Managing Apache Kafka infrastructure is no small feat. For organizations that rely on streaming data for mission-critical processes, Kafka costs could easily be in the hundreds of thousands or even millions of dollars per year. And when it comes to cost allocation, the challenge is more than just technical—it’s organizational. 

The View From the Platform Engineering Trenches

Having wrestled with Kafka’s financial and operational headaches firsthand, I’ve seen how the lack of means to provide ownership and accountability can push a thriving tech solution to the brink of extinction.

In past roles leading Platform and Architecture teams, I was responsible for Kafka, which means I was expected to justify the costs and identify the culprits behind runaway expenses. Sounds simple, right? It wasn’t. I remember facing a Kafka crisis that almost derailed the platform when our provider bill spiraled out of control, tripling in a short period. Suddenly, I was in the hot seat, defending why we should even be using Kafka at all given its expense.

Kafka is a shared resource, and while monitoring tools can surface technical usage data, the reality is far messier. It took me six stressful weeks to untangle the ownership of just 50% of the topics in our clusters. Six weeks of manually piecing together who was using what, without a clear tool to track ownership.

But even after figuring out who was responsible, I was stuck. I couldn’t just delete a bunch of topics because things could stop working. Meanwhile, for the teams using Kafka this wasn’t a priority; for them it was like free petrol—no cost, no accountability, no urgency to clean up. They were just driving their cars around with their own priorities to deliver against.

The Partition Problem

The worst part was the partitions. These were well into 5 figures, but only about a third were actually needed. The rest were idle, eating into our budget, and I couldn’t get teams to prioritize cleanup because it wasn’t their problem. It became mine. I ended up pestering people, pulling them away from their real work, just to fix something that shouldn’t have been broken in the first place.

Kafka infrastructure costs are impossible to justify without context and organizations can’t easily attribute resource consumption to teams, projects, or departments. This means teams are completely disconnected from the financial consequences of their actions, leading to inefficient resource utilization, wild cloud spending, and budgeting chaos. 

A proper tool could’ve saved me months of work, cut costs dramatically, and kept Kafka from becoming a distraction from the core business work. And I know I’m not alone in this. Recently, one of our customers shared that they exceeded their Kafka budget by $600K—and had no idea why. With better solutions, such situations could shift from chaos and frustration to stories of efficiency and growth .

Why a Chargeback Tool is Essential

Chargeback is a cost allocation method where expenses for shared resources are distributed to the teams or projects using them, fostering accountability and encouraging resource optimization.

In the case of Kafka, chargeback allows organizations to track and allocate costs/usage associated with Kafka resources to different teams or departments based on their data consumption and processing, facilitating cost accountability, management and optimization.

This is why I’m so excited about releasing Conduktor’s Chargeback capabilities to bring clarity and accountability to Kafka costs for our customers. Conduktor’s proxy acts as a bridge between applications and Kafka (whether it is on AWS MSK, Confluent, Redpanda, Aiven…), which means it observes all the traffic going through Kafka and can collect ingress/egress data and enrich it with business context (think purpose, ownership, team, domain, cost-center), turning technical data into business intelligence.

When split by business unit, by region, or by application, Conduktor Chargeback helps organizations understand and forecast their Kafka costs, scale their infrastructure efficiently, and integrate Kafka costs into the bigger picture around shared infrastructure costs. In summary, make better informed decisions.

By combining this Chargeback capability with Conduktor’s self-service controls—which empower application teams to manage their own Kafka operations—organizations will gain even greater business context and granularity into resource usage by each team or application.

The Benefits of Chargeback in Kafka

Chargeback in Kafka is just one piece of the broader challenge of allocating shared infrastructure costs across an organization, but it’s a critical piece because Kafka expenses are often hidden in plain sight. Unlike more visible resources like compute or storage, Kafka’s costs—driven by factors like partitions, topics, and data retention—can quietly grow unchecked, making them hard to track and justify. 

Implementing a chargeback model not only shines a light on these hidden costs but also drives accountability and optimization, ensuring Kafka remains a sustainable part of the infrastructure while aligning its use with business priorities.

With such a tool, the six weeks I spent unraveling ownership issues could have been condensed into days. The year-long process of reining in costs could have been tackled in less than a month.

With a proper chargeback solution, you can:

1. Drive Accountability: Assign costs directly to teams to motivate responsible usage and reduce unnecessary resource consumption.

2. Optimize Resources: Identify and eliminate inefficiencies like unused partitions or topics to cut costs and improve operational efficiency. 

3. Improve Forecasting: Use detailed cost insights to accurately predict future Kafka expenses and plan budgets more effectively.

From Pain to Progress

Reflecting on my Kafka experience, the cost allocation challenge wasn’t just about managing infrastructure; it was about navigating the complexities of people, processes, and technology. 

For any organization relying on Kafka, addressing cost allocation isn’t just good practice; it’s essential for sustainability. It transforms Kafka from a chaotic cost center into a transparent, accountable system that supports growth rather than hindering it. And with the right tools, this once-daunting challenge becomes an opportunity to streamline operations, cut costs and drive efficiency.

If you are interested in seeing how this can help your organization, book some time for a quick demo!