# Data Reliability Engine

*/Software/Data_Reliability_Engine*

## Solution Overview

The Data Reliability Engine continuously tests analytical data pipelines to catch anomalous row counts, null values, and schema drifts before they reach downstream dashboards. It scans Snowflake and BigQuery data warehouses on every dbt run, generating deterministic incident alerts with root-cause query traces. The outcome is an automated quarantine system that pauses faulty data updates and outputs a clean incident log.

Lead Data Engineers buy this headless software to stop stakeholder complaints about broken financial or operational metrics. Instead of writing hundreds of manual SQL assertions for every new table, the engine infers expected data distributions from historical metadata and applies statistical bounds to new ingestion jobs. Human engineers remain in the loop solely to approve intentional upstream schema changes or to resolve isolated quarantine alerts.

As a headless SaaS primitive, the engine sits directly between the cloud data warehouse and the orchestration layer. It consumes raw query logs and table schemas via native warehouse APIs below it. Above it, the engine exposes a REST API that autonomous data-quality agents and orchestration tools like Airflow consume to instantly halt broken directed acyclic graphs.

## Headless Saas Data Model

**Entities**:
- Name: Incident · Description: A detected data anomaly or schema drift that halts pipeline execution
- Name: Workspace · Description: The tenant environment grouping data assets and reliability monitors
- Name: DataAsset · Description: A table or view in the data warehouse being continuously scanned
- Name: DataMonitor · Description: Statistical bounds and expected distributions inferred for a data asset
- Name: PipelineRun · Description: An ingestion job execution tracked from the orchestration layer
- Name: QuarantineEvent · Description: The automated quarantine action applied to pause faulty data updates
**Relations**:
- To: Workspace · From: Incident · Label: belongs to · Cardinality: one-to-many
- To: DataMonitor · From: Incident · Label: triggered by · Cardinality: one-to-many
- To: PipelineRun · From: Incident · Label: detected in · Cardinality: one-to-many
- To: Workspace · From: DataAsset · Label: belongs to · Cardinality: one-to-many
- To: DataAsset · From: DataMonitor · Label: monitors · Cardinality: one-to-many
- To: Workspace · From: PipelineRun · Label: belongs to · Cardinality: one-to-many
- To: Incident · From: QuarantineEvent · Label: secures · Cardinality: one-to-one
**Tenant Anchor**: Workspace
**Primary Resource**: Incident

## Api Definition

**Protocols**:
- REST
- SDK
- MCP
- Webhooks
**Consumed By**:
- [Data Quality Agent](/Agents/Data_Quality_Agent)
- [Pipeline Triage Agent](/Agents/Pipeline_Triage_Agent)
- [Analytics Engineering Agent](/Agents/Analytics_Engineering_Agent)
**Integrations**:
- [Snowflake](/Products/Snowflake)
- [BigQuery](/Products/BigQuery)
- [dbt](/Products/dbt)
- [Apache Airflow](/Products/Apache_Airflow)
**Consumption Model**: A pipeline triage agent registers the MCP server to trigger pipeline scans upon dbt job completion, while subscribing to the quarantine.enforced webhook to immediately halt downstream orchestration graphs.
**Workflow Wrappers**:
- Name: Execute Pipeline Scan · Wraps: evaluates active monitors against a pipeline run and quarantines anomalous assets automatically
- Name: Infer Asset Bounds · Wraps: analyzes historical table metadata to generate statistical bounds and configures new data monitors
- Name: Clear Quarantine State · Wraps: resolves the root-cause incident, lifts the associated quarantine event, and resumes pipeline execution

## Api Function Cascade

**Ai Role**: Operating as a fully stateless headless primitive, the data reliability engine executes end-to-end via deterministic queries and generative anomaly-detection models, evaluating pipeline telemetry and enforcing data quarantines straight-through with zero human intervention.
**Cascade**:
- Kind: Code · Note: Receives job execution states from dbt and Apache Airflow runs. · Step: Ingest Pipeline Telemetry · Verb: ingest · Realizes: Collect System Telemetry · Oversight: none
- Kind: Code · Note: Fetches table profiles and metadata from Snowflake and BigQuery. · Step: Query Target Warehouses · Verb: query · Realizes: Extract Database Records · Oversight: none
- Kind: Generative · Note: Scores metrics against historical bounds to flag data quality drift. · Step: Detect Data Anomalies · Verb: detect · Realizes: Identify Statistical Anomalies · Oversight: none
- Kind: Code · Note: Halts downstream Airflow orchestration graphs automatically. · Step: Quarantine Anomalous Assets · Verb: isolate · Realizes: Isolate Compromised Systems · Oversight: none
- Kind: Code · Note: Emits quarantine.enforced event for triage agent consumption. · Step: Dispatch Incident Webhook · Verb: dispatch · Realizes: Broadcast System Notifications · Oversight: none
**Optimizes**:
- [Data Quality Incident Mean Time To Detect](/Metrics/Data_Quality_Incident_Mean_Time_To_Detect)
- [Downstream Processing Failure Rate](/Metrics/Downstream_Processing_Failure_Rate)
- [False Positive Anomaly Rate](/Metrics/False_Positive_Anomaly_Rate)
- [Data Pipeline Uptime](/Metrics/Data_Pipeline_Uptime)

