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The document discusses using RabbitMQ as an event tracking architecture to log new events in MongoDB rather than the existing logging service. RabbitMQ would act as a message broker to decouple services so that the web app does not need to know about other services like MixPanel. Other services like analytics and email sending could subscribe to events from RabbitMQ to process them asynchronously and without affecting the user experience.
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This session will begin with a short recap of how we created systems over the past 20 years, up to the current idea of building systems, using a Microservices architecture. What is a Microservices architecture and how does it differ from a Service-Oriented Architecture? Should you use traditional REST APIs to integrate services with each eachother in a Microservcies Architecture? Or is it better to use a more loosely-coupled protocol? Answers to these and many other questions are provided. The talk will show how a distributed log (event hub) can help to create a central, persistent history of events and what benefits we achieve from doing so. Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk shows the difference between a request-driven and event-driven communication and answers when to use which. It highlights how a modern stream processing systems can be used to hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
Building Event Driven (Micro)services with Apache Kafka
What is a Microservices architecture and how does it differ from a Service-Oriented Architecture? Should you use traditional REST APIs to bind services together? Or is it better to use a richer, more loosely-coupled protocol? This talk will start with quick recap of how we created systems over the past 20 years and how different architectures evolved from it. The talk will show how we piece services together in event driven systems, how we use a distributed log (event hub) to create a central, persistent history of events and what benefits we achieve from doing so.
Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk will show the difference between a request-driven and event-driven communication and show when to use which. It highlights how the modern stream processing systems can be used to hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
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Yochay Kiriaty gave a presentation on serverless computing using Microsoft Azure services. He began by defining serverless and its benefits like event-driven scaling, sub-second billing, and abstraction of servers. He then demonstrated several serverless patterns using Azure Functions for tasks like processing data from Blob storage, responding to API requests, and replicating logs between data centers. Throughout the presentation, he emphasized best practices for building serverless applications including designing functions to do single tasks, finish quickly, be stateless and idempotent.
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In November 2014, AWS Lambda introduced developers to serverless compute with automatic scaling, pay-per-request billing, and built-in high availability. As a result, startups and enterprises are changing the way they build their applications. Since then, we've learned a lot from our customers about what it takes to build successful serverless applications. We’ve also seen some common and not so common missteps that developers building serverless applications have made along the way. Today, we're going to share some of those learnings, and show you how you can build the best serverless application that you can.
Building Microservices with Scala, functional domain models and Spring Boot -...
This document summarizes Chris Richardson's presentation on building microservices with Scala, functional domain models, and Spring Boot. The presentation discusses using event sourcing to build event-driven microservices that are eventually consistent. It describes how to design aggregates that generate domain events, implement an event store to persist events immutably, and use event subscribers to update other services and materialized views. The document also covers challenges like handling duplicate events and implementing queries in an eventually consistent system.
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In this talk you will learn about a modern way of designing applications that’s very different from the traditional approach of building monolithic applications that persist mutable domain objects in a relational database.We will talk about the microservice architecture, it’s benefits and drawbacks and how Spring Boot can help. You will learn about implementing business logic using functional, immutable domain models written in Scala. We will describe event sourcing and how it’s an extremely useful persistence mechanism for persisting functional domain objects in a microservices architecture.
Apply best parts of microservices to serverless
Whenever a new paradigm comes along, we often cast the previous incumbents as relics to be forgotten by history, only to then repeat the same mistakes as they once did. On the surface Serverless has revolutionised how we build and run software, but deep down we are still building microservices and face the same challenges. As more of us adopt Serverless and build increasingly complex systems using this new paradigm, it's important to take a moment to reflect on the lessons others have learnt about building microservices and how they can be applied to our Serverless applications.
Microservices with Kafka Ecosystem
Should you use traditional REST APIs to bind services together? Or is it better to use a richer, more loosely-coupled protocol? This talk will dig into how we piece services together in event driven systems, how we use a distributed log (event hub) to create a central, persistent history of events and what benefits we achieve from doing so. Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk will show the difference between a request-driven and event-driven communication and show when to use which. It highlights how the modern stream processing systems can be used to
hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
Event Driven Streaming Analytics - Demostration on Architecture of IoT
1. Devices generate taxi trip data including coordinates and payment info. This data flows through an IoT gateway and platform for real-time and offline analytics applications and services.
2. Traditional request-driven architectures have drawbacks like high latency and lack of scalability, while event-driven architectures address these with low latency, scalability, and high availability.
3. The proposed event-driven architecture uses streaming analytics, publishes and subscribes to enriched events, and provides both online and offline analytics through data pipelines and microservices.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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7 17 event_logging_architecture 2
- 2. Context We’re considering logging a lot of new events Kapil wants to save them in MongoDB rather than use our existing Event Logging Service Rashmi is asking why we don’t use MixPanel for this Jon is lobbying for a consolidated solution
- 3. http RabbitMQ http Analytics Service WebApp Code Logs a “User Signup” Event. EventsDB (mongo or mysql)
- 4. Why use RabbitMQ? Why not just a DelayedJob?
- 5. Other software can subscribe to the same event. Each piece of software stays small. LOOSE COUPLING. The services don’t need to know about each other. The webapp doesn’t need to know that mixpanel even exists! MixPanel ProxyService MixPanel http WebApp Code Logs a “User Signup” Event. http RabbitMQ http Analytics Service EventsDB (mongo or mysql)
- 6. Other things that need to happen on that event can slowly be added as chunks of code that subscribe to that event. Email Sending Service http MixPanel ProxyService MixPanel http WebApp Code Logs a “User Signup” Event. http RabbitMQ http Analytics Service EventsDB (mongo or mysql)
- 7. Why not call mixpaneletc from client-side? Performance. This removes analytics from the page rendering loop. It’s handled afterwards, on our servers. Mixpanel being slow wouldn’t effect our users. We have more back-end coders than front-end coders. This brings analytics into their domain, on the server in ruby.