際際滷shows by User: TarasSlipets / http://www.slideshare.net/images/logo.gif 際際滷shows by User: TarasSlipets / Sun, 09 Apr 2023 18:52:43 GMT 際際滷Share feed for 際際滷shows by User: TarasSlipets FlixBus Ride with Snowflake /slideshow/flixbus-ride-with-snowflake/257269125 flixbusridewithsnowflake-230409185243-935cecc9
Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles.]]>
Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles.]]> Sun, 09 Apr 2023 18:52:43 GMT /slideshow/flixbus-ride-with-snowflake/257269125 TarasSlipets@slideshare.net(TarasSlipets) FlixBus Ride with Snowflake TarasSlipets Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/flixbusridewithsnowflake-230409185243-935cecc9-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Our ride with Snowflake began 4 years ago. We faced the daunting task of building a decentralized data platform that could empower our 50+ engineering and analytical teams with autonomy while complying with international regulations. Snowflake has quickly become an essential component of our platform, enabling new cross-teams and cross-department data-sharing scenarios that have led to significant time-to-market and cost reductions (up to 2x). Fine-grained RBAC allows us to quickly adapt to rapidly changing local and international compliance regulations. Nowadays, we are proud to present our distributed data platform based on Snowflake, which adheres to fundamental data-mesh principles.
FlixBus Ride with Snowflake from Taras Slipets
]]> 469 0 https://cdn.slidesharecdn.com/ss_thumbnails/flixbusridewithsnowflake-230409185243-935cecc9-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Serverless Kafka Patterns /slideshow/serverless-kafka-patterns/253109034 serverlesskafkapatterns-220922051044-602b1502
Kafka is a top-notch industry platform for streaming data processing at scale. No surprise that first-class citizens of the Kafka world are 24/7-running producer/consumer applications (e.g. classical servers, k8s-pods, etc.) But what about the rapidly rising world of cloud-native Serverless ecosystems? This talk summarizes the practical experience of Serverless paradigm application for Kafka production/consumption in AWS.]]>
Kafka is a top-notch industry platform for streaming data processing at scale. No surprise that first-class citizens of the Kafka world are 24/7-running producer/consumer applications (e.g. classical servers, k8s-pods, etc.) But what about the rapidly rising world of cloud-native Serverless ecosystems? This talk summarizes the practical experience of Serverless paradigm application for Kafka production/consumption in AWS.]]> Thu, 22 Sep 2022 05:10:43 GMT /slideshow/serverless-kafka-patterns/253109034 TarasSlipets@slideshare.net(TarasSlipets) Serverless Kafka Patterns TarasSlipets Kafka is a top-notch industry platform for streaming data processing at scale. No surprise that first-class citizens of the Kafka world are 24/7-running producer/consumer applications (e.g. classical servers, k8s-pods, etc.) But what about the rapidly rising world of cloud-native Serverless ecosystems? This talk summarizes the practical experience of Serverless paradigm application for Kafka production/consumption in AWS. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/serverlesskafkapatterns-220922051044-602b1502-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Kafka is a top-notch industry platform for streaming data processing at scale. No surprise that first-class citizens of the Kafka world are 24/7-running producer/consumer applications (e.g. classical servers, k8s-pods, etc.) But what about the rapidly rising world of cloud-native Serverless ecosystems? This talk summarizes the practical experience of Serverless paradigm application for Kafka production/consumption in AWS.
Serverless Kafka Patterns from Taras Slipets
]]> 20 0 https://cdn.slidesharecdn.com/ss_thumbnails/serverlesskafkapatterns-220922051044-602b1502-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Customers feedback from data mess to data mesh /slideshow/customer-presentation-by-flixmobility-customers-feedback-from-data-mess-to-data-mesh/253063846 customersfeedbackfromdatamesstodatamesh-220920130628-856c9a1d
Five phases Flixmobilty went through on their journey to decentralized cross-department data analysis and business intelligence on direct customer feedback.]]>
Five phases Flixmobilty went through on their journey to decentralized cross-department data analysis and business intelligence on direct customer feedback.]]> Tue, 20 Sep 2022 13:06:27 GMT /slideshow/customer-presentation-by-flixmobility-customers-feedback-from-data-mess-to-data-mesh/253063846 TarasSlipets@slideshare.net(TarasSlipets) Customers feedback from data mess to data mesh TarasSlipets Five phases Flixmobilty went through on their journey to decentralized cross-department data analysis and business intelligence on direct customer feedback. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/customersfeedbackfromdatamesstodatamesh-220920130628-856c9a1d-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Five phases Flixmobilty went through on their journey to decentralized cross-department data analysis and business intelligence on direct customer feedback.
