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You are a reporter for a major world newspaper. Write your response as if you were writing a short, high-quality news article for your paper. Limit your response to one paragraph. Use the following article for context: Stream All the Things: Patterns of Effective Data Stream Processing Explored by Adi Polak at QCon SF - InfoQ<link rel="stylesheet" type="text/css" href="https://cdn.infoq.com/statics_s2_20241128133046/styles/style_en.css"/> <link rel="stylesheet" href="https://cdn.infoq.com/statics_s2_20241128133046/styles/icons.css"> <link rel="stylesheet" type="text/css" media="screen" href="https://cdn.infoq.com/statics_s2_20241128133046/styles/style_extra.css"/><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-W9GJ5DL" height="0" width="0" style="display:none;visibility:hidden"></iframe>BTInfoQ Software Architects' NewsletterA monthly overview of things you need to know as an architect or aspiring architect.View an exampleEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.CloseToggle NavigationFacilitating the Spread of Knowledge and Innovation in Professional Software DevelopmentEnglish editionEnglish editionChinese editionJapanese editionFrench editionWrite for InfoQSearchSign Up / LoginEmailPasswordForgot password ?InfoQ Account EmailBack to loginResend ActivationBack to loginLogin with:GoogleMicrosoftTwitterFacebookDon't have an InfoQ account?Sign UpLogo - Back to homepageNewsArticlesPresentationsPodcastsGuidesTopicsDevelopmentJavaKotlin.NetC#SwiftGoRustJavaScriptFeatured in DevelopmentBeyond the Breach: Proactive Defense in the Age of Advanced ThreatsMichael Brunton-Spall discusses some of the most advanced attacks that are in the public domain, mostly attributed in public by commercial organizations.All in developmentArchitecture & DesignArchitectureEnterprise ArchitectureScalability/PerformanceDesignCase StudiesMicroservicesService MeshPatternsSecurityFeatured in Architecture & DesignThink, Architect, and Sustain Your Serverless Applications As [Set] Pieces!Sheen Brisals discusses how the characteristics of serverless influence us to think in a new way of architecting and evolving modern applications as set piecesAll in architecture-designAI, ML & Data EngineeringBig DataMachine LearningNoSQLDatabaseData AnalyticsStreamingFeatured in AI, ML & Data EngineeringNavigating Responsible AI in the FinTech LandscapeExplore the dynamic intersection of responsible AI, regulation, and ethics in the FinTech sector. 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Join now.InfoQ Dev Summit BostonLearn how senior software developers are solving the challenges you face. Register now with early bird tickets.The Software Architects' NewsletterYour monthly guide to all the topics, technologies and techniques that every professional needs to know about. Subscribe for free.InfoQ HomepageNewsStream All the Things: Patterns of Effective Data Stream Processing Explored by Adi Polak at QCon SFArchitecture & DesignStream All the Things: Patterns of Effective Data Stream Processing Explored by Adi Polak at QCon SFLikeBookmarksNov 29, 20242 min readbySteef-Jan WiggersWrite for InfoQFeed your curiosity.Help 550k+ globalsenior developerseach month stay ahead.Get in touchAdi Polak, Director of Advocacy and Developer Experience Engineering at Confluent, presented "Stream All the Things—Patterns of Effective Data Stream Processing" at the latestQCon San Francisco. Polak's talk highlighted the persistent challenges of data streaming and unveiled pragmatic solutions that can aid organizations in managing scalable and efficient data streaming pipelines.Despite a decade of technological advancements, data streaming has long posed significant challenges for organizations. Teams often spend up to 80% of their efforts troubleshooting issues like downstream output errors or suboptimal pipeline performance. Polak outlined the core expectations for an ideal data streaming solution: reliability, compatibility with diverse systems, low latency, scalability, and high-quality data.However, meeting these demands requires tackling key challenges, including throughput, real-time processing, data integrity, and error handling. The presentation focused on advanced aspects like exactly-once semantics, join operations, and ensuring data integrity while adapting infrastructures for AI-driven applications.Polak introduced several design patterns that address the complexities of data streaming pipelines. These includeDead Letter Queues(DLQ) for error management and patterns for ensuring exactly-once processing across systems.Exactly-Once SemanticsAchievingexactly-once semanticsremains a cornerstone of reliable data processing. Polak contrasted legacy Lambda architectures with modern Kappa architectures, which more deterministically handle real-time events, state, and time. She explained implementing exactly-once guarantees through two-phase commit protocols using tools likeApache KafkaandApache Flink. Operators perform pre-commits, followed by a system-wide commit, ensuring consistency even if individual components fail. Windows-based time calculations (e.g., tumbling, sliding, and session windows) further enhance deterministic processing.Join OperationsJoining data streams—either between stream-batch combinations or two real-time streams—is complex. Polak emphasized the need for precise planning to ensure seamless integration and exactly-once semantics during joins.Error Handling and Data IntegrityData integrity was highlighted as critical for trustworthy pipelines. Polak introduced the concept of "guarding the gates," which includes schema validation, versioning, and serialization using a schema registry. Such measures ensure physical, logical, and referential integrity, preventing "bad things from happening to good data." Pluggable failure enrichers, like automated error-processing tools integrated with Jira, were showcased as solutions for labeling and systematically resolving errors.Polak concluded by exploring the growing intersection of data streaming with AI-driven use cases. Whether powering fraud detection, dynamic personalization, or real-time optimization, the success of AI systems hinges on robust, real-time