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At Stitch Fix, we maintain a distributed Kafka Connect cluster running several hundred connectors. Over the years, we've learned invaluable lessons for keeping our connectors going 24/7. As many conference goers probably know, event driven applications require a new way of thinking. With this new paradigm comes unique operational considerations, which I will delve into. Specifically, this talk will be an overview of: 1) Our deployment model and use case (we have a large distributed Kafka Connect cluster that powers a self-service data integration platform tailored to the needs of our Data Scientists). 2) Our favorite operational tools that we have built for making things run smoothly (the jobs, alerts and dashboards we find most useful. A quick run down of the admin service we wrote that sits on top of Kafka Connect). 3) Our approach to end-to-end integrity monitoring (our tracer bullet system that we built to constantly monitor all our sources and sinks). 4) Lessons learned from production issues and painful migrations (why, oh why did we not use schemas from the beginning?? Pausing connectors doesn't do what you think it does... rebalancing is tricky... jar hell problems are a thing of the past, upgrade and use plugin.path!). 5) Future areas of improvement. The target audience member is an engineer who is curious about Kafka Connect or currently maintains a small to medium sized Kafka Connect cluster. They should walk away from the talk with increased confidence in using and maintaining a large Kafka Connect cluster, and should be armed with the hard won experiences of our team. For the most part, we've been very happy with our Kafka Connect powered data integration platform, and we'd love to share our lessons learned with the community in order to drive adoption.

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Tracing in the world of micro services has become a standard with people using distributed tracers like Zipkin, Jaeger, Appdash etc. But, with so many different tracers, its confusing to choose one tracer and then painful to replace a tracer. That's where OpenTracing comes in. OT provides a consistent, vendor-neutral API to allow users to choose whatever distributed tracer they need and can change the tracer with just an O(1) operation.

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NATS 2.0 is the largest feature release since the original code base for the server was released. NATS 2.0 was created to allow a new way of thinking about NATS as a shared utility, solving problems at scale through distributed security, multi-tenancy, larger networks, and secure sharing of data. In this presentation, Derek discusses the motives behind the newest features of NATS and how to leverage them to reduce total cost of ownership, decrease time to value, support extremely large scale deployments, and decentralize security to create secure and easy to manage modern distributed systems.

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Here's the challenge: we've got a Kafka topic, where services publish messages to be delivered to browser-based clients through web sockets. Sounds simple? It might, but we're faced with an increasing number of messages, as well as a growing count of web socket clients. How do we scale our solution? As our system contains a larger number of servers, failures become more frequent. How to ensure fault tolerance? There’s a couple possible architectures. Each websocket node might consume all messages. Otherwise, we need an intermediary, which redistributes the messages to the proper web socket nodes. Here, we might either use a Kafka topic, or a streaming forwarding service. However, we still need a feedback loop so that the intermediary knows where to distribute messages. We’ll take a look at the strengths and weaknesses of each solution, as well as limitations created by the chosen technologies (Kafka and web sockets).

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Apache Kafka is the most used data streaming broker by companies. It could manage millions of messages easily and it is the base of many architectures based in events, micro-services, orchestration, ... and now cloud environments. OpenShift is the most extended Platform as a Service (PaaS). It is based in Kubernetes and it helps the companies to deploy easily any kind of workload in a cloud environment. Thanks many of its features it is the base for many architectures based in stateless applications to build new Cloud Native Applications. Strimzi is an open source community that implements a set of Kubernetes Operators to help you to manage and deploy Apache Kafka brokers in OpenShift environments. These slides will introduce you Strimzi as a new component on OpenShift to manage your Apache Kafka clusters. Slides used at OpenShift Meetup Spain: - https://www.meetup.com/es-ES/openshift_spain/events/261284764/

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In order to maximize Kafka accessibility within an organization, Kafka operators must choose an authentication option that balances security with ease of use. Kafka has been historically limited to a small number of authentication options that are difficult to integrate with a Single Signon (SSO) strategy, such as mutual TLS, basic auth, and Kerberos. The arrival of SASL/OAUTHBEARER in Kafka 2.0.0 affords system operators a flexible framework for integrating Kafka with their existing authentication infrastructure. Ron Dagostino (State Street Corporation) and Mike Kaminski (The New York Times) team up to discuss SASL/OAUTHBEARER and it’s real-world applications. Ron, who contributed the feature to core Kafka, explains the origins and intricacies of its development along with additional, related security changes, including client re-authentication (merged and scheduled for release in v2.2.0) and the plans for support of SASL/OAUTHBEARER in librdkafka-based clients. Mike Kaminski, a developer on The Publishing Pipeline team at The New York Times, talks about how his team leverages SASL/OAUTHBEARER to break down silos between teams by making it easy for product owners to get connected to the Publishing Pipeline’s Kafka cluster.

