Credit-based pricing models are becoming increasingly common, especially among API-first and AI-native products. They offer flexibility to abstract complex or variable usage patterns into a single unit, and they offer a simple purchasing experience for customers.
But implementing a credit system, especially one that supports real time burndown, isn’t simple. At first glance, it might seem like a straightforward problem: track usage, subtract credits, and block access when the balance hits zero. In practice, it touches nearly every part of the system: product instrumentation, data pipelines, access controls, billing infrastructure, and user-facing dashboards.
This article is a technical guide to building a credit burndown system. It’s meant for engineers and engineering leaders who are designing or maintaining this kind of infrastructure. We’ll walk through the core components, highlight the architectural tradeoffs, and surface the common pitfalls that can make credit systems unreliable or hard to change.
Done well, a credit system becomes a powerful abstraction that can evolve as your product and pricing do. Done poorly, it becomes a source of confusion, disputes, and operational debt. The goal is to help you avoid the second outcome.
Credit burndown isn’t a self contained billing feature — it's a core part of your application logic. Once credits are involved, nearly every system needs access to current balances, and they all depend on that data to make decisions in real time.
Product experiences need to reflect credit state clearly. That means:
Blocking or limiting usage when a user runs out of credits
Highlighting remaining usage to drive urgency
Creating clear upgrade paths when limits are hit
Each paywall, feature gate, or upsell prompt becomes credit aware, and those UX decisions depend on having reliable, real time data.
The credit balance must be consistently available across services to answer a simple but critical question: can this user do this right now? That means:
Credit state needs to be fast to read and write
Usage events need to decrement credits atomically
Systems need to handle failure and resiliency
If this layer is too slow, requests get blocked. If it’s too eventual, access decisions become inconsistent.
Customers expect to see their current usage, remaining credits, and historical spend instantly and accurately. To support this:
Usage events must flow quickly from ingestion to UI
Balances shown in the dashboard must match what the backend is enforcing
Any discrepancies create support churn and erode trust
Customers are more likely to accept limits if they can see them coming.
Sales teams rely on credit data to identify expansion opportunities and close deals. That typically means:
Spotting accounts with high or accelerating credit burn
Bundling credits into custom plans or packaging them with premium features
Issuing promotional credits or discounts to unblock a deal
Offering flexible terms like minimum commits or discounted overages
These are all reasonable, and often necessary, requests. But each one introduces edge cases, exceptions, and pricing drift that your system needs to account for. Without guardrails, it becomes easy to lose track of what a customer should be paying, or why one account burns credits differently than another. Over time, this creates operational debt, makes pricing harder to change, and increases the risk of unintentional revenue leakage.
Everything starts with tracking what users do. Whether you're measuring API calls, compute time, or tokens, events should include:
A stable customer ID
A timestamp
A usage quantity
A resource or feature identifier
These events feed your metering and billing systems, if they’re wrong, everything downstream will be too.
Tips:
Use structured events with consistent schemas across services
Capture customer IDs at the point of usage, not later
Avoid early aggregation, emit raw events where possible to allow reprocessing
Allow the passing of additional information. An unstructured "metadata" field can be helpful to preserve flexiblity.
This service maintains the customer’s current credit balance and applies debits as usage is processed. It’s one of the most sensitive parts of the system, used by infrastructure, billing, and customer facing dashboards.
Tips:
Use atomic, idempotent operations for debits and credits
Store a full history of balance adjustments (including source and reason)
Treat balances as critical state, back them up and monitor them like you would a payments system
Your application needs to make real-time decisions (does the customer have enough credits to do this?) Enforcement can be:
Hard blocking — deny requests when balance is zero
Soft limits — show warnings, apply degraded performance, or alert the user
Hybrid — allow temporary overages or grace periods with backdated charges
Each of these requires a very different technical implementation. Hard blocks often need inline checks with strong consistency guarantees. Soft limits might rely on periodic syncs or cached values. Grace periods introduce the need for credit debt, delayed enforcement, and additional state tracking.
Tips:
Keep enforcement logic consistent across backend and frontend
If caching balances, define and monitor acceptable staleness thresholds
Design enforcement to degrade gracefully if balance data is temporarily unavailable (e.g. fallback to soft limits or serve warnings instead of failing requests outright)
Customers need ways to acquire and replenish credits, via purchases, renewals, or grants. This system defines how credits are issued, tracked, and expired.
