Agile Development From A Developers Perspective

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The document discusses Agile development from a developer's perspective. It defines Agile as a set of processes for faster software development that values individuals, collaboration, and response to change over rigid processes. The Agile Manifesto and principles emphasize satisfying customers, effective communication, trust, and continuous improvement. Specific Agile practices like Scrum and its roles, ceremonies, and artifacts are covered. The document also discusses engineering practices like testing, version control, and continuous integration used in Agile development.

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Just over a year ago (before becoming the full time chair and advocate of QCon London, San Francisco, and New York), my main role was with HPE as the principal architect for a client in the US public sector. The systems we supported were responsible for personnel information, scholarships decisions, and record management. Like so many others, we were also faced with legacy applications, COTS product integrations, polyglot code bases, and often brittle deployments. In an effort to decouple code bases and address some of these issues, we started advocating for a Microservice architecture and trying to distinguish it from the SOA practices of the past. Now, it’s a year later. I have had the incredible opportunity to have access to architects, engineers, and leaders from some of the world’s more respected software companies. These are companies like Uber, Microsoft, Netflix, Apple, Google, Slack, Pinterest, and Etsy. I’ve had the chance to have one-on-one discussions with Chief Architects, developers, and engineers building the apps I most admire and use every day (some leveraging Microservices, some embracing Monoliths, and others falling somewhere in between). Patterns & Practices of Microservices is some of the things I wish I knew before beginning a push towards Microservices just over a year ago. It’s the practices of companies leveraging Microservices, it’s the technology tradeoffs when deciding between Monoliths and Microservices, and it’s the advice I’ve heard in interviewing, podcasting, and iterating on presentations from software giants like Adrian Cockcroft, Matt Ranney, Josh Evans, Martin Thompson, and literally hundreds of other engineers who drop knowledge at QCons around the world.

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My talk from http://microxchg.io/2016/index.html. Here is the video - https://www.youtube.com/watch?v=1mcVQhbkA2U When architecting an enterprise Java application, you need to choose between the traditional monolithic architecture consisting of a single large WAR file, or the more fashionable microservices architecture consisting of many smaller services. But rather than blindly picking the familiar or the fashionable, it’s important to remember what Fred Books said almost 30 years ago: there are no silver bullets in software. Every architectural decision has both benefits and drawbacks. Whether the benefits of one approach outweigh the drawbacks greatly depends upon the context of your particular project. Moreover, even if you adopt the microservices architecture, you must still make numerous other design decisions, each with their own trade-offs. A software pattern is an ideal way of describing a solution to a problem in a given context along with its tradeoffs. In this presentation, we describe a pattern language for microservices. You will learn about patterns that will help you decide when and how to use microservices vs. a monolithic architecture. We will also describe patterns that solve various problems in a microservice architecture including inter-service communication, service registration and service discovery.

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Microservices architecture is a very powerful way to build scalable systems optimized for speed of change. To do this, we need to build independent, autonomous services which by definition tend to minimize dependencies on other systems. One of the tenants of microservices, and a way to minimize dependencies, is “a service should own its own database”. Unfortunately this is a lot easier said than done. Why? Because: your data. We’ve been dealing with data in information systems for 5 decades so isn’t this a solved problem? Yes and no. A lot of the lessons learned are still very relevant. Traditionally, we application developers have accepted the practice of using relational databases and relying on all of their safety guarantees without question. But as we build services architectures that span more than one database (by design, as with microservices), things get harder. If data about a customer changes in one database, how do we reconcile that with other databases (especially where the data storage may be heterogenous?). For developers focused on the traditional enterprise, not only do we have to try to build fast-changing systems that are surrounded by legacy systems, the domains (finance, insurance, retail, etc) are incredibly complicated. Just copying with Netflix does for microservices may or may not be useful. So how do we develop and reason about the boundaries in our system to reduce complexity in the domain? In this talk, we’ll explore these problems and see how Domain Driven Design helps grapple with the domain complexity. We’ll see how DDD concepts like Entities and Aggregates help reason about boundaries based on use cases and how transactions are affected. Once we can identify our transactional boundaries we can more carefully adjust our needs from the CAP theorem to scale out and achieve truly autonomous systems with strictly ordered eventual consistency. We’ll see how technologies like Apache Kafka, Apache Camel and Debezium.io can help build the backbone for these types of systems. We’ll even explore the details of a working example that brings all of this together.

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