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Nancy is a lightweight, low-ceremony, framework for building HTTP based services on .Net and Mono. The goal of the framework is to stay out of the way as much as possible and provide a super-duper-happy-path to all interactions. Find more about it at nancyfx.org. This Slide deck (in English) used at the DWX Conference in Nürnberg in July 2013 and provides you with an overview of the basic elements of the framework. The presentation material as well as the demo code can be found on github at https://github.com/Timothep/Talk.NancyFx

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"Microservices" is one of the hottest buzzwords and, as usual, everyone wants them, but few know how to build them. In this talk we will offer our interpretation of microservice architecture, and show how we are implementing these ideas: using Scala, Akka, sbt and Docker, we modularized Akka applications, Spark jobs and Play servers. In the talk we will discuss design trade-offs and challenges that we faced in the process, and how we have overcome them. The focus is not on particular features of Scala language or a library, but on building modern applications using the Typesafe stack and other open-source tools.

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We talk a lot about managing an agile team, agile transformations and about Scrum, Kanban, TDD, CI, small nimble companies about building positive motivation. It's all a set of beautiful buzzwords. A lot of people make living coaching and helping to make transformations. But as it comes to real work in the companies - reality rarely resembles beautiful stories from trainings. Why? An attempt to answer this question is model "Truly Agile Company", which is trying to catch the complexity of the transformation of the company. An attempt to capture the key roles and aspects often overlooked by the "Dogmatic Agile." Let's try to think about: • What is the "Pragmatic agile"? • How to work effectively with all key aspects of Agile transformation? • How not to get lost? • How to work with people and build on their potential for change?

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Microservices - opportunities, dilemmas and problems

This talk begins 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 Microservices 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.

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Workflows are a key component of server side of IoT solution along with Analytics, Rule Engine and IoT device management. IoT focused Workflow tools draw their inspiration of classical workflow tools that exist in market, but focus more on IoT use cases. For example they are able to connect with IoT devices using IoT specific protocols like CoAP or MQTT. Node-RED is a visual tool for wiring together hardware devices, APIs and online services in new and interesting ways. It’s build by IBM Emerging Technology team from group for IoT, though it’s not limited only to IoT.

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We all love open source software and open culture, and of course we all want to contribute to and leverage the power of open source in our work. However when it comes to working in a startup, openness is often sacrificed to give way to work efficiency and business logic. In this talk I will talk about some of my experience(and failures) to be open source, and how our company is trying to be open by default without too much efficiency overhead. https://hkoscon.org/2020/topics/open-default-trying-run-startup-open-source-culture-mind

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Software Architecture Conference 2018, London (UK): Talk by Mario-Leander Reimer (@LeanderReimer, Principal Software Architect at QAware) === Please download slides if blurred! === Abstract: In a microservice world, things become more complex. Platforms such as Kubernetes address a lot of the complexity; they handle resource isolation and utilization, networking, and deployments nicely. But a lot of the involved complexity such as load balancing, rollout scenarios, circuit breaking, retries, rate limiting, observability, tracing and transport security is still left up to the development teams. Of course, you can address all of these challenges in your microservices programmatically using popular open-source components such as Hystrix, Ribbon, Eureka, the EFK Stack, Prometheus or Jaeger. But, unfortunately, this approach can quickly lead to excessive library bloat and suddenly your microservices are not quite so micro anymore. All this might seem acceptable if you’re on a single, consistent development stack like Java EE or Spring Boot. But tackling these complexities becomes even more challenging if you’re dealing with multiple stacks and multiple frameworks, to say nothing about dealing with legacy applications that you can’t modify to retrofit these requirements. In comes Istio to the rescue. It is a so-called service mesh that addresses many of the cross-cutting communication concerns in a microservice architecture. Think of Istio as AOP (aspect-oriented programming) for microservice communication. Instead of implementing everything directly within your services, Istio transparently injects and decorates the desired concerns into the individual communication channels. Mario-Leander Reimer offers an overview of Istio and explains how it addresses the inherent complexities in microservice architectures. He briefly discusses the conceptual architecture and the main building blocks of Istio before diving into several examples deployed on a live Kubernetes cluster to demonstrate the different traffic management features, as well as diagnosability and security.

