Microservices in Java

The benefits of using microservices to replace monolith architectures and how microservices communicate with each other in Java are becoming more evident in the development world but in this article, we will shed light over some of the other aspects of the microservices Java architecture, too. What Are Microservices Very simply, as it is implied in its name, microservices are smaller or larger services able to function on their own
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Why to learn Scala in 2020

Every young technology enthusiast or someone who is looking for a new development path is asking a question to himself - what is the next trending programming language to be learned? After many years of Java being a market leader in back-end development, in the last couple of years seems that Scala is overtaking leadership. But is that still so? Is it worth learning Scala in 2020 and what is
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Case Study: How Groupon scales personalised offers to 48 Million customers on time

Use Case Retain market leadership with personalised, time-sensitive offerings to a user base that includes more than 48 million active customers. Challenge With evidence showing that delays in outreach impact conversions, Groupon must ensure campaign delivery of millions of daily emails and push notifications to users in 500+ markets across 15 countries. Maintain a resilient and responsive user experience, especially when scaling out to handle large peaks in demand–2-3 hours
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Case Study: Flipkart reduces infrastructure by 75% and “Connekts” with 70 million shoppers using reactive microservices

Introduction Flipkart first opened for business selling books in 2007, and has grown rapidly since then to now employing over 33,000 people serving a marketplace of over 100 million consumers. Now with a market valuation of over $11 billion and over $2 billion in revenues, Flipkart has become a significant market power in India’s massive e-commerce industry–offering everything from books and electronics to furniture and washing machines. One of the untold
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Real-time processing and aggregation of Call Detail Records (CDRs) using Kafka and Flink

With the exponential growth in data, the biggest problem plaguing the telecom industry is how to process and aggregate huge volumes of call detail records (CDRs). Telcos are taking  fresh approaches to get the real-time value of streaming data. They are shifting from heavy batch processing systems to faster, scalable and resilient IT architectures. However, integrating devices and machines to enable real-time data processing is complex and time-consuming. Kafka ecosystem,
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Stateful Cloud Native Applications – Why Reactive Matters

What is a Cloud Native Application? A Cloud Native application is an application designed to leverage the cloud operating model. They are predictable, decoupled from the infrastructure, right-sized for capacity, enable a tight collaboration between development and operations, decomposed into loosely coupled independently operating microservices, resilient from failures, driven by data, and intelligently operate across geographic nodes. It’s not uncommon to see an application demand increasingly tougher requirements: High transactions per second
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The rise of event stream processing

“The perfect kind of architecture decision is the one which never has to be made”  Robert C. Martin From being a phenomenal trend to becoming one of the most essential IT designs considerations, event streaming has evolved to be pivotal for businesses due to an exponential increase in data and growing requirements for them to be real-time. A customer no longer waits for three hours before receiving a confirmation of
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Failure detection and alert from real-time data flow using Kafka and KSQL

Apache Kafka ecosystem is relevant to detect anomalies (failure detection) in the huge volume of data sets. These data sets can come from various industries including IoT, banking or insurance. In this article, we present a use case on how to use the cloud-native ecosystem with Kafka, MQTT, Kafka Connect, Stream, KSQL to build scalable and resilient solutions for real-time IoT anomalies detection. Processing huge volumes of data for anomaly
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5 Things to Know About Event-Driven APIs and Apache Kafka

APIs are becoming the crux of any digital business today. They provide a multitude of internal and external uses, including making B2B connections and linking building blocks for low-code application development and event-driven thinking. Digital business can’t exist without event-driven thinking. There are real benefits to developing event-driven apps and architecture—to provide a more responsive and scalable customer experience. Your digital business requires new thinking. New tools are required to adopt event-driven