Run
The run stream processor pipeline executes apps that report on, receive, and optimize events at the edge and in the cloud. To run this pipeline locally, use the @apps/dev engine pipeline; the MCP drives it for you.
Workflow
This pipeline chains together the following units:
graph LR
A["<div style='font-size: 16px;'>📚 Symbols</div><div style='font-size: 14px;'>Load Libraries</div>"] --> B["<div style='font-size: 16px;'>📥 Inputs</div><div style='font-size: 14px;'>Read Events</div>"]
B --> C["<div style='font-size: 16px;'>🦋 Transform</div><div style='font-size: 14px;'>→ TenXObjects</div>"]
C --> D["<div style='font-size: 16px;'>∑ Aggregate</div><div style='font-size: 14px;'>→ TenXSummaries</div>"]
D --> E["<div style='font-size: 16px;'>âš¡ Receive</div><div style='font-size: 14px;'>Apply Policies</div>"]
E --> F["<div style='font-size: 16px;'>📤 Output</div><div style='font-size: 14px;'>Send Results</div>"]
classDef symbols fill:#9333ea88,stroke:#7c3aed,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef inputs fill:#2563eb88,stroke:#1d4ed8,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef transform fill:#059669,stroke:#047857,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef aggregate fill:#ea580c88,stroke:#c2410c,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef receive fill:#dc262688,stroke:#b91c1c,color:#ffffff,stroke-width:2px,rx:8,ry:8
classDef output fill:#16a34a88,stroke:#15803d,color:#ffffff,stroke-width:2px,rx:8,ry:8
class A symbols
class B inputs
class C transform
class D aggregate
class E receive
class F output
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Symbols
Load symbol library files produced by the compile pipeline.
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Inputs
Input log/trace events from log forwarders, analyzers, and object storage.
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Transform
Transform input events into well-defined, typed TenXObjects.
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Aggregate
Aggregate TenXObjects into summaries to publish to metrics outputs.
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Receive
Receive which TenXObjects to output based on local and environment-wide policies
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Output
Output TenXObject and TenXSummaries to event/metric output destinations.
This pipeline is defined in run/pipeline.yaml.