## Headless Saas Representative Offer

**Warranty**: Maintains a 99.9% API uptime SLA, offering prorated service credits if automated asset evaluations or webhook triggers exceed latency thresholds.
**Price Band**: ~$0.01 to $0.05 per pipeline asset scan or evaluated monitor, depending on metadata volume
**Pricing Kind**: UsageMeter
**Deliverables**:
- Pipeline scan execution endpoints
- Automated anomaly bounds generation configuration
- Quarantine state management and webhook event streams
- Direct metadata extractors for Snowflake, BigQuery, and dbt
**Delivery Mode**: The offering is provisioned instantly via self-serve API keys and MCP server endpoints, allowing agents to immediately instrument data environments and evaluate pipelines.
**Business Function**: ProvideService
**Agent Checkout Support**:
- agentic-commerce-protocol
- stored-credential

## Headless Saas Crud Surface

**Auth Model**: Service Account
**Endpoints**:
- GET /incidents — list incidents
- POST /incidents — create an incident
- GET /incidents/{id} — fetch one incident
- PATCH /incidents/{id} — update an incident
- GET /incidents/{id}/quarantine-event — fetch the securing quarantine event
- GET /workspaces — list workspaces
- POST /workspaces — create a workspace
- GET /workspaces/{id} — fetch one workspace
- PATCH /workspaces/{id} — update a workspace
- GET /workspaces/{id}/incidents — list incidents belonging to a workspace
- GET /workspaces/{id}/data-assets — list data assets belonging to a workspace
- GET /workspaces/{id}/pipeline-runs — list pipeline runs belonging to a workspace
- GET /data-assets — list data assets
- POST /data-assets — create a data asset
- GET /data-assets/{id} — fetch one data asset
- PATCH /data-assets/{id} — update a data asset
- GET /data-assets/{id}/data-monitors — list data monitors for a data asset
- GET /data-monitors — list data monitors
- POST /data-monitors — create a data monitor
- GET /data-monitors/{id} — fetch one data monitor
- PATCH /data-monitors/{id} — update a data monitor
- GET /data-monitors/{id}/incidents — list incidents triggered by a data monitor
- GET /pipeline-runs — list pipeline runs
- POST /pipeline-runs — create a pipeline run
- GET /pipeline-runs/{id} — fetch one pipeline run
- PATCH /pipeline-runs/{id} — update a pipeline run
- GET /pipeline-runs/{id}/incidents — list incidents detected in a pipeline run
- GET /quarantine-events — list quarantine events
- POST /quarantine-events — create a quarantine event
- GET /quarantine-events/{id} — fetch one quarantine event
- PATCH /quarantine-events/{id} — update a quarantine event
**Multitenancy**: Row-level isolation
**Webhook Events**:
- incident.detected
- incident.status_updated
- data_monitor.bounds_updated
- pipeline_run.status_updated
- quarantine_event.enforced

## Headless Saas Erd

```mermaid
erDiagram
    Incident {
        UUID id PK
        UUID workspaceId FK
        UUID dataMonitorId FK
        UUID pipelineRunId FK
        VARCHAR status
        JSONB rootCauseTrace
        TIMESTAMP createdAt
    }
    Workspace {
        UUID id PK "tenant key"
        VARCHAR name
        VARCHAR warehousePlatform
        TIMESTAMP createdAt
    }
    DataAsset {
        UUID id PK
        UUID workspaceId FK
        VARCHAR fullyQualifiedName
        VARCHAR schemaHash
        TIMESTAMP lastScannedAt
    }
    DataMonitor {
        UUID id PK
        UUID dataAssetId FK
        VARCHAR anomalyType
        JSONB statisticalBounds
        BOOLEAN isEnabled
    }
    PipelineRun {
        UUID id PK
        UUID workspaceId FK
        VARCHAR orchestratorJobId
        VARCHAR executionStatus
        TIMESTAMP startedAt
    }
    QuarantineEvent {
        UUID id PK
        UUID incidentId FK
        VARCHAR quarantineStatus
        TIMESTAMP enforcedAt
    }
    Incident ||--o{ Workspace : "belongs to"
    Incident ||--o{ DataMonitor : "triggered by"
    Incident ||--o{ PipelineRun : "detected in"
    DataAsset ||--o{ Workspace : "belongs to"
    DataMonitor ||--o{ DataAsset : "monitors"
    PipelineRun ||--o{ Workspace : "belongs to"
    QuarantineEvent ||--|| Incident : "secures"
```

## Neighborhood

### Who offers this

- [Monte Carlo](/Startups/Monte_Carlo) — offers · Startups
- [Anomalyleap](/Startups/Anomalyleap) — offers · Startups

### Optimizes

- [Data Pipeline Uptime](/Metrics/Data_Pipeline_Uptime) — optimizes · Metrics
- [Data Quality Incident Mean Time To Detect](/Metrics/Data_Quality_Incident_Mean_Time_To_Detect) — optimizes · Metrics
- [Downstream Processing Failure Rate](/Metrics/Downstream_Processing_Failure_Rate) — optimizes · Metrics
- [False Positive Anomaly Rate](/Metrics/False_Positive_Anomaly_Rate) — optimizes · Metrics

### What it uses

- [BigQuery](/Products/BigQuery) — uses · Products
- [dbt](/Products/dbt) — uses · Products
- [Snowflake](/Software/Snowflake) — uses · Software
- [Apache Airflow](/Products/Apache_Airflow) — uses · Products

### Who consumes this

- [Analytics Engineering Agent](/Agents/Analytics_Engineering_Agent) — consumed by · Agents
- [Data Quality Agent](/Agents/Data_Quality_Agent) — consumed by · Agents
- [Pipeline Triage Agent](/Agents/Pipeline_Triage_Agent) — consumed by · Agents

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