Salesforce Core + Data Cloud Integration
How BuildForce monitors and maintains your Salesforce–Data Cloud integration health in real time.
Data Cloud problems show up as stale segments and wrong activations rather than as integration errors. The most common failure modes are streaming endpoints with rising ErrorRate but no DeadLetterQueueEnabled (events drop silently), data streams whose source schema drifted but whose mapping wasn't updated (new fields fill with nulls), identity resolution rulesets that stopped matching after a source DLO renamed a field, and DMOs whose primary DLOs haven't ingested fresh data in days. BuildForce reads DataStream, StreamingEndpoint, and DMO metadata directly to surface all four.
The Problem
Data Cloud sits between source systems and activation. When a stream silently degrades or a DLO mapping breaks, segments still publish — they just publish stale or wrong data. Marketing activates to an audience that doesn't reflect current reality. Personalization fires on identity matches that no longer hold. The failure is invisible until campaign performance drops or finance asks why churn predictions stopped tracking.
Streaming endpoint silent failures
StreamingEndpoints with high ErrorRate and no DLQ configured drop events with no recovery path. BuildForce surfaces endpoints where RetryPolicyConfigured=false or DeadLetterQueueEnabled=false.
Source schema drift
When a source system adds, renames, or removes a field, the DLO mapping doesn't auto-update. BuildForce diffs source schema against the active mapping and flags drift.
Identity resolution ruleset breakage
Identity resolution rules reference specific DLO field paths. A field rename breaks the rule silently and identity matches stop happening. BuildForce validates field references in every ruleset.
Stale DMO data
DMOs depend on regular DLO refreshes. When a DLO stops ingesting, the DMO appears available but contains stale data. BuildForce tracks last-ingest timestamp per DLO chain.
How BuildForce Solves It
BuildForce monitors every DataStream's last successful ingest timestamp, every StreamingEndpoint's ErrorRate and DeadLetterQueueEnabled status, every DLO-to-DMO mapping for schema drift, and every active segment's underlying data freshness.
Data stream health dashboard
Per-stream status, ErrorRate, last successful ingest, and DLQ configuration in one view.
DLO-to-DMO lineage map
Visual map of which DLOs feed which DMOs, with freshness indicators for each step.
Identity resolution audit
Validates every active ruleset's field references against current DLO schemas and surfaces broken references.
Segment freshness scoring
Scores active segments by the freshness of their underlying DMOs and flags segments activating on stale data.
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