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Hybrid Cloud: The gateway to growth for businesses

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Hybrid cloud market has been growing significantly over the last five years because of flexible offering across private and public clouds. With businesses (from small to large scale, across all industries) moving more towards cloud deployments, security, protection of intellectual property, compliance and reliance on legacy infrastructure have become impedance

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The rise of event stream processing

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“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

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Kibana: Data visualization made easier

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Kibana makes data analytics easy. It is one of the elites in providing visualization solutions for enterprises for data sets including runtime data, server logs, market statistics, geo-spatial data mappings, density graphs. It works with Elasticsearch and supports machine learning. The tool can unravel secrets such as trends/patterns from the

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Failure detection and alert from real-time data flow using Kafka and KSQL

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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,

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3 reasons your company needs real-time anomaly detection

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In the business world, time is money. When an anomaly, or unexpected data pattern, occurs, each second can amount to additional loss or missed opportunities. This is especially true for a fast-moving, data-driven business. When manual thresholds and dashboards prove no match at managing millions of metrics, companies need to

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Real-Time Data Streaming, Kafka and Analytics, Part 2: Going Beyond Pure Streaming

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Data transaction streaming is managed through many platforms, with one of the most common being Apache Kafka. In our first article in this data streaming series, we delved into the definition of data transaction and streaming and why it is critical to manage information in real-time for the most accurate

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Real-Time Data Streaming, Kafka, and Analytics Part 1: Data Streaming 101

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The terms “real-time data” and “streaming data” are the latest catch phrases being bandied about by almost every data vendor and company. Everyone wants the world to know that they have access to and are using the latest, greatest data for making business decisions. But using the term is not

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Event streaming using Apache Kafka

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There are levels of event recording in accordance with the use cases for which we are tracking like application logging (Log4j levels). Now a mission-critical application (like transactions) will generate a huge number of events, this will enable to debug/analyse in case of any failure or audits. For low to

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Why event stream processing is leading the new ‘big data’ era

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Big data is probably one of the most misused words of the last decade. It was widely promoted, discussed and spread by business managers, technical experts, and experienced academics. Slogans like ‘data is the new oil’ were widely accepted as unquestionable truth.  But with this hype, different ideas and solutions

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5 Things to Know About Event-Driven APIs and Apache Kafka

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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