Expect this to be an area of constant product iteration. Sales and growth teams will frequently want to experiment with new packaging, promotions, and pricing terms, and your implementation needs to support these changes without significant rework.
Tips:
Track the source of each credit (purchase, promo, grant) for clarity and accounting
Make expirations visible and configurable
Make sure to engage your finance team -- how credit revenue is recognized is critical to the business, but not always straightforward
Also, make sure all credits have an expiration date for Revenue Recognition purposes
Separate logic for recurring plans vs. one-time credit packs
A credit system isn’t just an internal ledger, it’s a part of your product’s experience. Customers are prepaying for something they often can’t see directly (e.g. compute time, API calls), and they’re trusting your system to burn those credits fairly. That trust is hard to earn and easy to lose.
Usage events, credit debits, and customer facing balances all need to agree. That’s difficult when those pieces flow through different pipelines, or when the credit logic lives in multiple services.
Tips:
Use the same balance source for internal logic and user facing dashboards
Monitor for drift between backend state and frontend display (it will happen)
Trust comes from transparency. Customers should be able to inspect what they used, how much it cost, and when it was charged.
Tips:
Make raw usage and credit logs exportable, even if only internally at first
Include timestamps, credit cost, and usage source in balance histories
If you offer tiered pricing or variable burn rates, expose the logic used to rate usage
You will get support tickets that ask:
“Why did I run out of credits?”
“Why does the dashboard say I’m out, but my usage shows less?”
“Why did I burn 50 credits at 3am?”
Without the right tools, engineers will have to debug this manually, usually from logs, pipelines, and databases.
Tips:
Give support and success teams a read only view into credit history and usage logs
Include internal notes or tags on credit adjustments (e.g. manual grants, refunds)
Add tooling to simulate or replay usage for debugging balance discrepancies
Most teams start by assuming credit burndown is straightforward: track usage, subtract credits, show a dashboard. And if your product is small, or usage patterns are simple, you can often get pretty far with a custom implementation.
But over time, the edge cases pile up:
Usage events arrive late or out of order
A customer disputes their balance
Sales wants to run a promotion with expiring credits
Support needs to issue manual top-ups
Pricing changes mid cycle and only applies to some customers
The real cost of building your own system isn’t just in the initial implementation, it’s in supporting all the ways the business needs to evolve. And the more the system sprawls across product, infrastructure, and billing, the harder it becomes to change anything safely.
That doesn’t mean you can’t or shouldn’t build it yourself. But if you do, treat it like critical infrastructure:
Make balances auditable and debuggable
Minimize hard coded pricing logic
Separate usage, rating, and accounting as cleanly as possible
Expect it to change constantly, and build for that
If you're looking to deploy a credit-based pricing model quickly, Schematic is built to handle credit-based pricing and many other pricing models.
Credit burndown systems are deceptively complex. While the core idea is simple, subtract credits as usage occurs, making that work across product, infrastructure, billing, and customer experience is anything but.
Done well, a credit system gives you flexibility: to change pricing, run promotions, or bundle usage in new ways. Done poorly, it creates confusion, erodes trust, and becomes a source of constant maintenance pain.
If you’re building one yourself, design for accuracy, visibility, and change. It’s not just a billing feature, it’s a system your entire business will depend on.
Because it touches multiple systems—product, infrastructure, billing, support, and sales—and each one relies on accurate, real-time balance data to make decisions. Misalignment between them creates trust issues, broken access logic, and maintenance headaches.
Aggregate usage over the same period that credits are granted—typically the billing cycle. Avoid arbitrary time windows like hourly or daily unless there’s a clear product need, and always retain raw usage events for reprocessing.
Balances need to support atomic updates, concurrency, rollback, and manual adjustments—all without corrupting state or losing audit history. Treat them like critical financial infrastructure.
Hard blocks require strong consistency and low-latency balance reads.
Soft limits can tolerate staleness but may allow overages.
Grace periods require tracking credit debt and additional enforcement logic. Each option has UX and technical implications that must stay aligned across systems.
Expose as much as possible: usage logs, timestamps, credit history, and burn rates. Ensure that dashboards match backend enforcement, and give internal teams tools to explain or debug discrepancies.
Because it’s constantly changing. Sales and growth teams will want to experiment with new pricing, grants, and bundles. If your system isn’t flexible—configurable expirations, credit types, and manual top-ups—you’ll end up hardcoding exceptions.
You can, but expect to invest heavily in accuracy, transparency, and change management. The real cost isn’t in the first implementation—it’s in everything that comes after.
