�ݺ�ߣshows by User: NeilAvery1

�ݺ�ߣshows by User: NeilAvery1 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: NeilAvery1 / Thu, 07 Nov 2019 10:09:04 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: NeilAvery1 Serverless London 2019 FaaS composition using Kafka and CloudEvents /slideshow/serverless-london-2019-faas-composition-using-kafka-and-cloudevents/191315165 serverlesslondon2019-faascompositionusingkafkaandcloud-events-191107100904
FaaS composition using Kafka and Cloud-Events LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/ Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member). Objective of the talk You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture.]]>
FaaS composition using Kafka and Cloud-Events LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/ Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member). Objective of the talk You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture.]]> Thu, 07 Nov 2019 10:09:04 GMT /slideshow/serverless-london-2019-faas-composition-using-kafka-and-cloudevents/191315165 NeilAvery1@slideshare.net(NeilAvery1) Serverless London 2019 FaaS composition using Kafka and CloudEvents NeilAvery1 FaaS composition using Kafka and Cloud-Events LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/ Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member). Objective of the talk You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/serverlesslondon2019-faascompositionusingkafkaandcloud-events-191107100904-thumbnail.jpg?width=120&height=120&fit=bounds" /> FaaS composition using Kafka and Cloud-Events LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/ Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member). Objective of the talk You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture.

Serverless London 2019 FaaS composition using Kafka and CloudEvents from Neil Avery

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0 Kafka summit SF 2019 - the art of the event-streaming app /slideshow/kafka-summit-sf-2019-the-art-of-the-eventstreaming-app/178246704 kafkasummitsf2019-theartoftheevent-streamingapp-191001172826
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.]]>
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.]]> Tue, 01 Oct 2019 17:28:26 GMT /slideshow/kafka-summit-sf-2019-the-art-of-the-eventstreaming-app/178246704 NeilAvery1@slideshare.net(NeilAvery1) Kafka summit SF 2019 - the art of the event-streaming app NeilAvery1 Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kafkasummitsf2019-theartoftheevent-streamingapp-191001172826-thumbnail.jpg?width=120&height=120&fit=bounds" /> Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.

Kafka summit SF 2019 - the art of the event-streaming app from Neil Avery

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0 Cloud Native London 2019 Faas composition using Kafka and cloud-events /NeilAvery1/cloud-native-2019-faas-composition-using-kafka-and-cloudevents-176022029 cloudnative2019-faascompositionusingkafkaandcloud-events-190925160736
Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions you can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means you can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member).]]>
Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions you can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means you can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member).]]> Wed, 25 Sep 2019 16:07:36 GMT /NeilAvery1/cloud-native-2019-faas-composition-using-kafka-and-cloudevents-176022029 NeilAvery1@slideshare.net(NeilAvery1) Cloud Native London 2019 Faas composition using Kafka and cloud-events NeilAvery1 Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions you can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means you can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/cloudnative2019-faascompositionusingkafkaandcloud-events-190925160736-thumbnail.jpg?width=120&height=120&fit=bounds" /> Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions you can build a homogenous ecosystem to run FaaS applications. Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means you can democratize and organize FaaS environments in a way that scales across the enterprise. Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member).

Cloud Native London 2019 Faas composition using Kafka and cloud-events from Neil Avery

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0 Kakfa summit london 2019 - the art of the event-streaming app /slideshow/kakfa-summit-london-2019-the-art-of-the-eventstreaming-app/145250062 kakfasummitlondon2019-theartoftheevent-streamingapp-190513090842
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed real-time database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through the patterns for: – Scalable payment processing – Run it on rails: Instrumentation and monitoring – Control flow patterns Finally, all of these concepts are combined in a solution architecture that can be used at an enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.]]>
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed real-time database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through the patterns for: – Scalable payment processing – Run it on rails: Instrumentation and monitoring – Control flow patterns Finally, all of these concepts are combined in a solution architecture that can be used at an enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.]]> Mon, 13 May 2019 09:08:42 GMT /slideshow/kakfa-summit-london-2019-the-art-of-the-eventstreaming-app/145250062 NeilAvery1@slideshare.net(NeilAvery1) Kakfa summit london 2019 - the art of the event-streaming app NeilAvery1 Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed real-time database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through the patterns for: – Scalable payment processing – Run it on rails: Instrumentation and monitoring – Control flow patterns Finally, all of these concepts are combined in a solution architecture that can be used at an enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kakfasummitlondon2019-theartoftheevent-streamingapp-190513090842-thumbnail.jpg?width=120&height=120&fit=bounds" /> Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed real-time database. In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through the patterns for: – Scalable payment processing – Run it on rails: Instrumentation and monitoring – Control flow patterns Finally, all of these concepts are combined in a solution architecture that can be used at an enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.

