Scaling up your Kafka event streaming processing: what can go wrong?

Enterprise organizations know that Apache Kafka is the data-centric gold standard they need to run mission-critical applications. Logically, it’s very tempting to scale up Kafka usage quickly — but it’s vital to tread carefully.

Here, we’ll look at key issues organizations frequently experience when scaling up their Kafka operations, as well as how to set your organization up to leverage Kafka’s full potential.

If you’re nearer the beginning of your Kafka event streaming journey, you might like to check out our blog on avoiding easily made mistakes when getting started with Kafka data governance.

Common pitfalls to avoid when scaling up with Kafka

Let’s imagine the scenario: Your organization introduced small-scale event streaming processing with Kafka — and it went down brilliantly.

With such clear opportunities to leverage real-time data, accelerate time to market for applications, and evolve the service your organization offers its customers, teams from all over the company are just about knocking down your Kafka architects’ door with enthusiastic expansion ideas.

What could go wrong? Unfortunately, the answer is a lot, very quickly.

You can easily lose track of scale, ownership, and access

As you scale up, increasing numbers of teams will start working with the data you manage with Kafka. Without clear processes in place to track who’s creating all these new Kafka topics and accessing your ever-growing range of applications — and also why, where, and when they’re doing it — your Kafka architects will rapidly lose their grasp of who has created which topics and who has access to what.

Your Kafka owners will also lose their overview of the what, why, how, and when of who’s making mistakes in Kafka within your organization. So when something does go wrong, it’s incredibly difficult to trace it, fix it, and prevent it from happening again.

Your central Kafka team can become a bottleneck

Your internal platform team can only handle so many requests, questions, and tasks at once. Often, the workload acceleration that goes hand in hand with an organization scaling its Kafka instance overwhelms these teams, meaning they inadvertently become a high-pressure bottleneck that prevents your Kafka from scaling smoothly.

How to scale up your Kafka data streaming effectively

The potential for enterprise organizations to evolve their service with a successful Kafka scale-up is vast. Yes, it’s a significant challenge — but the key is setting your organization up with the right tools to succeed.

With Axual’s user-centric, easy to interpret interface, you can tick these key security, data governance, and compliance boxes for your Kafka landscape:

• Secure access by ensuring traffic to and from your Kafka platform is encrypted
• Make sure all applications connected to your Kafka ecosystem are authenticated
• Use the latest TLS versions for authorization
• Grant permissions and topic access on a strictly need-only basis
• Configure your cluster settings to reduce the impact of potential server outages
• Offer Kafka self-service for developers, reducing pressure on your central Kafka team

Kafka data governance peace of mind? Axual is here to help.

We exist to take the stress out of Kafka streaming, compliance and data governance — so that’s no more sleepless nights for your Kafka team!
For an in-depth take on securing your organization’s event streaming processing, why not read our whitepaper on mastering Kafka data governance and compliance? Or for a bite-size look at why it’s so easy to make data governance mistakes when working with Kafka, dive into our blog on the topic.