When it comes to tracking Apache Kafka costs and chargeback, most teams begin with the same metrics: disk size and partition counts. For both open source and managed Kafka distributions, these two indicators are an accessible, basic source of usage data, providing an overview of how much data is stored in a given topic and how many partitions exist per topic. 

Because these two criteria often play key roles in Kafka cost structures, they are the default starting point for cost tracking and optimization. However, teams that only track disk size and partition counts will lack granular information on:

• Who produced or consumed the data within topics

• Which topics map to which projects and teams

• Which teams account for the highest or lowest costs

Service accounts: Accurate, but lacking depth

For most organizations, the next step is to base chargeback on service accounts, adding further depth to Kafka usage data. As credentials used by applications and services (rather than human users), service accounts are a valuable measure of how much data was moved, who connected to what, and metrics such as bytes in/out and messages produced/consumed. 

Still, service accounts provide only surface-level insights and weren’t necessarily designed to support detailed analysis, as they do not have a way to correlate usage to specific teams, projects, or environments. Without the necessary context, organizations can’t investigate anomalies in Kafka usage, traffic, and costs—nor can they determine which projects are the most expensive, which Kafka infrastructure is unused and unnecessary, and which teams own which specific topics or clusters. 

Because of their technical nature and lack of metadata (such as environment or project tags), service accounts can be difficult to parse for non-technical users in finance or business teams. To anyone unfamiliar with the nuances of their organization’s Kafka infrastructure, building a budget or tracking costs using only service accounts can be difficult. 

The dilemma is a frustrating one: the data is there, but absent important context, it’s not useful for analytics, strategy, and decision making.

Chargeback is now generally available

Today, Conduktor Chargeback is now generally available as part of our Scale+ package, and features full support for user-defined labels. Now, you can provide granular visibility into your business’ Kafka costs, tracking and attributing usage by any combination of team, product line, project, or environment.

After you add metadata labels to service accounts, Chargeback will automatically group your Kafka usage into the specified categories. In this way, teams throughout your organization can align technical data with real business units, allocate costs by product line, differentiate between staging and production environments, and even track project-specific consumption. 

By mapping expenses and activity to the structure of your organization—rather than the architecture of your Kafka environment—this data becomes more relevant, understandable, and intuitive. This not only enables more accurate budgeting and forecasting, but also helps teams take ownership of their Kafka footprint.

Chargeback in action

As an example, take an online retailer that specializes in outdoor goods, such as hiking boots, tents, jackets, and other recreational equipment. They ship to customers internationally, and have a high volume of orders. 

Among the features that they offer are real-time order tracking, inventory updates (accurate to the minute), dynamic pricing, and personalization. Given the nature of their time-sensitive business, this retailer will rely heavily on Kafka data to power many of their business-critical functions.

Their hypothetical Kafka environment could be structured as follows:

• Dozens of microservices across five product teams: checkout, product search, recommendations, order and inventory tracking, and returns/exchanges

• Shared Kafka clusters used in dev, staging, and prod

• A mix of self-hosted and cloud-based, fully managed Kafka (using platforms such as Confluent, Aiven, etc.)
  
  

With Chargeback, a finance team at this retailer can tag each service account with labels  by team, environment, or project, as below:

• team=checkout

• env=prod

• project=cart-refactor
  
  

Fig. 1. An example of Chargeback in action—a team grouping service accounts with detailed labels.

Now, rather than the raw data that is the default of service accounts, the finance team can be more thoughtful and organized in their approach. They can group expenses by meaningful, actionable dimensions to answer questions such as:

• Which pieces of infrastructure account for the highest Kafka costs? Which teams own these services?

• Are there cost disparities between staging and production environments? If so, why and how?

• Which projects are pushing the most traffic this quarter?

• Which clusters or topics see the least traffic but drive the highest costs? What is their average partition count?

With this enriched context, the finance team can visualize and optimize Kafka expenditures. They can find underperforming (yet expensive) Kafka infrastructure; identify teams that exceeded their budgets (and assist them in getting their spending under control); and cut out unnecessary operational outlays without resorting to layoffs or other harmful measures.

Unify service accounts with Chargeback

If you’re taking an agnostic approach to your Kafka infrastructure, hosting it on multiple cloud providers (such as Confluent Cloud or Aiven), it can be difficult to consolidate service accounts and their associated data in a single place for visibility and insights. 

With Chargeback, you can now monitor, manage, and tag service accounts, regardless of Kafka provider, via the API directly. This takes away the need to switch between platforms and solutions, and provides:

• Centralized visibility into all service accounts

• The ability to organize accounts by team or project

• Reduced config drift and manual cleanup, especially in fast-changing orgs
  
  

Kafka Usage You Can Actually Explain

This release is about visibility, accountability, and alignment. It brings platform teams and finance teams onto the same page—without adding more overhead.

Kafka powers the real-time core of your business. Now you can track it like it matters—by relevant criteria such as project, team, or environment. With Chargeback, you can get improved insights for smarter decisions, lower costs, more efficient operations, and better accountability.

To try Chargeback for yourself, sign up for a free demo.