). <i>Modular system design and evaluation</i>. Springer.</li> <li>Maier, Mark W.; Rechtin, Eberhardt (2000). <i>The Art of System Architecting</i> (Second ed.). Boca Raton: CRC Press.</li> <li><a href="/facts/Jerry_Saltzer/VBf7aHTJ">J. H. Saltzer</a>; <a href="/facts/David_P._Reed/9TBrXRHY">D. P. Reed</a>; <a href="/facts/David_D._Clark/uRsLKFUd">D. D. Clark</a> (1 November 1984). <a href="https://web.mit.edu/Saltzer/www/publications/endtoend/endtoend.pdf">"End-to-end arguments in system design"</a> (PDF). <i><a href="/facts/ACM_Transactions_on_Computer_Systems/9h0Im15G">ACM Transactions on Computer Systems</a></i>. 2 (4): 277–288. <a href="/facts/Doi_(identifier)/muM9Etpq">doi</a>:<a href="https://doi.org/10.1145%2F357401.357402">10.1145/357401.357402</a>. <a href="/facts/ISSN_(identifier)/DPAflDvU">ISSN</a> <a href="https://search.worldcat.org/issn/0734-2071">0734-2071</a>. <a href="/facts/S2CID_(identifier)/ldJsHa2Y">S2CID</a> <a href="https://api.semanticscholar.org/CorpusID:215746877">215746877</a>. <a href="/facts/WDQ_(identifier)/5Myy74K5">Wikidata</a> Q56503280.</li> <li><a href="/facts/Whitten,_Jeffrey_L./50SLnMRx">Whitten, Jeffrey L.</a>; <a href="/facts/Lonnie_D._Bentley/cWAutet0">Bentley, Lonnie D.</a>; <a href="/facts/Kevin_C._Dittman/wotb7U6n">Dittman, Kevin C.</a> (2004). <i>Fundamentals of system analysis and design methods</i>.</li></ul> <h2 id="external-links">External links</h2> Look up <i>systems design</i> in Wiktionary, the free dictionary. <ul><li><a href="http://www.dcs.gla.ac.uk/~johnson/teaching/isd/course.html">Interactive System Design</a>. Course by Chris Johnson, 1993</li> <li><a href="https://systemdesign.htw-berlin.de/produkte-prozesse/">[1]</a> Course by Prof. Birgit Weller, 2020</li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>Papanek, Victor J. (1984) [1972]. Design for the Real World: Human Ecology and Social Change (2nd ed.). Chicago: Academy Chicago. p. 276. ISBN 0897331532. OCLC 12343986. <a href="0897331532" target="_blank">0897331532</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>Blizzard, Jacqualyn; Klotz, Leidy (2012). "A framework for sustainable whole systems design". R Design Studies. 33 (5): 456–479. doi:10.1016/j.destud.2012.03.001. <a href="https://www.sciencedirect.com/science/article/abs/pii/S0142694X12000105" target="_blank">https://www.sciencedirect.com/science/article/abs/pii/S0142694X12000105</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>Lukosh, Heidi; Bekebrede, Geertje; Kurapati, Shalini; Lukosch, Stephan (2018). "A Scientific Foundation of Simulation Games for the Analysis and Design of Complex Systems". Simulation & Gaming. 49 (3): 279–314. doi:10.1177/1046878118768858. PMC 6187265. PMID 30369775. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187265" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187265</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>Werner, Ulrich (September 1987). "Critical heuristics of social systems design". European Journal of Operational Research. 31 (3): 276-283. doi:10.1016/0377-2217(87)90036-1. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>Ulrich, Karl T.; Eppinger, Steven D. (2000). Product Design and Development (Second ed.). Boston: Irwin McGraw-Hill. <a href="/wiki/Steven_D._Eppinger" target="_blank">/wiki/Steven_D._Eppinger</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>This article incorporates public domain material from Federal Standard 1037C. General Services Administration. Archived from the original on 2022-01-22. <a href="/wiki/Copyright_status_of_works_by_the_federal_government_of_the_United_States" target="_blank">/wiki/Copyright_status_of_works_by_the_federal_government_of_the_United_States</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> <li id="fn:7"><p>This article incorporates public domain material from Dictionary of Military and Associated Terms. United States Department of Defense. <a href="/wiki/Copyright_status_of_works_by_the_federal_government_of_the_United_States" target="_blank">/wiki/Copyright_status_of_works_by_the_federal_government_of_the_United_States</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li> <li id="fn:8"><p>Arden, Trevor (1991). Information technology applications. London: Pitman. ISBN 978-0-273-03470-4. <a href="978-0-273-03470-4" target="_blank">978-0-273-03470-4</a> <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li> <li id="fn:9"><p>Sorvisto, Dayne (2023). MLOps Lifecycle Toolkit: A Software Engineering Roadmap for Designing, Deploying, and Scaling Stochastic Systems. Apress. ISBN 978-1-4842-9641-7. <a href="978-1-4842-9641-7" target="_blank">978-1-4842-9641-7</a> <a href="#fnref:9" class="footnote-back-ref">↩</a></p></li> <li id="fn:10"><p>Polyzotis, Neoklis (2018). "Data Management Challenges in Production Machine Learning". Proceedings of the 2017 ACM SIGMOD International Conference on Management of Data. doi:10.1145/3035918.3054782. <a href="/wiki/Doi_(identifier)" target="_blank">/wiki/Doi_(identifier)</a> <a href="#fnref:10" class="footnote-back-ref">↩</a></p></li> <li id="fn:11"><p>Huyen, Chip (2022). Designing Machine Learning Systems. O'Reilly Media. ISBN 978-1-098-10796-3. <a href="978-1-098-10796-3" target="_blank">978-1-098-10796-3</a> <a href="#fnref:11" class="footnote-back-ref">↩</a></p></li> <li id="fn:12"><p>"Machine Learning at Scale: Challenges and Best Practices". Google Cloud Blog. 2020. <a href="https://cloud.google.com/blog/topics/developers-practitioners/machine-learning-scale-challenges-and-best-practices" target="_blank">https://cloud.google.com/blog/topics/developers-practitioners/machine-learning-scale-challenges-and-best-practices</a> <a href="#fnref:12" class="footnote-back-ref">↩</a></p></li> </ol>