Day: March 10, 2024

The adage “Rome wasn’t built in a day” applies perfectly to DevOps. Many companies yearn for the instant gratification of “blitzing” their way to market dominance, but true success in DevOps is a marathon, not a sprint. It requires a commitment to building a sustainable DevOps culture - one that fosters collaboration, automation, and security from the ground up.

This blog post delves into the core components of a successful DevOps journey, using the insights from a leading DevOps services provider. We’ll explore how to move beyond the initial hype and build a long-lasting DevOps foundation that drives innovation and agility.

Over the past few years, Apache Kafka has emerged as the leading standard for streaming data. Fast-forward to the present day: Kafka has achieved ubiquity, being adopted by at least 80% of the Fortune 100. This widespread adoption is attributed to Kafka's architecture, which goes far beyond basic messaging. Kafka's architecture versatility makes it exceptionally suitable for streaming data at a vast "internet" scale, ensuring fault tolerance and data consistency crucial for supporting mission-critical applications. 

Flink is a high-throughput, unified batch and stream processing engine, renowned for its capability to handle continuous data streams at scale. It seamlessly integrates with Kafka and offers robust support for exactly-once semantics, ensuring each event is processed precisely once, even amidst system failures. Flink emerges as a natural choice as a stream processor for Kafka. While Apache Flink enjoys significant success and popularity as a tool for real-time data processing, accessing sufficient resources and current examples for learning Flink can be challenging.