Customers feedback from data mess to data mesh from Taras Slipets
]]> 19 0 https://cdn.slidesharecdn.com/ss_thumbnails/customersfeedbackfromdatamesstodatamesh-220920130628-856c9a1d-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Experiment more, pay less for your AWS ML.pdf /slideshow/experiment-more-pay-less-for-your-aws-mlpdf/252168012 experimentmorepaylessforyourawsml-220712155019-18160569
Review day to day routines of Dara Scientist and/or Data Engineer. Compare resources usage patterns and describe possible infrastructure/costs optimization techniques.]]>
Review day to day routines of Dara Scientist and/or Data Engineer. Compare resources usage patterns and describe possible infrastructure/costs optimization techniques.]]> Tue, 12 Jul 2022 15:50:19 GMT /slideshow/experiment-more-pay-less-for-your-aws-mlpdf/252168012 TarasSlipets@slideshare.net(TarasSlipets) Experiment more, pay less for your AWS ML.pdf TarasSlipets Review day to day routines of Dara Scientist and/or Data Engineer. Compare resources usage patterns and describe possible infrastructure/costs optimization techniques. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/experimentmorepaylessforyourawsml-220712155019-18160569-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Review day to day routines of Dara Scientist and/or Data Engineer. Compare resources usage patterns and describe possible infrastructure/costs optimization techniques.
Experiment more, pay less for your AWS ML.pdf from Taras Slipets
]]> 18 0 https://cdn.slidesharecdn.com/ss_thumbnails/experimentmorepaylessforyourawsml-220712155019-18160569-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Fantastic datasets and where to find them /slideshow/fantastic-datasets-and-where-to-find-them-251205241/251205241 fantasticdatasetsandwheretofindthem-220219095733
Data engineering basics, architectural concepts for big data, tools ecosystem overview and lessons learned from practical 3+ years of experience.]]>
Data engineering basics, architectural concepts for big data, tools ecosystem overview and lessons learned from practical 3+ years of experience.]]> Sat, 19 Feb 2022 09:57:33 GMT /slideshow/fantastic-datasets-and-where-to-find-them-251205241/251205241 TarasSlipets@slideshare.net(TarasSlipets) Fantastic datasets and where to find them TarasSlipets Data engineering basics, architectural concepts for big data, tools ecosystem overview and lessons learned from practical 3+ years of experience. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fantasticdatasetsandwheretofindthem-220219095733-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Data engineering basics, architectural concepts for big data, tools ecosystem overview and lessons learned from practical 3+ years of experience.
Fantastic datasets and where to find them from Taras Slipets
]]> 774 0 https://cdn.slidesharecdn.com/ss_thumbnails/fantasticdatasetsandwheretofindthem-220219095733-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Seven Cloud Sins of DevOps /slideshow/seven-cloud-sins-of-devops/197357477 sevencloudsinsofdevops-191125092037
Cloud computing is widely used by industry for more than a decade. There are many patterns, best practices and tools around it including DevOps, despite that, they do not prevent from shouting yourself if misused. This talk is a summary of practical experience and observations about top-most misuse of DevOps practices when applied to cloud software engineering and operations. AWS Cloud provider is used for cases examples.]]>
Cloud computing is widely used by industry for more than a decade. There are many patterns, best practices and tools around it including DevOps, despite that, they do not prevent from shouting yourself if misused. This talk is a summary of practical experience and observations about top-most misuse of DevOps practices when applied to cloud software engineering and operations. AWS Cloud provider is used for cases examples.]]> Mon, 25 Nov 2019 09:20:36 GMT /slideshow/seven-cloud-sins-of-devops/197357477 TarasSlipets@slideshare.net(TarasSlipets) Seven Cloud Sins of DevOps TarasSlipets Cloud computing is widely used by industry for more than a decade. There are many patterns, best practices and tools around it including DevOps, despite that, they do not prevent from shouting yourself if misused. This talk is a summary of practical experience and observations about top-most misuse of DevOps practices when applied to cloud software engineering and operations. AWS Cloud provider is used for cases examples. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sevencloudsinsofdevops-191125092037-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Cloud computing is widely used by industry for more than a decade. There are many patterns, best practices and tools around it including DevOps, despite that, they do not prevent from shouting yourself if misused. This talk is a summary of practical experience and observations about top-most misuse of DevOps practices when applied to cloud software engineering and operations. AWS Cloud provider is used for cases examples.