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JavaLand 2019, Brühl: Talk by Mario-Leander Reimer (@LeanderReimer, Principal Software Architect at QAware) === Please download slides if blurred! === Abstract: Building microservice architectures is complex. Modern platforms such as Kubernetes address a lot of the complexity, they handle resource isolation and utilization, networking and deployments nicely. But still, handling the remaining complexities, like circuit breaking, rate limiting, observability or transport security, is usually left up to the development teams to implement. Using open source components to address these challenges is an option, but this quickly leads to excessive library bloat and suddenly your microservices are not quite so micro anymore. Now, all this might seem acceptable if you are on a single, consistent development stack like Java EE or Spring Boot. But tackling these complexities becomes even more challenging if you are dealing with multiple stacks and multiple frameworks. Or you might even deal with legacy applications that you can't modify to retrofit these requirements. Istio to the rescue. It is a so called service mesh that addresses many of the cross-cutting communication concerns in a microservice architecture. Think of Istio as AOP (aspect oriented programming) for microservice communication. Instead of implementing everything directly within your services, Istio transparently injects and decorates the desired concerns into the individual communication channels. This session provides an overview of the Istio system and how it addresses the inherent complexities in microservice architectures. We will briefly discuss the conceptual architecture and the main building blocks of Istio. Then we will dive right into several showcases that are deployed on a Kubernetes cluster to demonstrate the different traffic management features, as well as diagnosability and security.

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Laura Chirca – NEURER BUSINESS SOLUTIONS We’ve seen several IoT based door access control hacks over the years at TADHack. INOVO is making this a commercial reality for its customers in Romania and beyond. It’s a great example of the migration from hack to business, and the power of the democratization in telecoms enabling people to create solutions for their customers that fit their specific local needs. The Cloud Control Access System opens doors with cards, codes, phones, and SMS. The prototype starts with physical door controllers (the first release is Arduino-based), then migrates to intermediate building proxies that hold the customers’ database in case the internet goes down (a reality most businesses face several times a year) and them migrating to a scalable cloud authentication and portal layer.

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In 2 hours, we discuss about apache shindig and how to integrate shindig in eXo Platform production. The presentation lay-out in a simple way to understand about shindig, why and how using shindig as a part of developing product. Since shindig is a best implementation of OpenSocial then know about it and find the way to apply it is needed. In eXo Platform now, shindig is being used as Gadget Container/Server and the based Container to enable eXo Social fully support OpenSocial standard. Short but clear about shindig, hope it helps.

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Presentation title: Model and pilot all cloud layers with OCCIware, from IoT to Big Data Abstract: Who uses multi cloud today ? Everybody. Alas, this leads to a lot of "technical glue". Enter OCCIware's Studio and Runtime : manage all layers and domains of the Cloud (XaaS) in a uniform, standard, extensible way - the Cloud consumer platform.presentation. This talk presents how the OCCIware Studio - currently being contributed to the Eclipse Foundation by Inria and Obeo - takes advantage of Eclipse Modeling and SIrius in order to support a metamodel for the generic Open Cloud Computing Interface (OCCI) REST API and build a "studio factory", while providing feedback and lessons learned on various other Eclipse components. It concludes on a live demonstration of using it to model and pilot an IoT (nodeMCU/ESP8266), Linked & Big Data (JSON-LD, Spark), containerized Cloud solution to let electricity consumption be monitored across territories by all actors - individuals, utility providers, up to regional public bodies.

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Who uses multi cloud today ? Everybody. Alas, this leads to a lot of "technical glue". Enter OCCIware's Studio and Runtime : manage all layers and domains of the Cloud (XaaS) in a uniform, standard, extensible way - the Cloud consumer platform. This talk presents how the OCCIware Studio - currently being contributed to the Eclipse Foundation by Inria and Obeo - takes advantage of Eclipse Modeling and SIrius in order to support a metamodel for the generic Open Cloud Computing Interface (OCCI) REST API and build a "studio factory", while providing feedback and lessons learned on various other Eclipse components. It concludes on a live demonstration of using it to model and pilot an IoT (nodeMCU/ESP8266), Linked & Big Data (JSON-LD, Spark), containerized Cloud solution to let electricity consumption be monitored across territories by all actors - individuals, utility providers, up to regional public bodies.

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Микросервисы получают все большую популярность в компаниях по всему миру. Какие организационные и технические проблемы они помогают решать? С какого момента монолиты перестают справляться с растущей нагрузкой на ваш сервис? Почему Zalando -- самый большой онлайн-ретейлер в Европе -- выбрал микросервисы в качестве главной архитектуры для новых проектов? Помогая в решении организационных проблем быстрорастущей компании, микросервисы ставят новые технические задачи, одной из которых, помимо увеличения сложности системы в целом, является проблема безопасного обмена сообщениями между микросервисами, удобной интеграции данных и возможности их корреляции и анализа. Слушатели узнают, как в Zalando решают эту проблему с использованием централизованной шины передачи данных -- Nakadi. Получат представление о тех проблемах, которые их могут поджидать при выборе похожей архитектуры на примере проблем выбора формата передачи данных, системы версионирования формата сообщений и сложностей эксплуатации высоконагруженных кластеров Kafka в облачной системе AWS.

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