Confluent Blog

Hi there, it’s me, Danica Fine, your friendly neighborhood Kafka Summit London Program Committee Chair. Kafka Summit London 2023 is in just over two weeks, and I’ll be joining our incredible community members at the ExCeL in London to talk all things Apache Kafka® over two jam-packed days.

It's hard to properly calculate the cost of running Kafka. In part 1 of 4, learn to calculate your Kafka costs based on your infrastructure, networking, and cloud usage.

When Steven Zhang graduated from college in 2019, he, was searching for intellectually-stimulating work. That search led him to Confluent. Four years in, Steven currently works as a senior software engineer in the Stream Processing and Analytics organization

Shaun Clowes, Confluent’s Chief Product Officer since December of last year, will tell you data is the lifeblood of modern organizations. But he will also tell you he isn’t a big fan of the word “data.”

Capturing tech trends has become a bit tricky these days: whatever industry you’re in, uncertainty abounds. Planning has become harder, but businesses are finding new ways to innovate and respond quickly to fast-changing market conditions.

If you’ve been working with Kafka Streams and have seen an “unknown magic byte” error, you might be wondering what a magic byte is in the first place, and also, how to resolve the error. This post explains the answers to both questions.

The National Cybersecurity Strategy released by the Biden-Harris administration in March 2023 was designed to provide direction for developing and evolving the digital ecosystem that will become a key line of defense for the security of our nation

Spring has arrived in the northern hemisphere, and as we delight in the sight of flowers blossoming, trees budding, and greenery sprouting, we're reminded of the promise of brighter and warmer days ahead.

The ML and data streaming markets have socio-technical blockers between them, but they are finally coming together. Apache Kafka and stream processing solutions are a perfect match for data-hungry models.

Over the last decade, financial services companies have doubled down on using real-time capabilities to differentiate themselves from the competition and become more efficient. This trend has had a huge impact on customer experience in banking especially, and home mortgage company Mr. Cooper

Breaking encapsulation has led to a decade of problems for data teams. But is the solution just to tell data teams to use APIs instead of extracting data from databases? The answer is no. Breaking encapsulation was never the goal, only a symptom of data and software teams not working together.

Confluent has successfully achieved Google Cloud Ready - AlloyDB designation for AlloyDB for PostgreSQL, Google Cloud’s newest fully managed PostgreSQL-compatible database service for the most demanding enterprise database workloads.

Apache Kafka and stream processing solutions are a perfect match for data-hungry models. Our community’s solutions can form a critical part of a machine learning platform, enabling machine learning engineers to deliver real-time MLOps strategies.