Seven Cloud Sins of DevOps from Taras Slipets
]]> 301 0 https://cdn.slidesharecdn.com/ss_thumbnails/sevencloudsinsofdevops-191125092037-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Evolution of AWS infrastructure for ML: from Zero to Hero /slideshow/evolution-of-aws-infrastructure-for-ml-from-zero-to-hero/142195280 evolutionofawsinfrastructureforml-190425175722
Real experience of building and evolution of Machine Learning model using AWS ecosystem from from scratch to fully-fledged production solution generating 20M predictions per day just in 2 month.]]>
Real experience of building and evolution of Machine Learning model using AWS ecosystem from from scratch to fully-fledged production solution generating 20M predictions per day just in 2 month.]]> Thu, 25 Apr 2019 17:57:22 GMT /slideshow/evolution-of-aws-infrastructure-for-ml-from-zero-to-hero/142195280 TarasSlipets@slideshare.net(TarasSlipets) Evolution of AWS infrastructure for ML: from Zero to Hero TarasSlipets Real experience of building and evolution of Machine Learning model using AWS ecosystem from from scratch to fully-fledged production solution generating 20M predictions per day just in 2 month. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/evolutionofawsinfrastructureforml-190425175722-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Real experience of building and evolution of Machine Learning model using AWS ecosystem from from scratch to fully-fledged production solution generating 20M predictions per day just in 2 month.
Evolution of AWS infrastructure for ML: from Zero to Hero from Taras Slipets
]]> 237 2 https://cdn.slidesharecdn.com/ss_thumbnails/evolutionofawsinfrastructureforml-190425175722-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 DevOps applied: Survival guide /slideshow/devops-applied-survival-guide/125359666 devopsappliedsurvivalguide-181208094359
Practical success story for building DevOps culture in Product company within classical development team from scratch: growing t-shaped skills, knowledge sharing practices used, tools to build efficient delivery ecosystem. https://xpdays.com.ua/programs/devops-applied-survival-guide/]]>
Practical success story for building DevOps culture in Product company within classical development team from scratch: growing t-shaped skills, knowledge sharing practices used, tools to build efficient delivery ecosystem. https://xpdays.com.ua/programs/devops-applied-survival-guide/]]> Sat, 08 Dec 2018 09:43:58 GMT /slideshow/devops-applied-survival-guide/125359666 TarasSlipets@slideshare.net(TarasSlipets) DevOps applied: Survival guide TarasSlipets Practical success story for building DevOps culture in Product company within classical development team from scratch: growing t-shaped skills, knowledge sharing practices used, tools to build efficient delivery ecosystem. https://xpdays.com.ua/programs/devops-applied-survival-guide/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/devopsappliedsurvivalguide-181208094359-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Practical success story for building DevOps culture in Product company within classical development team from scratch: growing t-shaped skills, knowledge sharing practices used, tools to build efficient delivery ecosystem. https://xpdays.com.ua/programs/devops-applied-survival-guide/
DevOps applied: Survival guide from Taras Slipets
]]> 214 1 https://cdn.slidesharecdn.com/ss_thumbnails/devopsappliedsurvivalguide-181208094359-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Full stack, Full run, Full test /slideshow/full-stack-fullrunfulltest/119300484 fullstackfullrunfulltest-181013092748
Practical example of simplifying full-stack development and testing routines using containerisation and orchestration techniques. Sample application: data streaming app with React.js / Apache Kafka / Java SpringBoot / Elasticsearch based on Docker / Kubernetes orchestration. -- Web Tech Fun 2018 Conference Chernihiv, Ukraine]]>
Practical example of simplifying full-stack development and testing routines using containerisation and orchestration techniques. Sample application: data streaming app with React.js / Apache Kafka / Java SpringBoot / Elasticsearch based on Docker / Kubernetes orchestration. -- Web Tech Fun 2018 Conference Chernihiv, Ukraine]]> Sat, 13 Oct 2018 09:27:47 GMT /slideshow/full-stack-fullrunfulltest/119300484 TarasSlipets@slideshare.net(TarasSlipets) Full stack, Full run, Full test TarasSlipets Practical example of simplifying full-stack development and testing routines using containerisation and orchestration techniques. Sample application: data streaming app with React.js / Apache Kafka / Java SpringBoot / Elasticsearch based on Docker / Kubernetes orchestration. -- Web Tech Fun 2018 Conference Chernihiv, Ukraine <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fullstackfullrunfulltest-181013092748-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Practical example of simplifying full-stack development and testing routines using containerisation and orchestration techniques. Sample application: data streaming app with React.js / Apache Kafka / Java SpringBoot / Elasticsearch based on Docker / Kubernetes orchestration. -- Web Tech Fun 2018 Conference Chernihiv, Ukraine
