Queue Depth
The number of items waiting in a queue; signals whether capacity is keeping up with demand.
Queue depth measures how many items are waiting to be processed. It shows if consumers are keeping up with producers.
Operations teams watch queue depth for jobs like email sends, data syncs, and ticket triage. Rising depth signals capacity constraints or downstream slowness.
In workflows, depth informs scaling decisions—adding workers, throttling inputs, or triggering alerts. Managing depth keeps latency predictable and prevents backlog crises.
Frequently Asked Questions
What is a healthy queue depth?
One that stays within SLA targets for wait time. Small, stable depth is ideal; spikes should drain quickly.
How do I react to rising depth?
Add consumers, throttle producers, or investigate downstream performance. Check for stuck or poison messages.
Should depth thresholds differ by queue?
Yes—set thresholds based on SLA and workload type. Critical paths get tighter limits and alerts.
How do retries affect depth?
Retries increase depth. Space them out with backoff to avoid compounding backlog during incidents.
How do I monitor depth effectively?
Track depth, age of oldest message, throughput, and error rates. Alert on sustained growth, not just transient spikes.
Can depth be zero?
Yes, during low load. Constant zero may mean over-provisioning or idle resources; balance cost vs. latency needs.
How do I prevent unbounded queues?
Set max lengths, dead-letter policies, and backpressure to callers. Drop or reroute low-priority work when overloaded.
Does queue depth impact cost?
Yes—larger backlogs can drive storage and compute costs. Right-size consumers and retention to control spend.
What about multi-tenant queues?
Isolate high-noise tenants, apply per-tenant limits, and monitor fairness to prevent one tenant from starving others.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
Ship glossary-backed automations
Bring your terms into GrowthAX delivery—map them to owners, SLAs, and instrumentation so your automations launch with shared language.
Plan Your First 90 Days