Guide
Sync Structure & Methodology
Overview
ABM Warranty sync execution is structured as layered responsibilities rather than a single monolithic pipeline. At a high level, the app separates reconciliation, job coordination, and execution so each stage can evolve without changing the core data contract.
This design supports large-fleet stability, resumable behavior, and clearer run observability while keeping final data outcomes consistent across sync types. The internal implementation has additional detail, but the operational model can be understood through the layers described below.
Reconciliation Layer
The reconciliation layer establishes source-of-truth alignment before execution work begins. It evaluates incoming inventory against persisted state to build the authoritative workload buckets needed for safe downstream processing.
At this stage, the app decides what is active, what is inactive, and what should be processed next. This keeps later execution paths from making independent data truth decisions and reduces drift between sync runs.
Job Coordination Layer
After reconciliation, the coordinator builds a job plan and chunks work into bounded units. This layer controls ordering, progress accounting, completion state, and resumability signals for each job and chunk.
By separating coordination from data truth-making, the app can tune chunk size, track partial completion, and expose status without changing the reconciliation rules that define correct outcomes.
Execution Layer
The execution layer performs the actual API and enrichment operations through the selected runtime path. Different paths can optimize behavior for simple or enterprise conditions, but both consume the same planned chunk workload model.
Results flow through shared ingestion, where success and failure outcomes are applied back into persisted state using the existing sync contract boundaries. This keeps execution strategy separate from correctness rules.
Chunking and Cancellation
Chunking is a control mechanism for large workloads and long-running runs. It improves operational visibility and helps the app maintain stable progress under variable API conditions, including throttling and intermittent failures.
Cancellation is handled as an execution interruption, not a contract change. A cancelled run may end with incomplete jobs, but already committed chunk results remain durable and visible for follow-up continuation or review.
High-Level Flow
Sync Request
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Reconciliation Planner
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Job / Chunk Coordinator
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Execution Path (Primary or Enterprise)
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Shared Result Ingestion + Persisted State