Automation Watchdog LogoAutomation Watchdog

From Concept to Reality: Practical Use Cases

What Automation Watchdog Does

Automation Watchdog gives you proof that the events you expected actually happened and on time. Think of it as a the heart rate monitor for your various automation workflows with the ability to customize the expected heartbeat pattern.

Core Concepts

Watch

A rule that defines what success looks like (when something should check-in, how often, and what counts as "on time").

Check-in

A tiny API signal your workflow sends when it reaches the meaningful moment (e.g. work loaded to a queue, queue item completed or a report sent).

Outcomes

Satisfied

Check-in arrived within the allowed window → no alert.

Missed

Check-in didn't arrive in time → alert the team.

Privacy

You send only metadata (which watch, machine or queue). No PII or business data.

What it Is / Isn't

Is

A lightweight, PII-free heartbeat monitor that proves the right thing happened on time.

Isn't

A log collector, job scheduler or RPA platform replacement. It complements those by eliminating daily "babysitting."

Three Common RPA Monitoring Patterns

Automation Watchdog handles the most critical monitoring scenarios in RPA environments. Each pattern addresses different workflow types and timing requirements.

Scheduled Watch

Daily Dispatcher Assurance

Monitor time-based workflows that must complete within a specific window (e.g., M-F 3-4 PM).

Fixed schedule
Time window
Single check-in
Rolling Watch

Queue Processing

Monitor continuous workflows that should check in regularly while active (e.g., every 7 minutes).

Interval-based
Repeating windows
Multiple check-ins
Dependent Watch

Chained Reporting

Monitor workflows triggered by other processes (e.g., report generation after queue completion).

Event-triggered
Chained workflow
Conditional timing

Use Case 1 — Daily Dispatcher Assurance (M–F, 3–4 PM)

Scenario

Your Dispatcher must run successfully between 3–4 PM Monday–Friday. Today the RPA team checks on the job after 4 PM to verify success.

Watch Configuration

Type:

Scheduled Watch

Schedule:

M–F at 3:00 PM (local)

Check-in Type:

Fixed window = 60 minutes

Expectation:

A check-in must arrive by 4:00 PM each weekday

How it plays out
1

At 3:00 PM, AWD activates the watch window for the day.

2

Your Dispatcher runs and, on successful completion, sends a single API call (the check-in).

If AWD receives the check-in by 4:00 PM → Watch Satisfied.

!

If AWD does not receive a check-in by 4:00 PM → Alert sent to the team.

3

AWD auto-calculates the next active window for the following weekday.

Failure modes caught
  • Job skipped, stuck, or failed silently
  • Infra/job scheduler issues
  • Credential/queue dependencies preventing completion
Why it's better than job-checking
  • No human polling at 4 PM
  • No trawling through noisy platform alerts
  • Clear, binary assurance: Did the expected thing happen on time?

Use Case 2 — Performer Keeps the Queue Moving

Scenario

Your Performer robots pick items from the queue whenever they're loaded by the Dispatcher.

They should be completing work about every 3 minutes while items remain in the queue.

Today, the RPA team either checks queues manually or hears directly from their customer that something is wrong with the automation.

Watch Configuration

Type:

Rolling Watch (interval-based)

Activation:

When Dispatcher loads items to queue, it send and activate signal for this Watch

Check-in Type:

Cascading window = 7 minutes.
Set the window longer than the 3-minute average to allow normal variation, so alerts only fire when processing truly stalls.

Expectation:

At least one check-in every 7 minutes while queue is non-empty

Deactivation:

When queue is confirmed empty, the workflow sends a deactivate signal

How it plays out
1

Dispatcher loads items to the queue → activates the Performer Watch.

2

Each Performer robot, after finishing a queue item, sends a check-in signal.

As long as at least one check-in arrives within each 7-minute window → Watch is Satisfied.

!

If no Performer check-in is received within 7 minutes → Alert sent to the team.

3

When each Performer finds no more work, it sends a ‘deactivate’ signal. Once all Performers have deactivated, the Watch turns off until the next Dispatcher load.

Failure modes caught
  • Queue trigger misfires, so Performers never start
  • Performer crashes or hangs, leaving items unworked
  • Infrastructure issue blocks all Performers from running
  • Credentials, queue access, or resource contention issues cause silent failure

Use Case 3 — Reporter Delivers Final Report Within 30 Minutes

Scenario

After the Performer robots finish clearing the queue, a Reporter process must generate and send a summary report (email, file, dashboard update, etc.).

The Reporter must complete its job within 30 minutes after the Performers finish.

Today, teams often check shared folders, inboxes, or dashboards to confirm the report arrived. If it fails silently, the gap may not be caught until the next business day.

Watch Configuration

Type:

Dependent Watch (chained to Performer completion)

Activation:

When Performer Watch is deactivated"

Check-in Type:

Fixed window = 30 minutes

Expectation:

Reporter must check in within 30 minutes of Performer completion

Deactivation:

Once Reporter check-in is satisfied, the Reporter deactivates the watch until next Performer run triggers it again

How it plays out
1

Performer completes the queue and deactivates the Performer Watch → triggers Reporter Watch.

2

Automation Watchdog opens a 30-minute active window.

3

Reporter runs, finishes, and sends a check-in (e.g., after emailing the report).

If Reporter check-in arrives in time → Watch Satisfied.

!

If no check-in within 30 minutes → Alert sent to the team.

4

Reporter deactivates the watch.

Failure modes caught
  • Report never generated after queue completion
  • Email service or file transfer fails
  • Report takes too long to generate and misses SLA
  • Process silently fails after queue handoff

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