data infrastructures. She underscored the importance of designing pipelines supporting AI applications' high throughput and low-latency demands.Lastly, Polak left the audience with essential insights for effective data streaming:Prioritize data quality and implement DLQ for error management.Ensure exactly-once guarantees across the system using robust architectures.Plan rigorously for join operations, which are inherently challenging.Healthy error handling begins with clear labeling and systematic resolution.About the AuthorSteef-Jan WiggersShow moreShow lessRate this ArticleAdoptionStyleAuthor ContactedThis content is in theApache KafkatopicRelated Topics:DevelopmentArchitecture & DesignPatterns and PracticesDesign PatternQCon San Francisco 2024Apache KafkaApache FlinkStreamingPatternsRelated EditorialRelated Sponsored ContentPopular across InfoQAurora Limitless: AWS Introduces New PostgreSQL Database with Automated Horizontal ScalingSpring Framework 6.2 and Spring Boot 3.4 Improve Containers, Actuators Ahead of New 2025 GenerationsStripe Rearchitects Its Observability Platform with Managed Prometheus and Grafana on AWSOptimizing Java Applications on Kubernetes: Beyond the BasicsReactive Real-Time Notifications with SSE, Spring Boot, and Redis Pub/SubParticipatory Leadership and Developing a Culture of Psychological SafetyHow could we improve? Take the InfoQ reader surveyEach year, we seek feedback from our readers to help us improve InfoQ.Would you mind spending 2 minutes to share your feedback in ourshort survey?Your feedback will directly help us continually evolve how we support you.The InfoQ TeamTake the survey<div class="widget related__content article__widget"> <h3 class="widget__heading">Related Content</h3> <ul class="no-style cards" data-horizontal="true" data-size="xs" data-tax=""> </ul> </div>The InfoQNewsletterA round-up of last week’s content on InfoQ sent out every Tuesday. Join a community of over 250,000 senior developers.View an exampleEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.DevelopmentCarle Lerche Talking at QCon SF about Rust: a Productive Language for Writing Database ApplicationsGoogle Introduces Gemini AI Features to Android StudioGitHub Universe 2024 Unveils AI Innovations and Developer-Centric ToolsArchitecture & DesignStream All the Things: Patterns of Effective Data Stream Processing Explored by Adi Polak at QCon SFStripe Rearchitects Its Observability Platform with Managed Prometheus and Grafana on AWSThink, Architect, and Sustain Your Serverless Applications As [Set] Pieces!Culture & MethodsSpies, Lies, and Cybercrime: Insider Perspectives from a Former FBI AgentHow to Use Programming Rules and GuidelinesParticipatory Leadership and Developing a Culture of Psychological SafetyAI, ML & Data EngineeringEpoch AI Unveils FrontierMath: A New Frontier in Testing AI's Mathematical Reasoning CapabilitiesMistral AI Releases Two Small Language Model Les MinistrauxNavigating Responsible AI in the FinTech LandscapeDevOps2024 Accelerate State of DevOps Report Shows Pros and Cons of AIRise of Python, Generative AI, and Global Developer Communities: Insights from GitHub Octoverse 2024From Local to Production: a Modern Developer’s Journey towards KubernetesThe InfoQNewsletterA round-up of last week’s content on InfoQ sent out every Tuesday. Join a community of over 250,000 senior developers.View an exampleGet a quick overview of content published on a variety of innovator and early adopter technologiesLearn what you don’t know that you don’t knowStay up to date with the latest information from the topics you are interested inEnter your e-mail addressSelect your countrySelect a countryI consent to InfoQ.com handling my data as explained in thisPrivacy Notice.We protect your privacy.QCon San FranciscoNovember 18-22, 2024.QCon San Francisco International Software Conference returns on November 18-24. More than 1000 software professionals will join together and learn about the emerging trends they should pay attention to in 2024, how to adopt them, how to avoid pitfalls, and how to embrace the best practices.Join the experience and get implementable ideas to shape your projects that last beyond the conference.Register NowHomeCreate accountLoginQCon ConferencesEventsWrite for InfoQInfoQ EditorsAbout InfoQAbout C4MediaMedia KitInfoQ Developer Marketing BlogDiversityEventsQCon LondonAPRIL 7-9, 2025InfoQ Dev Summit BostonJune 9-10, 2025Follow us onYoutube223K FollowersLinkedin21K FollowersRSS19K ReadersX53.4k FollowersFacebook21K LikesAlexaNewStay in the knowThe InfoQ PodcastEngineering Culture PodcastThe Software Architects' NewsletterGeneral Feedbackfeedback@infoq.comAdvertisingsales@infoq.comEditorialeditors@infoq.comMarketingmarketing@infoq.comInfoQ.com and all content copyright © 2006-2024 C4Media Inc.Privacy Notice,Terms And Conditions,Cookie PolicyBT<img height="1" width="1" src="https://www.facebook.com/tr?id=842388869148196&ev=PageView&noscript=1"/>

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what is the latest trending article on infoq about design patterns

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https://www.infoq.com/news/2024/11/effective-data-stream-processing/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Architecture+%26+Design

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Adi Polak's presentation at QCon San Francisco, titled "Stream All the Things—Patterns of Effective Data Stream Processing," has been highlighting the latest trends in design patterns for data stream processing. Polak, the Director of Advocacy and Developer Experience Engineering at Confluent, discussed the significant challenges organizations face with data streaming and introduced various design patterns to address these complexities. Key solutions she presented include Dead Letter Queues for error management and ensuring exactly-once processing across systems. Her discussion also encompassed the complexities of join operations, error handling, and the integration of data streaming with AI-driven applications. Polak's insights emphasize the importance of achieving reliable, low-latency, and high-quality data streaming solutions, essential for meeting the advanced requirements of modern AI applications.