Kakfa summit london 2019 - the art of the event-streaming app from Neil Avery

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0 Building Ebay using Serverless and stream processing - Big Data London November 2018 /slideshow/building-ebay-using-serverless-and-stream-processing-big-data-london-november-2018/123075248 serverlessandstreamprocessing-bigdatalondon-2018-181115094303
Serverless brings with it a groundswell of interest in event-driven architectures. Many advocate FaaS as a natural fit for stream processing and event-driven design, but is that just marketing speak? In this talk, I will dispel the myths behind serverless and show how it can form part of a data flow, event-driven streaming architecture that could power ‘eBay’. I dive into how the data flow model works with streams and stream processors interacting to provide a network of related data and essentially Kafka becomes a deconstructed database. I then elaborate on FaaS, the challenges, and uses and how it is becoming an essential part of being a cloud-native story that fits with Streaming architectures. This is all tied together by walking through data flow functionality like item-placement, item-bidding, item-search, auction analytics and where FaaS fits into these!]]>
Serverless brings with it a groundswell of interest in event-driven architectures. Many advocate FaaS as a natural fit for stream processing and event-driven design, but is that just marketing speak? In this talk, I will dispel the myths behind serverless and show how it can form part of a data flow, event-driven streaming architecture that could power ‘eBay’. I dive into how the data flow model works with streams and stream processors interacting to provide a network of related data and essentially Kafka becomes a deconstructed database. I then elaborate on FaaS, the challenges, and uses and how it is becoming an essential part of being a cloud-native story that fits with Streaming architectures. This is all tied together by walking through data flow functionality like item-placement, item-bidding, item-search, auction analytics and where FaaS fits into these!]]> Thu, 15 Nov 2018 09:43:03 GMT /slideshow/building-ebay-using-serverless-and-stream-processing-big-data-london-november-2018/123075248 NeilAvery1@slideshare.net(NeilAvery1) Building Ebay using Serverless and stream processing - Big Data London November 2018 NeilAvery1 Serverless brings with it a groundswell of interest in event-driven architectures. Many advocate FaaS as a natural fit for stream processing and event-driven design, but is that just marketing speak? In this talk, I will dispel the myths behind serverless and show how it can form part of a data flow, event-driven streaming architecture that could power ‘eBay’. I dive into how the data flow model works with streams and stream processors interacting to provide a network of related data and essentially Kafka becomes a deconstructed database. I then elaborate on FaaS, the challenges, and uses and how it is becoming an essential part of being a cloud-native story that fits with Streaming architectures. This is all tied together by walking through data flow functionality like item-placement, item-bidding, item-search, auction analytics and where FaaS fits into these! <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/serverlessandstreamprocessing-bigdatalondon-2018-181115094303-thumbnail.jpg?width=120&height=120&fit=bounds" /> Serverless brings with it a groundswell of interest in event-driven architectures. Many advocate FaaS as a natural fit for stream processing and event-driven design, but is that just marketing speak? In this talk, I will dispel the myths behind serverless and show how it can form part of a data flow, event-driven streaming architecture that could power ‘eBay’. I dive into how the data flow model works with streams and stream processors interacting to provide a network of related data and essentially Kafka becomes a deconstructed database. I then elaborate on FaaS, the challenges, and uses and how it is becoming an essential part of being a cloud-native story that fits with Streaming architectures. This is all tied together by walking through data flow functionality like item-placement, item-bidding, item-search, auction analytics and where FaaS fits into these!

Building Ebay using Serverless and stream processing - Big Data London November 2018 from Neil Avery

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0 https://cdn.slidesharecdn.com/profile-photo-NeilAvery1-48x48.jpg?cb=1569427507 Work on all the cool things for Streaming and Apache Kafka at Confluent www.neilavery.com https://cdn.slidesharecdn.com/ss_thumbnails/serverlesslondon2019-faascompositionusingkafkaandcloud-events-191107100904-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/serverless-london-2019-faas-composition-using-kafka-and-cloudevents/191315165 Serverless London 2019... https://cdn.slidesharecdn.com/ss_thumbnails/kafkasummitsf2019-theartoftheevent-streamingapp-191001172826-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/kafka-summit-sf-2019-the-art-of-the-eventstreaming-app/178246704 Kafka summit SF 2019 -... https://cdn.slidesharecdn.com/ss_thumbnails/cloudnative2019-faascompositionusingkafkaandcloud-events-190925160736-thumbnail.jpg?width=320&height=320&fit=bounds NeilAvery1/cloud-native-2019-faas-composition-using-kafka-and-cloudevents-176022029 Cloud Native London 20...