Getting started with Kafka event streaming: what common data governance mistakes are made?

For enterprise organizations streaming real-time data, Apache Kafka is the gold standard for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. But it’s a complex beast to use. Even for highly experienced architects, it’s all too easy to go wrong — especially when it comes to all-important data governance.

Below, we’ll explore the common data governance mistakes organizations using Kafka can make, key steps to take if you’re already experiencing compliance issues with Kafka, and how to avert these types of issues before they adversely affect your mission-critical applications.

Kafka data governance: common errors to avoid

As digital transformation picks up the pace, enterprise organizations are increasingly reliant on real-time data to deliver optimal service and performance for their customers. In parallel, ensuring customer data is handled in a secure, compliant manner is a top priority for Kafka developers and operators.

Despite this awareness, though, we see frequent, easily made mistakes in organizations working with Kafka. Let’s outline a couple of them:

New topics just appear — with no record of who created them, or why

When a producer produces to a topic that didn’t previously exist in your Kafka ecosystem, the topic is created by default. So the new topic is up and running, but without any checks on completeness or correctness. There’s also no administration record of who created it, who’s able or permitted to access it, or its intended use case.

This untraceability can rapidly get out of control, causing multiple issues:

• Topics created accidentally need to be cleaned up, wasting time and resources
• Use cases are unclear, hindering your organization’s workflows
• Data breaches can be caused by creating accidental or experimental topics without applying your organization’s standard data governance rules

Gaps in security put your customer data at risk

For enterprise organizations, embedded security is a must-have for protecting sensitive customer data. To address this need, it’s possible to implement various security layers in Kafka. Authorizations can be carried out topic by topic, via mutual SSL or SASL between Kafka brokers and Kafka clients. Brokers can also run authenticated clients against Access Control Lists (ACLs) to confirm or deny access to specific topics.

However, your developers and operators need in-depth knowledge and serious resources to implement these Kafka security layers and ensure there are zero gaps.

Take Kafka ACLs as one example: These are based on predefined rules for user access, which need to be configured and maintained across all your organization’s Kafka applications. With increasing numbers of applications, growing numbers of users, and expanding use cases and access needs, that’s a lot of weight on your Kafka team’s shoulders — and it creates a prime situation for human error and oversight.

Already experiencing compliance issues with Kafka? Here’s what to do.

1. Stop use cases from going to production

Keep applications and use cases in pre-production until they’re verified as fully secure and tested, then apply the changes to your production environment.

Here, it’s vital you don’t bow to pressure from internal teams who want to see their applications rapidly rolled out with Kafka. Rather than making those swift turnarounds happen at any cost, take the time needed to set up watertight security and compliance protocols — because whether you’re in finance, energy, utilities or retail, a data breach puts your organization’s reputation on the line.

2. Review your event streaming configurations

Ensure you understand the Kafka configurations you have in place, how to set the right configurations to prevent data loss, and how to secure your Kafka setup overall.

3. Train users with Kafka data governance best practices

Effective stakeholder communication and knowledge acquisition is key. To make sure all your users interact with your Kafka platform correctly, put procedures and guidelines in place for anyone who connects to it within your organization. This is instrumental in supporting users to avoid accidentally making the common errors we explored above.

4. Stay calm — lean on an expert partner

The ultimate goal for large-scale organizations leveraging Kafka is knowing and trusting that everyone who needs to (and no-one else) can work with real-time, even highly sensitive, customer data in a secure, compliant manner. For Kafka developers and operators, that’s the ticket to a disaster-proof life at work.

As an all-in-one Apache Kafka platform for enterprises that specializes in self-service for data streaming, Axual offers a comprehensive, intuitive interface to quickly and easily add the Kafka security layers your organization requires.

Avoid easily made Kafka data governance mistakes with Axual

Comprehensively test your streaming applications in isolation before moving them to production, enable granular governance via environment-specific rules, ensure Kafka application security with compulsory SSL certificates, and more with Axual.
For further insights into safeguarding your organization’s event streaming processing, read our whitepaper on mastering data governance and compliance with Apache Kafka.

If you would like to discuss event streaming use cases and best practices, feel free to reach out to us. Our industry experts are here to help!

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