README.md

---
license: apache-2.0
pretty_name: "ops-lite: Curated RCA Evaluation Set for Microservice Systems"
size_categories:
  - n<1K
task_categories:
  - graph-ml
  - tabular-classification
  - other
task_ids:
  - multi-class-classification
language:
  - en
tags:
  - root-cause-analysis
  - rca
  - microservices
  - observability
  - aiops
  - chaos-engineering
  - causal-graph
  - benchmark
annotations_creators:
  - machine-generated
language_creators:
  - machine-generated
source_datasets:
  - original
configs:
  - config_name: default
    data_files:
      - split: test
        path: "manifest.jsonl"
---

# ops-lite

A curated 500-case root-cause-analysis (RCA) evaluation set for
microservice systems, with manifest-driven causal-graph ground truth.

Each case bundles:

- a chaos-injection ground truth (`injection.json`)
- a causal service graph derived from the injection's fault contract
  (`causal_graph.json`)
- the runtime environment snapshot (`env.json`, `result.json`,
  `label.txt`)
- 12 parquet metric tables per case, split into the abnormal window
  (during fault) and the normal window (baseline)

The corpus spans three open-source microservice testbeds:

| system | n | description |
|---|---:|---|
| `ts` (Train-Ticket)        | 320 | Java/Spring Cloud microservice system, 44 application services |
| `hs` (Hotel Reservation / DeathStarBench) | 142 | Go/gRPC microservice system, 9 application services |
| `otel-demo`                |  38 | OpenTelemetry Demo e-commerce app, 15 polyglot application services |

## Intended use

Benchmarking RCA algorithms on microservice fault propagation. Each case
provides the ground-truth root-cause service(s) and a manifest-derived
causal graph against which an algorithm's predicted ranking or path can
be scored.

## Pipeline

1. **Generation** — chaos faults are injected and observed by AegisLab,
   an open-source RCA benchmarking platform. A detector confirms each
   case is observable end-to-end before it enters the candidate pool.
2. **Annotation** — for every observable case, a manifest-driven causal
   graph reasoner (rcabench-platform v3 `internal/reasoning`)
   enumerates the fault propagation layer-by-layer from the registered
   fault manifest, producing the `causal_graph.json` ground truth.
3. **Curation** — a 1464-case raw pool is reduced to 500 via a greedy
   selector with hard filters (cyclic graphs, lp ≤ 1, frontend-only
   injections) and soft caps on system / chaos-family / root-service.

This repo card summarizes the released artifact itself. The full
generation and selection pipeline will be documented in the associated
paper / artifact release.

## Data layout

```
ops-lite/
├── manifest.jsonl            # 500 lines, one JSON record per case
├── README.md
├── croissant.json            # core Croissant + RAI fields
└── cases/
    └── <case-name>/
        ├── injection.json
        ├── causal_graph.json
        ├── env.json
        ├── result.json
        ├── label.txt
        └── *.parquet         # abnormal_* + normal_*
```

`manifest.jsonl` schema:

```json
{
  "name": "ts0-ts-order-service-exception-l2bqm5",
  "system": "ts|hs|otel-demo",
  "longest_path": 7,
  "n_svc": 13,
  "n_edge": 21,
  "n_alarm_svc": 2,
  "root_services": ["ts-order-service"],
  "chaos_family": "JVM*|HTTP*|Network*|Pod*|*Stress|DNS|Time|hybrid_clean|hybrid_kill",
  "primary_kind": "<chaos_type or 'hybrid'>",
  "subtypes": ["..."],
  "hybrid": false,
  "has_kill_leg": false
}
```

## Composition

| metric | value |
|---|---:|
| total cases | 500 |
| mean `longest_path` | 3.18 |
| mean `n_edge` | 4.06 |
| mean `n_svc` | 3.97 |
| chaos families | 8 |
| systems | 3 |

## License

Apache-2.0. The underlying microservice testbeds (Train-Ticket,
Hotel Reservation / DeathStarBench, OpenTelemetry Demo) retain their own
upstream licenses.

## Citation

A formal citation will be added on publication.