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Operate and improve

Spot backlogs before work stalls

Distinguish a healthy burst from work that is accumulating faster than workers clear it.

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Captured from the product Demo workspace
See whether accepted work is clearing, aging, or accumulating.

What this changes for your team.

Fleet queue metrics show how much work is waiting, how long the oldest item has waited, and whether processing is draining the backlog. These signals make capacity pressure visible without requiring operators to infer it from individual sessions.

How it works in practice.

  1. 01

    Read current queue depth to quantify outstanding accepted work.

  2. 02

    Check oldest queue age to find whether any item has waited unusually long.

  3. 03

    Use drain state to see whether throughput is reducing or growing the backlog.

What you can plan around.

The behaviour you can design against, stated concretely.

Queue metrics are read from worker queue state and correlated with persisted execution ownership.

Oldest age uses the earliest waiting item's accepted or enqueued timestamp.

A healthy queue metric does not promise an individual external provider will respond successfully.

Complete the operating path

View all capabilities
Operate and improveTrace every trigger attempt

Answer when a trigger fired, what it targeted, and how its fan-out progressed.

Operate and improveSee which agents are reliable - and which are slow

See whether an agent finishes dependably and how long typical and slow runs take.

Run it reliablyNever lose track of accepted work

Give every accepted unit of work a durable identity and history before execution begins.

Bring one real process

See how Yekar.AI fits the way you work.

Start with a job your team already owns, plus the tools and decisions around it.

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