Machine learning with Kafka - The modern Stream Processing platform for all data preprocessing needs Some bits about Kafka Kafka is a popular messaging platform based on pub-sub mechanism. It is a highly available, fault tolerant & distributed system. Most organisations are using Kafka in different use-cases, but the best
Kafka Security / SSL Protocols Security in modern enterprises is the utmost cause of concern, it's extremely essential to mitigate any risks of attacks, unauthorised access and data corruption. It is addressed with caution considering compliance and performance implications. Apache Kafka comes with inbuilt configurable security protocols, (Kafka SSL Protocols)
Is Kafka secure? What is Kafka security? Security in modern enterprises is the utmost cause of concern, it's essential to mitigate any risks of attacks, unauthorised access and data corruptions. It is addressed with extreme caution considering compliance and performance implications. Considering this, Apache kafka users automatically thinks, what do
What is Apache Kafka? Apache Kafka is a fast, scalable, durable, and fault-tolerant publish-subscribe messaging system used to manage big volumes of data. Due to high efficiency, reliability and replication characteristics, Kafka is applicable for systems like tracking service calls (tracks every call), instant messaging or tracking IoT sensor data
Kafka Connect is a technology for linking Kafka with other services. One of the main challenges of an IT architecture is the batch process and a bunch of codes that transport or align data from one to another application. A small failure can cause ultimate data and business losses with
Apache Kafka is the key product for not only messaging transformations but also real-time data processing, in addition to many other use cases. Architectures hosted inside the cloud claim to be secure in terms of communication and providing general security. But when it comes to the multiple client/consumer communication from
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
“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
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,
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
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
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
