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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteA batch move should be designed as many independently tracked item operations, not one all-or-nothing job, unless the storage system explicitly guarantees atomicity. Persist each item’s outcome, retry only failures likely to be temporary, and make resumption and recovery part of the workflow from the start.
Define what “moved” means before writing the worker
First specify the invariant for a single item. Identify its source and destination, whether an existing destination may be overwritten, and which system is authoritative for declaring the move complete. Without that definition, a timeout or partial response can leave the worker unable to distinguish a completed move from an unfinished one.
For a copy-then-delete workflow, one useful state model is pending → copied/staged → verified → source removed → complete. Add explicit retryable_failure and permanent_failure states, and use compensated if the workflow may undo an earlier step. These are proposed application states, not fields required by a particular batch service.
Give the job a durable operation ID and each item a stable key. Persist state transitions and actionable error details so a restarted worker can resume and duplicate deliveries can be recognized. Make each step idempotent where possible, or guard it with a deduplication check. If a request times out, do not assume it failed: check the destination or durable operation record before repeating a destructive action.
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Track results for each item
A job-level success or failure hides mixed outcomes. Record at least an item identifier, current state, attempt count, last error code and description, and timestamps useful for diagnosing or resuming work. Report totals for attempted, completed, retryable, permanently failed, and compensated items.
Amazon S3 Batch Operations illustrates this model: it can produce a completion report with each task’s object key or version, status, error code, and description. S3 jobs are asynchronous, and AWS warns that task order need not match manifest order; use individual results rather than input order to identify successes and failures. AWS: Tracking job status and completion reports.
AWS also documents a service-specific behavior: after a job has run at least 1,000 tasks, a task-failure rate of 50% can cause the job to fail. This threshold is about S3 Batch Operations, not a general rule for batch systems; check the current service documentation when implementing against it. AWS: Tracking job status and completion reports.
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Retry selectively, with bounded backoff
Classify failures before retrying. Temporary network errors, throttling, and short-lived service unavailability may be recoverable. Invalid input, missing permissions, and other deterministic configuration problems generally need correction rather than repeated attempts.
- Retryable: schedule another attempt with an increasing delay and a finite retry budget; record each attempt and its outcome.
- Permanent or configuration-related: stop automatic retries, preserve the error reason, and route the item for correction or operator review.
- Ambiguous outcome: resolve whether the operation took effect by checking authoritative state before retrying, particularly before deleting or overwriting data.
Retries can intensify an overloaded service, and repeating a non-idempotent operation can corrupt partially updated state. AWS’s guidance on retries and idempotency explains why backoff and safe repeat behavior belong together. AWS Builders’ Library: Timeouts, retries, and backoff with jitter.
Choose forward recovery or compensation across systems
When a move spans independent services or data stores, there may be no single atomic commit that covers every step. A saga coordinates local transactions and defines what happens when a later step fails: continue forward by retrying, or run compensating actions for earlier completed steps. AWS Prescriptive Guidance: Saga pattern.
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Prefer forward recovery when the operation must eventually finish
If a failure is temporary and the business operation remains valid, retry the failed step and continue from the persisted state. Do not redo completed steps unless they are safe to repeat.
Use compensation when a permanent failure invalidates earlier work
A compensating action is a new local operation, not a free rollback. Record whether compensation succeeded or failed, and expose intermediate states to any system or user that can observe the workflow. Sagas are eventually consistent and do not provide transaction isolation equivalent to one ACID transaction; concurrent operations may need semantic locks or other coordination. Their operational complexity also grows with the participating services. AWS Prescriptive Guidance: Saga pattern; AWS Prescriptive Guidance: Saga orchestration.
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Pick a recovery pattern that matches the failure boundary
| Pattern | Useful when | Tradeoff to plan for |
|---|---|---|
| Per-item status and retry | Items can be processed independently, and one failure should not invalidate successful work. | Requires durable results and duplicate-safe processing. DynamoDB batch APIs, for example, return unprocessed items for diagnosis and retry. AWS API Reference: BatchWriteItem. |
| Partial batch response | A message handler receives a batch but should request retry of failed messages alone. | Support depends on the event source and handler integration; AWS documents partial batch responses for SQS-triggered Lambda processing. AWS Lambda: Using Lambda with Amazon SQS. |
| Saga orchestration or choreography | A business workflow spans services or stores and needs defined continuation or compensation. | Requires idempotent participants and management of eventual consistency, isolation concerns, and growing workflow complexity. AWS Prescriptive Guidance: Saga pattern; AWS Prescriptive Guidance: Saga orchestration. |
| Transactional outbox | A local database update must reliably trigger an event. | Consumers still need idempotent handling because delivery can be duplicated. AWS Prescriptive Guidance: Transactional outbox pattern. |
Compare options by where failures are isolated (item, batch, or whole workflow), whether recovery retries forward or compensates, required consistency, duplicate handling, ordering and concurrency, audit needs, and implementation complexity. No single pattern is universally best.
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Apply platform-specific constraints to the actual move
Amazon S3 is one concrete example, not a universal definition of a move. S3 Batch Operations accepts a list of objects and performs a specified action; documented actions include copying objects and invoking Lambda. AWS describes it as tracking progress and producing completion reports. AWS: Performing large-scale batch operations on Amazon S3 objects.
For an individual S3 object, AWS documents that the console can move objects smaller than 5 GB; larger objects require the CLI, an SDK, or the REST API. Permissions and encryption settings also constrain the operation. Treat the 5 GB threshold and those requirements as S3-specific, and consult the current move guidance for the exact source and destination setup. AWS: Moving objects.
For bulk S3 transfers, AWS lists options including the CLI, replication, S3 Batch Operations, S3DistCp, and DataSync. Choose based on object count and size, source/destination topology, transformations, reporting and retry requirements, and who will operate the transfer; the available guidance does not establish one best method for every workload. AWS: Transferring data to and from Amazon S3.
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Make interruption and reconciliation routine
A resumable job needs a durable source of truth, not just a worker’s in-memory progress. Store the job ID, stable item key, state, attempts, and latest error in a record that survives worker restarts. On recovery, load unfinished items, reconcile uncertain states against the authoritative destination or operation record, and continue only from a known safe point.
Expose durable logs and metrics alongside a human-readable summary. Include item identifiers and useful error reasons in addition to counts, so operators can distinguish a transient backlog from bad input or missing access. If the job feeds events from a database change, an outbox can make the local update and event publication reliably connected, but downstream duplicate handling remains necessary.
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