Apache Kafka® security: The 5 non-negotiables for secure data streaming

Securing real-time data streaming

Imagine you’re flying 30,000 feet in the air, trying to doze off, but you’re also tempted to catch up on that show you’ve been meaning to finish for the last several years. In the meantime, you’re being jolted awake by turbulence along the way—maybe causing a bit of panic here and there. But, hey, you still have several hours left until landing, so you manage to doze off after all. And all the while, that airplane–and every other airplane currently in the sky–is streaming real-time data back to different stakeholders:

• The turbine company monitoring for any abnormalities
• The airline keeping track of its geographical location
• Weather monitoring for turbulence from other planes on the same route

This data streaming keeps your flight safe, smooth, and on time. Now, imagine how critical security becomes when sensitive data is involved. Enterprises relying on data streaming must prioritize robust security measures to protect their operations.

Real-time fraud detection, hyper-personalized shopping experiences, data from IoT devices, AI insights…the list of use cases for data streaming is extensive and growing.

And along with a growing need for data streaming is the need to make sure that data is secure.

But with so many changes going on (here’s looking at you AI) how can enterprises secure their data streaming? For organizations leveraging Apache Kafka® to power their data infrastructure, here are five essential best practices to ensure Kafka security and long-term scalability.

1. Stay on top of regular updates and patching notices

This one’s a no-brainer—or rather, it should be a no brainer, but unfortunately, it’s not. The sheer number of enterprises that don’t stay on top of regular updates and patching for their software is uncomfortably larger than it should be.

In 2024 alone, there were a record-breaking 40,009 CVEs announced, and so far in 2025, we’re well on our way to surpassing that number by a good margin—some are already estimating that we’ll have upwards of 50,000 CVEs this year. With so many vulnerabilities out there (and growing), maintaining regular patching and staying on top of software updates is imperative. Thankfully, the solution is straightforward.

Don’t kick the can down the road. When a CVE is announced, action it. When a software update is rolled out, prioritize updating it. This will help save you from far more severe problems later.

2. Create strong authentication and access controls

How many people have access to your database? How easy it is to access it? Does everyone really need to have that access to it? Ask yourself these questions and you could very well be surprised by the answer.

Use role-based access control (RBAC) or attribute-based access control (ABAC) to limit access to data streams based on user roles or attributes.

Control access to resources by setting up fine-grained access control lists (ACLs). This ensures that only authorized users or applications can read from or write to specific topics/channels.

By creating strong authentication and access controls, you’re helping to prevent unauthorized access, protect sensitive data, and ultimately mitigating security risks.

3. Keep it private: Use VPC peering and private networks

What’s the best way to enhance the confidentiality, integrity, and availability as you scale your data streams? Utilize privacy measures like VPC peering and private networks.

Why? Using VPC peering and private network connections ensures that your data streams are transmitted securely within a controlled environment, reducing exposure to external threats and improving performance.

This is beneficial for a few reasons:

• It reduces the risk of attacks like man-in-the-middle (MITM), DDoS, or unauthorized access that can occur when data is exposed to the public internet.
• By keeping data within a private network, you eliminate the need for public IP addresses, which are more vulnerable to exploitation.
• Publicly accessible endpoints increase the attack surface for your data streaming infrastructure. With private connections, only internal resources (e.g., producers, consumers, and brokers) can communicate, significantly reducing the risk of external threats.

By taking active privacy measures like VPC peering and private networks, you’re helping to build a robust and secure data streaming architecture.

4. Stay compliant with data privacy rules and regulations

Admittedly, this one is easier said than done—but that doesn’t mean it’s not worth investing in.

It’s no surprise that many industries that rely heavily on streaming data (like finance and healthcare) have strict compliance requirements: GDPR, HIPAA, PCI-DSS, etc. and these requirements aren’t going away anytime soon—if anything, they’ll become more stringent.

While using VPC and private network connections can help meet these regulatory requirements, you can—and should—take it further. If you’re at the early stages of architecture design, then you can start by implementing privacy principles from the get-go. Incorporate privacy controls and data anonymization techniques to minimize the exposure of sensitive data.

Beyond the early-stage position? Not to worry, there’s still a lot you can do:

• Implement monitoring mechanisms to detect and report any potential data breaches or non-compliance incidents.
• Consistently audit logs, access attempts, and permissions.
• Define data retention policies to ensure sensitive data is securely deleted or anonymized.
• Train employees on data privacy rules, best practices, and regulations to build a culture of security and awareness across your organization.

5. Stick with open source

And finally, what’s the best way to secure data streaming and help you scale for whatever your enterprise may face?

Use open source software.

Sure, that may seem counterintuitive at first; after all, the actual source code for open source (as the name suggests) is literally out in the open for all to see. But open source provides security benefits that its proprietary counterparts simply cannot match.

Apache Kafka® has proved itself to become a leading streaming data technology, and for good reason. Its distributed architecture is designed to scale seamlessly, making it capable of handling massive volumes of real-time data without performance degradation.

Plus, Kafka’s flexibility enables it to easily integrate with AI-driven systems—a key driver of increased workloads both now and in the future. Being open source, you get numerous security benefits that propriety code simply cannot match: a strong community bringing transparency and quick updates to any security vulnerabilities that can (and will) arise.

Final thoughts on Kafka security

AI is changing everything, and enterprises are already living it.

According to the 2024 Data complexity report from NetApp, 69% of enterprises are already noting an increase in security threats because of AI. Most C-level executives list global security challenges as their main stressor, which will only increase in 2025 and beyond.

But the demand for streaming data is not slowing down anytime soon. Financial institutions still need to stay ahead of the curve with fraud detection. Healthcare providers want to deliver the best possible outcome. Retailers are coming up with new ways to make the shopping experience as personalized as possible.

And airplanes—with all the real-time data monitoring keeping them in the sky—still need to fly; odds are, that data is streaming with Apache Kafka, too.

Want to know exactly how to implement these best practices?