Apify Credits Monitoring

Apify Credits Monitoring is a read-only Actor that tracks Apify usage credits across one or more accounts — your own, or client organizations that have explicitly shared their API token with you. For each account it reports the current billing cycle (included vs. used credits, remaining balance, days until reset) and walks back through past billing cycles to build a usage history with averages, trends, and top cost drivers.

Because it runs on the Apify platform, you get API access to the results, scheduling (e.g., a weekly credit check), integrations, and monitoring out of the box.

Why use Apify Credits Monitoring?

• Never lose prepaid credit — see which accounts have unused credit about to reset.
• Spot overages early — accounts that exceeded their included allowance are flagged.
• Understand spend — per-service cost breakdown shows what actually drives usage (compute, proxy, storage…).
• Agency-friendly — monitor many client accounts in one run, one dataset row per client.
• Safe by design — it only sends read GET requests. It never starts runs, changes settings, or writes to any monitored account.

How to use Apify Credits Monitoring

1. Open the Actor and go to the Input tab.
2. Add the API tokens of the accounts to monitor as a JSON array, e.g. ["apify_api_…"] — to monitor your own account, paste a token from Apify Console (Settings → API & Integrations). Account names are looked up automatically.
3. Optionally set how many past billing cycles to analyze (default 6).
4. Click Start and open the Output tab, or Schedule the Actor for a recurring credit check.

Input

Field	Type	Description
tokens	array	Required. API tokens of the accounts to monitor: ["apify_api_…", "apify_api_…"]. Secret input — encrypted before storage, decrypted only inside the run. Account name and username are fetched from the API.
months	integer	Past billing cycles to pull per account (default 6, max 24).

Tokens are used only for authentication of read requests and are never written to the output.

Output

One dataset row per monitored account. In Apify Console, the Output tab renders the results as a sortable table — the Credit snapshot view shows every account's current cycle at a glance, and the History stats view summarizes spending across past cycles. Example of the Credit snapshot view:

#	Client	Plan	Included $	Used $	Left $	% Used	Days left	Trend	Usage (old→new)	Top cost driver
1	Acme Care Group	STARTER	29	3.87	25.13	13.3	16	n/a	▁	PAID_ACTORS_PER_EVENT
2	Northwind Automations	FREE	5	0.74	4.26	14.8	14	n/a	▁	PAID_ACTORS_PER_EVENT
3	DACH Leads GmbH	STARTER	29	1.08	27.92	3.7	9	n/a	▁	PROXY_RESIDENTIAL_TRANSFER_GBYTES
4	Harvest Farm Co	STARTER	29	0	29	0	26	n/a	▁	PAID_ACTORS_PER_EVENT
5	Beacon Reviews	STARTER	39	0.05	38.95	0.1	25	n/a	▁	PAID_ACTORS_PER_EVENT
6	Windward Org	STARTER	29	0	29	0	14	n/a	▁	DATASET_TIMED_STORAGE_GBYTE_HOURS
7	Optiva Labs	STARTER	29	5.37	23.63	18.5	2	n/a	▁	PAID_ACTORS_PER_EVENT

Simplified JSON example of one row:

{
    "name": "Acme Ltd",
    "username": "acme",
    "plan": "STARTER",
    "included_credits_usd": 49,
    "used_usd": 31.2,
    "remaining_usd": 17.8,
    "pct_used": 63.7,
    "cycle_end": "2026-07-19T00:00:00.000Z",
    "days_left": 12,
    "overage": false,
    "hist_avg_usd": 28.4,
    "trend": "rising",
    "spark": "▁▃▄▅▆█",
    "top_service": "DATA_TRANSFER_EXTERNAL_GBYTES",
    "history": [{ "start": "…", "end": "…", "total_usd": 24.1, "services": { "…": 12.3 } }]
}

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Data fields

Field	Meaning
included_credits_usd / used_usd / remaining_usd	Current-cycle allowance, spend, and what's left
pct_used, days_left, overage	How far into the allowance and the cycle the account is
hist_avg_usd, hist_min_usd, hist_max_usd, hist_cycles	Stats across completed billing cycles (the in-progress cycle is excluded so it doesn't skew averages and trends; it appears in history flagged "partial": true)
trend, trend_pct, spark	Rising / steady / falling spend, with a text sparkline
avg_unused_usd	Typical unused credit per cycle (assumes the current plan applied historically)
top_services, history	Per-service cost drivers and the full per-cycle detail

How much does it cost to monitor Apify credits?

Very little — the Actor only makes a handful of lightweight API requests per account (roughly 2 + months requests each), so runs finish in seconds and consume minimal compute. Monitoring the accounts costs orders of magnitude less than the credits it helps you keep track of.

Tips

• Schedule it weekly or a few days before your billing cycle resets to catch idle credit in time.
• History depth is limited by Apify's data retention; cycles older than retention are skipped automatically.
• Billing cycles are anchored to each account's signup day, not calendar months — the Actor handles this by walking cycles back one by one.

FAQ, disclaimers, and support

Is it safe to give this Actor a client's token? The Actor sends only read GET requests to Apify's official API (/users/me, /users/me/limits, /users/me/usage/monthly). The tokens input is a secret input field: tokens are encrypted (AES-256-GCM + RSA) before being saved, appear only as ENCRYPTED_VALUE:… in the run detail, Console, and API, and are decrypted only inside the Actor run itself. They are never written to the dataset or logs (logs show at most the last 4 characters). Only share tokens with the explicit consent of their owner, and prefer scoped/limited-permission tokens where possible.

Why is history shorter than requested? Older cycles fall outside Apify's data retention and are skipped.

Found a bug or need an extra metric? Please open an issue in the Issues tab.