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Pandio’s Top 10 Rules for Managing Apache Pulsar Apache Pulsar is the next generation of messaging systems and streaming platforms built to handle the demands of AI and ML. Because of its architectural design, it has a lot to offer compared with older technologies like Apache Kafka. Apache Pulsar is a rich and complex system […]

Data in Motion: Reality vs Fantasy We are here to distinguish fact from fiction in recent marketing hype about querying live data streams, popularly called “Data in Motion.” Examples include live event streaming from many types of network connected devices such as IoT sensors, webcams, financial monitoring instruments and many more. Providing intelligence from these […]

Confluent Announced Their S1 and “Data In Motion” Mission The world of business runs strictly on numbers and values, and as companies slowly shift to the digital world, they require intricate solutions to accommodate their new requirements. As a result, data processing is practically a necessity in the modern age, and the naturalization of the […]

Why a Managed Service Might Make Sense for your Distributed Messaging Instant and distributed messaging is taking the world by storm. Like with social media apps, more and more companies are using distributed messaging solutions to streamline their communications. Messaging apps like Viber, WeChat, Facebook Messenger, and WhatsApp have already gathered more than 6 billion […]

Kubernetes – What It Is and Why It’s Critical for a Performant Distributed Messaging System Kubernetes and distributed messaging systems go hand in hand. It’s hardly imaginable to see a distributed messaging platform able to meet the performance requirements nowadays without the use of Kubernetes. Building cloud-native environments without properly distributing and allocating storage and […]

Why Machine Learning Initiatives Fail in Media Machine learning (ML) is a technological breakthrough that is changing the way we live.  Machine learning has many practical implications including the ability to help us to predict future outcomes, optimize and automate processes, make decisions, and generate content.  In most cases, machine learning algorithms can be optimized […]