restore-test agent hit API rate limit mid-sweep and the verification failed

TL;DR

A restore-test sweep that dies on rate limits is doing unbounded work against a bounded API. Add checkpointing so each verified snapshot is recorded before the next call, pace requests with exponential backoff on 429 responses, budget calls per sweep window, and resume from the checkpoint instead of restarting the whole verification.

restore-test agent hit API rate limit mid-sweep and the verification failed

Use this when

• The agent verifies early snapshots then fails mid-sweep with rate limit errors.
• Retries happen instantly with no backoff and worsen the throttling.
• A restarted sweep re-verifies everything from zero.

Not for this skill when

• The backup product itself rejects jobs for licensing or capacity. Different limit.
• One call fails once with a transient limit and a simple retry succeeds.

Steps

1. Inspect the sweep logs to find the call rate, the limit response, and whether any progress was saved. Verify: rate, limit type and checkpoint behaviour are documented
2. Add persistent checkpoints recording each snapshot verification outcome as it completes. Verify: killing a test sweep mid-run preserves completed results
3. Implement exponential backoff with jitter on rate limit responses and honour any retry-after guidance. Verify: a simulated limit shows growing delays, not instant retries
4. Set a per-window request budget below the API published limit and make the sweep stop cleanly at budget, scheduling its own continuation. Verify: the sweep pauses gracefully at budget
5. Run the full sweep and confirm it completes across one or more windows with no lost work. Verify: all snapshots are verified exactly once in the final report

Variant phrasings

agent sweep 429 rate limit checkpoint resume

The checkpoint phrasing.

restore verification agent throttled api

The throttle variant.

agent backoff retry after verification sweep

The backoff wording.

Compatibility: Agent frameworks calling Veeam, cloud and storage REST APIs with published rate limits, Python or TypeScript orchestrators with persistent run state.

Why it happens

Sweeps feel cheap to write as simple loops, but APIs defend themselves with limits a tight loop will always hit at scale. Without checkpoints, the failure cost is the whole run, which tempts developers into aggressive retries that deepen throttling. Checkpoint plus backoff converts a hard failure into a scheduling property.

Edge cases / pitfalls

• Count a verification as done only after its evidence is stored. In-memory progress is not progress.
• Different APIs limit by different keys, per account, per agent, per IP. Know which key you consume.
• A sweep that respects limits but never finishes needs its window or budget renegotiated, not its manners removed.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Kvu6VzUZlBYJl5Sv83Vygw