Usage & Billing

The Usage & Billing page gives you a real-time view of your organization's compute consumption and associated costs for the current billing period. Use it to track spend, understand where minutes are being consumed, and manage payment information.

Pay-as-you-go billing - $0.004 / min

You only pay for what you use - billed per compute minute with no monthly minimums. Every new organization starts with 5,000 free minutes.

5,000 free minutes on the base 4vCPU runner. For higher-tier plans, a multiplier is applied to your free minute consumption (e.g., 8vCPU runners consume free minutes at a 2x rate).

The page is organized into three sections:

Summary Metrics - total spend, compute minutes, and job count for the current billing month
Spend Over Time - a line chart showing daily cost and job activity over the selected time range
Spend Breakdown - a donut chart attributing spend by repository or runner configuration

Adding Payment Information

Before your organization can run jobs beyond the free tier, a valid payment method must be on file. The Add Payment Info button appears in the top-right corner of the page if no payment method has been added yet.

Jobs will be queued but not executed once the free-tier minute allowance is exhausted. Adding a payment method immediately unblocks all queued jobs.

Navigate to Usage & Billing

Select Usage & Billing from the left-hand navigation sidebar.

Click Add Payment Info

The button is located in the top-right corner of the page. Clicking it opens a secure external payment portal.

Enter your billing details

Provide your card number, expiry date, CVC, and billing address. Monk CI uses a PCI-DSS compliant payment processor - Razorpay for domestic payments and Dodo Payments for international payments. Card details are never stored on Monk CI servers.

Confirm and save

Once saved, your payment method will appear as active and any queued jobs will resume automatically within a few seconds.

Summary Metrics

Three metric cards at the top of the page provide a snapshot of your organization's usage for the current billing month. All three values reset on the 1st of each billing month.

Total Spend

Cumulative USD charges for compute minutes consumed this month.

Total Minutes

Compute minutes consumed across all job executions this month.

Total Jobs

All job executions triggered this month, regardless of status.

Compute minutes are billed per runner configuration. Larger runners (e.g., 16vcpu) consume minutes at a higher multiplier than smaller ones. See the Runner Pricing section below for the full rate table.

Runner Pricing

Runner	vCPU	Multiplier	Effective Rate	Typical Workloads
`2vcpu`	2	1×	$0.004 / min	Linting, unit tests, small builds
`4vcpu`	4	2×	$0.008 / min	Integration tests, moderate builds
`8vcpu`	8	4×	$0.016 / min	End-to-end tests, Docker image builds
`16vcpu`	16	8×	$0.032 / min	Heavy compilation, monorepo builds

Spend Over Time

The Spend Over Time chart plots daily spend (USD) and daily job count on a shared time axis, making it straightforward to correlate cost spikes with periods of high job activity.

Hovering over any data point surfaces a tooltip showing the exact Spend in USD and Job count for that bucket. The time range selector in the top-right adjusts chart granularity:

Range	Granularity
`2h`, `1D`	Hourly buckets
`7D`, `1M`	Daily buckets
`6M`	Weekly buckets

Spend (USD) - daily cost calculated as minutes × per-minute rate for each runner configuration used that day.
Jobs - total job executions for that day. Use this series to distinguish between cost increases caused by more jobs versus longer or more expensive jobs.

If spend is rising but job count is flat, jobs are likely running longer or routing to larger runner configurations. Cross-reference with the Analytics page to inspect P90 Duration and runner utilization.

Spend Breakdown

The Spend Breakdown section displays a donut chart attributing the current month's total spend. Use the Repository and Runner toggle buttons in the top-right corner of the section to switch between views.

Each segment of the donut chart represents one repository within your organization, sized proportionally to its share of total compute spend for the month. A legend to the right lists each repository alongside its percentage contribution.

Use this view to identify which repository is the primary cost driver, then navigate to Analytics and apply a repository filter to inspect job volume, failure rate, and duration trends for that repository specifically.

The donut chart breaks down spend by runner configuration - for example, the proportion of cost attributable to 2vcpu jobs versus 8vcpu or 16vcpu jobs.

Use this view to evaluate whether right-sizing your runner configurations could meaningfully reduce monthly cost.

Common Use Cases

Identifying which repository is driving costs

Navigate to Spend Breakdown and select the Repository view.
Locate the largest segment in the donut chart and confirm against the legend.
Go to Analytics, apply the repository filter, and review job volume, failure rate, and duration trends.

Investigating a sudden cost spike

Set the time range to 7D and find the elevated day in Spend Over Time.
Hover the spike - if job count was also high, the spike is volume-driven. If job count was normal, jobs ran longer or on larger runners.
Switch to the Runner view in Spend Breakdown to check which configurations were used that day.

Forecasting end-of-month spend

Set the time range to 1M and observe the Spend Over Time trajectory.
Divide Total Spend by the number of elapsed days in the month, then multiply by total days in the month.
Contact support if you need to configure spend alerts or billing caps.

Evaluating runner right-sizing

Open Spend Breakdown → Runner and check if a large share is attributed to 16vcpu.
Navigate to Analytics and apply the runner filter for those configurations.
Review the P90 Duration chart - if large runners are completing jobs in under 2 minutes, switching to smaller runners could reduce cost meaningfully.