Short answer / recommendation
Switch high-volume lead ingestion off pure Zapier polling and onto webhooks + a lightweight queue (SQS/PubSub/Redis) or a batched worker. Use Zapier only for low-volume/edge processing or as the consumer of aggregated events. This reduces queuing inside Zapier and keeps SLA-sensitive notifications reliable.

Why this works (diagnostics to run first)
1) Inspect Zapier Task History: look for a growing backlog, queued tasks, and spikes in task runtime or retries. Filter by error type and timestamps.
2) Check trigger type & frequency: polling triggers (every 1–15 min) create bursts; instant webhooks are immediate.
3) Identify rate-limited external API calls inside zaps — slow steps cause subsequent tasks to queue.
4) Confirm Zapier plan limits and concurrent-processing behavior (task concurrency and task/month caps).
5) Monitor upstream burst pattern: is traffic spiky (campaign-driven) or sustained high volume?

Immediate (minutes–hours) mitigations
- Convert polling zaps to Webhooks by Zapier where possible to avoid spikes caused by polling.
- Add filters early in the zap to drop irrelevant leads and reduce task count.
- Consolidate or remove nonessential steps (formatters, lookups).
- Temporarily increase notification channel redundancy (SMS/Teams/Email) outside Zapier if SLA-critical.

Short-term (days) mitigations
- Batch leads: collect leads into minute windows and post a single aggregated payload to Zapier (use a small staging endpoint).
- Use Delay/Delay After or Buffer by Zapier carefully to smooth throughput (not a permanent fix for very high volumes).
- Implement basic exponential backoff/ retry logic for steps that hit 3rd-party limits.
- Replace heavy multi-step zaps with a single “Code by Zapier” step that does multiple transformations server-side to reduce task count.

Medium-term (weeks) architecture fixes
- Introduce a message queue (AWS SQS, Google Pub/Sub, Redis streams) as the ingestion buffer. Workers pull from the queue at a controlled concurrency, process business logic, and call the notification endpoint(s).
- Move real-time SLA notifications to a dedicated service (small microservice or serverless function) that scales independently and only use Zapier for enrichment or secondary workflows.

Decision criteria (pick a path based on constraints)
- If budget and engineering time are limited: prioritize webhook conversion, filters, step consolidation, and Zapier plan upgrade.
- If SLAs are strict and volume is sustained/spiky: build a queue + worker pattern or migrate heavy flows to an enterprise iPaaS or custom service.
- If your team is small but can script: use Code by Zapier or a lightweight serverless endpoint to batch and pre-process payloads.

Best-for / Avoid-if
- Best-for: teams handling occasional spikes who need quick wins (webhooks, filters, batching).
- Avoid-if: sustained tens of thousands/day of leads — Zapier will become costly and brittle; use a queue/worker or enterprise platform.

Practical checklist
- [ ] Check Zapier Task History and Status.
- [ ] Convert polling triggers to webhooks.
- [ ] Add early filters and reduce steps.
- [ ] Batch/aggregate leads for high-volume bursts.
- [ ] Add queue (SQS/ PubSub/Redis) if spikes continue.
- [ ] Move SLA-critical notifications to a dedicated service.

If you want, I can outline a minimal queue + worker design (serverless example) or a compact “Code by Zapier” script to batch/process N leads per request.

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