Simple definition
A method where one system repeatedly checks another system for new data at defined intervals.
Polling is one of the most common collection patterns for security connectors because many APIs expose query endpoints rather than an event stream. The engineering challenge is to make repeated requests complete, efficient, and recoverable over long periods.
What does a polling connector need to manage?
Interval
Determine how often the connector checks for new or changed data.
Checkpoint
Remember the last safely processed source position between runs.
Query window
Define the start and end boundaries used to retrieve incremental data.
Pagination
Retrieve every page in each polling window.
Rate limits
Keep request frequency and page count inside provider quotas.
Retries
Recover safely from temporary network, server, or throttling failures.
Why polling design matters
- Polling too slowly increases detection and workflow latency.
- Polling too aggressively wastes requests and can trigger throttling or provider blocks.
- Incorrect query windows can create permanent data gaps or repeated records.
- Long-running polling services must recover from restarts, deployments, outages, and credential failures.
- Large result sets require pagination and careful checkpoint advancement.
- Polling health needs to be observable because an integration can fail silently while the destination itself appears healthy.
How API polling works
Load durable state
Read the last checkpoint, source cursor, or previous collection boundary.
Calculate the next window
Choose the start/end time, overlap, filters, page size, and source-specific parameters.
Call the source API
Request new or changed data using current authorization and rate-limit controls.
Process all pages
Validate, normalize, enrich, deduplicate, and deliver records while following pagination.
Advance the checkpoint
Persist the new safe position only after processing succeeds.
Wait and repeat
Schedule the next run according to latency needs, API quotas, and operational policy.
Polling interval and window design
Short interval
Reduces data latency but increases request volume and rate-limit pressure.
Long interval
Uses fewer API calls but delays new security information.
Overlap window
Re-reads a small period to protect against late-arriving records.
Source delay
Accounts for APIs where new events become queryable after their event timestamp.
Schedule jitter
Spreads many connector instances so they do not all poll at exactly the same second.
Catch-up mode
Handles larger windows safely after a long outage or connector downtime.
Common security API polling use cases
Alert and log collection
Poll security products or SaaS audit APIs for new events.
Incident synchronization
Retrieve new and updated incidents or alerts from an XDR platform.
Posture findings
Check cloud security APIs for new findings, asset changes, and status updates.
Vulnerability scanning
Retrieve newly discovered or changed vulnerabilities after scanner processing.
Identity activity
Collect sign-ins, directory changes, sessions, and account events.
Threat feeds
Fetch new indicators and enrichment updates from intelligence services.
Polling vs Webhook vs Pagination
| Pattern | Primary purpose | Typical consideration |
|---|---|---|
| Polling | Repeatedly ask the source for new or changed data. | Broadly supported, but request volume and latency depend on the polling interval. |
| Webhook | Let the source push an HTTP notification when a supported event occurs. | Lower idle traffic and faster event delivery, but requires a reachable receiver and reliable delivery handling. |
| Pagination | Retrieve all pages in one result set. | Completes each polling window when the source returns more records than one response can hold. |
Key technical considerations
Checkpoint safely
Persist state only after records are durably processed.
Use bounded retries
Retry temporary failures with backoff rather than creating tight loops.
Honor rate limits
Adjust intervals, page sizes, and retry timing to provider quotas.
Deduplicate overlap
Small lookback windows improve completeness but require duplicate control.
Monitor credentials
Token expiration or revoked access can stop polling even while the scheduler still runs.
Measure sync health
Expose last success, poll duration, records received, lag, checkpoint age, retries, and failures.
Benefits and common problems
Benefits
- Works with APIs that do not push events.
- Simple recurring collection model.
- Can reconcile missed or changed records.
- Supports incremental ingestion with checkpoints.
- Flexible latency-versus-request-volume tradeoff.
Common problems
- Intervals that are too short or too long.
- Checkpoint advancement that creates data gaps.
- No overlap for late-arriving records.
- Throttling after large catch-up windows.
- Polling appears scheduled but authorization has failed.
How ForshTec builds production polling connectors
ForshTec designs API polling as a complete reliability loop with checkpoints, pagination, overlap, retries, rate limits, token lifecycle, deduplication, and health monitoring.
- Polling interval and query-window design
- Checkpointing and catch-up behavior
- Pagination and high-volume processing
- Retry, backoff, and rate-limit handling
- Token refresh and credential diagnostics
- Duplicate control and sync-health monitoring
Need to turn a periodic API into dependable security ingestion?
ForshTec can engineer the polling loop so it stays complete, rate-limit aware, recoverable, and observable through normal failures and platform changes.
Talk to ForshTecFAQs
What is polling in an API integration?
Polling is a pattern where the consumer repeatedly checks a source API at defined intervals for new or changed data.
How often should an API be polled?
The interval depends on required data latency, provider rate limits, event volume, query cost, and how quickly the source makes new records available.
Why does polling need checkpointing?
Checkpointing records the last safely processed position so each poll can continue without rereading the full history or skipping data.
How is polling different from a webhook?
Polling asks the source for changes on a schedule, while a webhook pushes a notification from the source to the receiver when an event occurs.
Why use an overlap window?
Some APIs expose records late or have timestamp-boundary issues. A small overlap reduces data-loss risk when combined with deduplication.
What should be monitored in a polling connector?
Last successful poll, checkpoint age, source lag, request duration, records retrieved, page count, rate limits, retries, and authentication failures.