What is Scheduled Execution?
Scheduled Execution lets you run any Autonoly workflow automatically on a recurring basis. Instead of manually triggering workflows, you define a schedule and the platform takes care of the rest — launching the workflow on time, handling failures gracefully, and notifying you of results.
This turns one-time automations into persistent, always-running processes. A Data Extraction workflow that scrapes competitor prices becomes a daily price monitoring system. A Browser Automation that checks inventory becomes an hourly stock alert. The automation logic stays the same — scheduling makes it continuous. For teams just getting started with automation, our guide to scheduling automated workflows walks through the fundamentals.
Schedule Options
Autonoly supports flexible scheduling through multiple methods:
Preset intervals — every hour, every 6 hours, daily, weekly, monthly
Custom cron expressions — full cron syntax for precise control (e.g., "at 9:15 AM on weekdays")
Timezone support — schedules run in your configured timezone, handling DST transitions automatically
One-time scheduled runs — set a specific date and time for a single future execution
Event-plus-time combos — pair a schedule with a webhook trigger so workflows run on a regular cadence *and* respond to real-time events
Cron Expression Builder
Not everyone is fluent in cron syntax. The schedule configuration panel includes a visual cron builder where you select days, hours, and intervals from dropdowns, and the corresponding cron expression is generated automatically. A human-readable summary ("Every weekday at 9:15 AM EST") is always displayed next to the raw expression so you can verify at a glance.
Distributed Scheduler
The scheduling engine is designed for reliability. It runs on a distributed architecture that ensures your workflows execute even if individual servers have issues:
Retry Logic
Not every run succeeds on the first try. Network timeouts, temporary site outages, and transient errors happen. The scheduler automatically retries failed runs with configurable retry policies:
Retry count — set how many times to retry (default: 3)
Backoff strategy — exponential backoff prevents hammering a struggling target
Failure threshold — disable a schedule automatically after N consecutive failures
Custom retry conditions — define which error types should trigger retries and which should fail immediately (e.g., retry on network timeout but not on authentication failure)
Execution Windows
For time-sensitive workflows, you can define execution windows. If a scheduled run can't start within its window (due to system load or other factors), it's either queued or skipped based on your preference. This prevents stale runs from executing hours after their intended time.
Concurrency Controls
When multiple scheduled workflows overlap, concurrency controls determine how they share resources. You can set a global concurrency limit for your workspace and per-workflow limits to prevent resource contention. If a workflow is already running when a new scheduled execution triggers, you can choose to queue the new run, skip it, or cancel the in-progress run and start fresh.
Notifications and Alerts
Stay informed about your scheduled workflows without checking the dashboard constantly:
Failure alerts — get notified via email or Slack when a run fails
Completion summaries — receive a daily digest of all scheduled run results
Conditional alerts — trigger notifications only when results match specific criteria (e.g., price dropped below threshold)
Health reports — weekly summary of schedule reliability and performance metrics
SLA alerts — get notified if a workflow takes longer than an expected duration, which can indicate a site change or performance degradation
Managing Schedules
The schedule dashboard gives you a centralized view of all active schedules:
Calendar view — see upcoming runs across all workflows on a timeline
Execution history — review past runs with status, duration, and output
Bulk management — pause, resume, or delete multiple schedules at once
Quick edit — change schedule timing without modifying the underlying workflow
Dependency chains — configure workflow B to start only after workflow A completes, creating sequential pipelines that run on a single schedule trigger
Combining with Other Features
Scheduled execution pairs naturally with nearly every Autonoly feature:
[Data Extraction](/features/data-extraction) — schedule daily scrapes for price monitoring or lead generation
[Data Processing](/features/data-processing) — run nightly data cleanup and transformation jobs
[Webhooks](/features/webhooks) — combine time-based and event-based triggers for complex automation patterns
[Logic & Flow](/features/logic-flow) — add conditional logic that adapts based on time of day or day of week
[Website Monitoring](/features/website-monitoring) — schedule frequent checks for content changes
Best Practices
Start with a conservative schedule and tighten later. If you are unsure how often you need data refreshed, begin with daily runs and increase frequency only when you confirm the data changes more often. This conserves execution credits and avoids unnecessary load on target sites.
Use execution windows for time-sensitive workflows. A price monitoring workflow that runs three hours late produces stale data. Setting an execution window of 30 minutes ensures the run either happens on time or is flagged as missed, so you always know the data is current.
Combine cron schedules with webhook triggers. Many real-world processes benefit from both. A nightly batch run handles the baseline, while a webhook triggers an immediate re-run when critical events occur — like a competitor updating their pricing page. Learn more about this pattern in our post on AI workflow automation.
Monitor failure rates weekly. The health report surfaces trends you might miss in individual failure alerts. A gradual increase in retry rates often signals that a target site is implementing anti-bot measures, giving you time to adjust before the workflow breaks entirely. Our guide to bypassing anti-bot detection covers strategies for handling these situations.
Tag and organize your schedules. Once you have dozens of active schedules, use tags and naming conventions to keep them manageable. Group by purpose (monitoring, reporting, data sync) or by team, and use the calendar view to spot scheduling conflicts.
Security & Compliance
Scheduled workflows run in isolated environments with the same security guarantees as manually triggered runs. Each execution spins up a fresh browser instance in a sandboxed container, and all data is encrypted in transit and at rest.
Schedule configurations — including cron expressions, retry policies, and notification settings — are version-controlled within Autonoly. You can see who changed a schedule, when, and what the previous configuration was. This audit trail is valuable for compliance in regulated industries and for debugging unexpected behavior changes.
For organizations that require approval before workflows execute, Autonoly supports approval gates. A scheduled workflow can be configured to require manual approval before it runs, with a configurable timeout after which the run is either auto-approved or skipped. This is useful for workflows that perform write operations — such as updating a database or submitting forms via Form Automation — where a human review step adds an extra layer of safety.
Common Use Cases
Daily Competitive Price Monitoring
An e-commerce team schedules a workflow to run every morning at 6 AM. The workflow visits five competitor websites, extracts product prices using Data Extraction, compares them to the previous day's data, and sends a summary to a Slack channel highlighting any significant changes. If a competitor drops a price by more than 10%, an additional alert goes to the pricing team's email. Read more about this pattern in our e-commerce price monitoring guide.
Weekly Lead Generation and Outreach
A sales team runs a weekly workflow every Monday morning. The workflow searches LinkedIn for new prospects matching specific criteria using LinkedIn Automation, enriches the leads with company data from Data Extraction, deduplicates against the existing CRM database, and feeds new contacts into an Email Campaign sequence. The entire pipeline runs unattended and the team reviews results in their Monday standup.
Nightly Data Warehouse Sync
A data team schedules an overnight workflow that extracts data from multiple web-based SaaS tools, transforms it with Data Processing, and loads it into a PostgreSQL database using the Database feature. The workflow runs at 2 AM when system load is low, and results are ready for the analytics team by morning. If any step fails, the retry logic handles transient errors, and persistent failures trigger an alert to the on-call engineer.
Monthly Compliance Reporting
A compliance team schedules a monthly workflow that checks regulatory websites for updated filings, extracts the relevant documents using PDF & OCR, and compiles a summary report. The report is emailed to stakeholders and archived in Google Drive via Integrations. The execution window ensures the run happens within the first business day of each month.
Check pricing to see schedule limits and concurrent execution slots for each plan.