Monitor website uptime on a schedule, alert your team via email and Slack, and log outcomes for long-term reliability.
This AI agent reads a list of websites from a Google Sheet, schedules regular checks, and determines if each site is UP or DOWN. It triggers alerts by email and Slack when a site is DOWN. It updates the sheet with the current state and logs uptime data to enable long-term reliability insights.
Concrete actions performed to keep sites healthy and auditable.
Fetch URLs from Google Sheet.
Perform HTTP checks on each URL.
Determine UP or DOWN status for each site.
Send email and Slack alerts for DOWN sites.
Update the Google Sheet with current state and timestamp.
Log uptime data to enable long-term analysis.
This AI agent replaces manual uptime checks with scheduled automation and centralized logs. It delivers alerts and auditable uptime data.
A simple three-step flow anyone can follow.
Fetch the website list from the data source on a fixed schedule.
Send HTTP requests to each URL and classify status as UP or DOWN.
If DOWN, send alerts and update the sheet; append a log entry for uptime calculations.
A realistic scenario showing inputs, actions, and results.
A webmaster monitors five sites by reading URLs from a Google Sheet, checks every 5 minutes, and logs results. In one cycle, Site A shows DOWN and an email plus Slack alert is sent within 60 seconds. Site A recovers within 5 minutes, and the sheet is updated with the DOWN duration; the weekly uptime percentage is updated accordingly.
Roles that gain concrete value from this agent.
Wants a low-cost uptime check across a small portfolio.
Needs reliable alerts for client sites and simple reporting.
Requires scheduled checks to complement existing monitoring.
Needs auditable uptime logs to report reliability to stakeholders.
Manages several sites with a tight budget and minimal tooling.
Ensures critical campaigns stay online and accessible.
Connects with familiar tools to run the AI agent.
Stores URLs to monitor and logs results back to the sheet.
Sends alert emails when a site is DOWN.
Posts alerts to a channel when a site is DOWN.
Practical scenarios where this AI agent shines.
Common questions about the AI agent and its workflow.
The agent monitors a list of websites provided in a data source (Google Sheets by default) and performs periodic HTTP checks to determine if each site is UP or DOWN. It aggregates results to provide a clear uptime picture and stores ongoing state in the same data source. The monitoring runs on a defined schedule, so it does not require constant manual triggering. It also logs each check to support historical analysis and trend identification.
When a site is DOWN, the agent immediately sends alerts through configured channels (email and Slack) to notify the on-call team. It updates the data source with the failure state and timestamp for traceability. A log entry is created to record the downtime duration and the event. The workflow continues to monitor other sites while the issue is addressed. Once the site recovers, the status is updated again in the log and source sheet.
Uptime data is stored in the chosen data source (Google Sheets by default). Each check updates the site's current status and timestamp, creating a running history of state changes. The sheet serves as the primary source of truth for current status and near-term trends. Logs may also be persisted in the agent’s internal log to support longer-term analysis and reporting.
Yes. The monitoring interval is configurable in the AI agent’s settings. The workflow example uses a 5-minute cadence, but you can adjust it to shorter or longer intervals depending on your needs, traffic volume, and tolerance for false positives. Changes apply across all monitored sites without modifying each URL individually. It’s also straightforward to test new intervals on a small subset of sites first.
The approach scales by increasing the number of rows in the data source and adjusting the schedule accordingly. Alerts are still sent per DOWN site, and logs are appended incrementally so historical data remains intact. As the site count grows, you can segment alerts or route them to different channels to avoid noise. If needed, you can migrate to a larger data source or integrate with a lightweight database for very large deployments.
Yes. The data source is pluggable. You can replace Google Sheets with Excel, Airtable, or another database as long as the agent can read the list of URLs and write status updates. The core logic—scheduling, HTTP checks, alerting, and logging—remains the same. If you replace the data source, ensure access permissions and data formats align with the agent’s input/output expectations.
Prerequisites include a data source containing the list of URLs to monitor, Gmail access for email alerts, and Slack access for channel alerts. You also need a means to host or run the AI agent (e.g., a local environment or cloud function) and an internet connection to perform HTTP checks. The workflow can be adapted to other data sources or alerting channels if your team uses different tools. Once set up, you can start with a small set of URLs and scale up gradually.
Monitor website uptime on a schedule, alert your team via email and Slack, and log outcomes for long-term reliability.
