Big Ideas

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.

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.

The big data revolution of the early 2000s saw rapid growth in data creation, storage, and processing. A new set of architectures, tools, and technologies emerged to meet the demand. But what of big data today? You seldom hear of it anymore. Where has it gone?

Experienced technology leaders know that adopting a new technology can be risky. Often, we are unable to distinguish between those investments that will be transformational and those that won’t be worthwhile. This post examines how one can decide if event streaming makes sense for them.

Learn how modern data management approaches like data mesh and event-driven architecture (EDA) can be used to manage data platforms and how to take advantage of them.

Perhaps the largest challenge for modern data teams is gaining and retaining trust. The challenge of Big Data has come and gone, now we face the challenge of Untrustworthy Data, which will be one of the core focal points of the data space in 2023 and beyond.

The worlds of data integration and data pipelines are changing in ways that are highly reminiscent of the profound changes I witnessed in application and service development over the last twenty years.

Decentralized architectures continue to flourish as engineering teams look to unlock the potential of their people and systems. From Git, to microservices, to cryptocurrencies, these designs look to decentralization as […]

A few years ago I helped build an event-driven system for gym bookings. The pitch was that we were building a better experience for both the gym members booking different […]

Data mesh. This oft-talked-about architecture has no shortage of blog posts, conference talks, podcasts, and discussions. One thing that you may have found lacking is a concrete guide on precisely […]

I’ve always found event sourcing to be fascinating. We spend so much of our lives as developers saving data in database tables—doing this in a completely different way seems almost […]

Data is the lifeblood of so much of what we build as software professionals, so it’s unsurprising that operations involving its transfer occupy the vast majority of developer time across […]

On a recent episode of Streaming Audio, Gwen Shapira, Michael Noll, and Ben Stopford joined me to hold forth about the near future of Apache Kafka® and software architecture in […]

First, what is event sourcing? Here’s an example. Consider your bank account: viewing it online, the first thing you notice is often the current balance. How many of us drill […]