Full stack, Full run, Full test from Taras Slipets
]]> 247 1 https://cdn.slidesharecdn.com/ss_thumbnails/fullstackfullrunfulltest-181013092748-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Java Developers /slideshow/java-developers-81495720/81495720 tarasslipetsjavadevelopers-171102074148
JuJa Conf 2017 27.05.2017]]>
JuJa Conf 2017 27.05.2017]]> Thu, 02 Nov 2017 07:41:48 GMT /slideshow/java-developers-81495720/81495720 TarasSlipets@slideshare.net(TarasSlipets) Java Developers TarasSlipets JuJa Conf 2017 27.05.2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tarasslipetsjavadevelopers-171102074148-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> JuJa Conf 2017 27.05.2017
Java Developers from Taras Slipets
]]> 177 3 https://cdn.slidesharecdn.com/ss_thumbnails/tarasslipetsjavadevelopers-171102074148-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Testing in Legacy /slideshow/testing-in-legacy/81495626 tarasslipetstestinginlegacy-171102073808
Ciklum Java Meetup in Gdansk 14.03.2016]]>
Ciklum Java Meetup in Gdansk 14.03.2016]]> Thu, 02 Nov 2017 07:38:08 GMT /slideshow/testing-in-legacy/81495626 TarasSlipets@slideshare.net(TarasSlipets) Testing in Legacy TarasSlipets Ciklum Java Meetup in Gdansk 14.03.2016 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tarasslipetstestinginlegacy-171102073808-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Ciklum Java Meetup in Gdansk 14.03.2016
Testing in Legacy from Taras Slipets
]]> 127 3 https://cdn.slidesharecdn.com/ss_thumbnails/tarasslipetstestinginlegacy-171102073808-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Testing in Legacy: From Rags to Riches /slideshow/testing-in-legacy-from-rags-to-riches/81495502 testinglegacyfromfromragstoriches-171102073231
JavaDay Kharkiv 2015]]>
JavaDay Kharkiv 2015]]> Thu, 02 Nov 2017 07:32:30 GMT /slideshow/testing-in-legacy-from-rags-to-riches/81495502 TarasSlipets@slideshare.net(TarasSlipets) Testing in Legacy: From Rags to Riches TarasSlipets JavaDay Kharkiv 2015 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/testinglegacyfromfromragstoriches-171102073231-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> JavaDay Kharkiv 2015
Testing in Legacy: From Rags to Riches from Taras Slipets
]]> 117 3 https://cdn.slidesharecdn.com/ss_thumbnails/testinglegacyfromfromragstoriches-171102073231-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 What developers can really contribute in DevOps concept? /slideshow/what-developers-can-really-contribute-in-devops-concept/81495400 devops-171102072808
JUG talk on 13.08.2014]]>
JUG talk on 13.08.2014]]> Thu, 02 Nov 2017 07:28:08 GMT /slideshow/what-developers-can-really-contribute-in-devops-concept/81495400 TarasSlipets@slideshare.net(TarasSlipets) What developers can really contribute in DevOps concept? TarasSlipets JUG talk on 13.08.2014 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/devops-171102072808-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> JUG talk on 13.08.2014
What developers can really contribute in DevOps concept? from Taras Slipets
]]> 86 1 https://cdn.slidesharecdn.com/ss_thumbnails/devops-171102072808-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 仍亳 亢亳亰仆 弍亠亰 /slideshow/ss-54631473/54631473 goit-v1-151102064342-lva1-app6891
弌 亟仍 仆仂于亳从仂于]]>
弌 亟仍 仆仂于亳从仂于]]> Mon, 02 Nov 2015 06:43:41 GMT /slideshow/ss-54631473/54631473 TarasSlipets@slideshare.net(TarasSlipets) 仍亳 亢亳亰仆 弍亠亰 TarasSlipets 弌 亟仍 仆仂于亳从仂于 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/goit-v1-151102064342-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 弌 亟仍 仆仂于亳从仂于
仍亳 亢亳亰仆 弍亠亰 from Taras Slipets
]]> 334 4 https://cdn.slidesharecdn.com/ss_thumbnails/goit-v1-151102064342-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-TarasSlipets-48x48.jpg?cb=1705412961 tarasslipets.com https://cdn.slidesharecdn.com/ss_thumbnails/flixbusridewithsnowflake-230409185243-935cecc9-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/flixbus-ride-with-snowflake/257269125 FlixBus Ride with Snow... https://cdn.slidesharecdn.com/ss_thumbnails/serverlesskafkapatterns-220922051044-602b1502-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/serverless-kafka-patterns/253109034 Serverless Kafka Patterns https://cdn.slidesharecdn.com/ss_thumbnails/customersfeedbackfromdatamesstodatamesh-220920130628-856c9a1d-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/customer-presentation-by-flixmobility-customers-feedback-from-data-mess-to-data-mesh/253063846 Customers feedback f...