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  1. .gitattributes +11 -0
  2. README.md +137 -0
  3. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/.done +0 -0
  4. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/.finished +0 -0
  5. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/causal_graph.json +0 -0
  6. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/env.json +8 -0
  7. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/injection.json +111 -0
  8. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/label.txt +1 -0
  9. cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/result.json +0 -0
  10. cases/hs10-rate-pod-failure-6xx86z/causal_graph.json +130 -0
  11. cases/hs10-rate-pod-failure-6xx86z/env.json +8 -0
  12. cases/hs8-user-pod-failure-q2q5tv/.done +0 -0
  13. cases/hs8-user-pod-failure-q2q5tv/.finished +0 -0
  14. cases/hs8-user-pod-failure-q2q5tv/causal_graph.json +863 -0
  15. cases/hs8-user-pod-failure-q2q5tv/env.json +8 -0
  16. cases/hs8-user-pod-failure-q2q5tv/injection.json +43 -0
  17. cases/hs8-user-pod-failure-q2q5tv/label.txt +1 -0
  18. cases/hs8-user-pod-failure-q2q5tv/result.json +0 -0
  19. cases/ts1-ts-route-service-exception-n729sm/.finished +0 -0
  20. cases/ts1-ts-route-service-exception-n729sm/causal_graph.json +958 -0
  21. cases/ts1-ts-route-service-exception-n729sm/env.json +8 -0
  22. cases/ts1-ts-route-service-exception-n729sm/injection.json +33 -0
  23. cases/ts1-ts-route-service-exception-n729sm/label.txt +1 -0
  24. cases/ts1-ts-route-service-exception-n729sm/result.json +0 -0
  25. cases/ts1-ts-station-food-service-stress-rlvxhc/.finished +0 -0
  26. cases/ts1-ts-station-food-service-stress-rlvxhc/injection.json +35 -0
  27. cases/ts1-ts-station-food-service-stress-rlvxhc/result.json +0 -0
  28. cases/ts1-ts-train-service-pod-failure-5qwqdz/.finished +0 -0
  29. cases/ts1-ts-train-service-pod-failure-5qwqdz/causal_graph.json +1498 -0
  30. cases/ts1-ts-train-service-pod-failure-5qwqdz/env.json +8 -0
  31. cases/ts1-ts-train-service-pod-failure-5qwqdz/injection.json +31 -0
  32. cases/ts1-ts-train-service-pod-failure-5qwqdz/label.txt +1 -0
  33. cases/ts1-ts-train-service-pod-failure-5qwqdz/result.json +0 -0
  34. cases/ts2-mysql-delay-d427wn/injection.json +44 -0
  35. cases/ts2-mysql-delay-d427wn/result.json +0 -0
  36. cases/ts3-ts-order-service-delay-9trpt4/.finished +0 -0
  37. cases/ts3-ts-order-service-delay-9trpt4/causal_graph.json +1760 -0
  38. cases/ts3-ts-order-service-delay-9trpt4/env.json +8 -0
  39. cases/ts3-ts-order-service-delay-9trpt4/injection.json +39 -0
  40. cases/ts3-ts-order-service-delay-9trpt4/label.txt +1 -0
  41. cases/ts3-ts-order-service-delay-9trpt4/result.json +0 -0
  42. cases/ts7-ts-travel-service-response-delay-t48wrc/.finished +0 -0
  43. cases/ts7-ts-travel-service-response-delay-t48wrc/causal_graph.json +728 -0
  44. cases/ts7-ts-travel-service-response-delay-t48wrc/env.json +8 -0
  45. cases/ts7-ts-travel-service-response-delay-t48wrc/injection.json +44 -0
  46. cases/ts7-ts-travel-service-response-delay-t48wrc/label.txt +1 -0
  47. cases/ts7-ts-travel-service-response-delay-t48wrc/result.json +0 -0
  48. croissant.json +307 -0
  49. manifest.jsonl +0 -0
  50. update_croissant.py +101 -0
.gitattributes CHANGED
@@ -58,3 +58,14 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ cases/batch-01KQKFP1BN9YPB54XYDNMF6JCM/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/batch-01KQKFRKAJZ8DVJZSHTAEGNEN9/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/batch-01KQKFRN92GEVSF4RKQ9STAHCS/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/batch-01KQKMQR349X061866XW7WW0JK/result.json filter=lfs diff=lfs merge=lfs -text
65
+ cases/batch-01KQKMRHFSXYCTWWH8B2T0YJR2/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/hs0-frontend-partition-j6lxxv/result.json filter=lfs diff=lfs merge=lfs -text
67
+ cases/ts1-ts-route-service-latency-vhk7dz/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/ts1-ts-travel-plan-service-return-kp5bqw/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/ts3-ts-inside-payment-service-return-vds5h6/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/ts4-ts-train-service-latency-5gvbsq/result.json filter=lfs diff=lfs merge=lfs -text
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+ cases/ts4-ts-travel-service-return-j872pp/result.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,137 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ pretty_name: "ops-lite: Curated RCA Evaluation Set for Microservice Systems"
4
+ size_categories:
5
+ - n<1K
6
+ task_categories:
7
+ - graph-ml
8
+ - tabular-classification
9
+ - other
10
+ task_ids:
11
+ - multi-class-classification
12
+ language:
13
+ - en
14
+ tags:
15
+ - root-cause-analysis
16
+ - rca
17
+ - microservices
18
+ - observability
19
+ - aiops
20
+ - chaos-engineering
21
+ - causal-graph
22
+ - benchmark
23
+ annotations_creators:
24
+ - machine-generated
25
+ language_creators:
26
+ - machine-generated
27
+ source_datasets:
28
+ - original
29
+ configs:
30
+ - config_name: default
31
+ data_files:
32
+ - split: test
33
+ path: "manifest.jsonl"
34
+ ---
35
+
36
+ # ops-lite
37
+
38
+ A curated 500-case root-cause-analysis (RCA) evaluation set for
39
+ microservice systems, with manifest-driven causal-graph ground truth.
40
+
41
+ Each case bundles:
42
+
43
+ - a chaos-injection ground truth (`injection.json`)
44
+ - a causal service graph derived from the injection's fault contract
45
+ (`causal_graph.json`)
46
+ - the runtime environment snapshot (`env.json`, `result.json`,
47
+ `label.txt`)
48
+ - 12 parquet metric tables per case, split into the abnormal window
49
+ (during fault) and the normal window (baseline)
50
+
51
+ The corpus spans three open-source microservice testbeds:
52
+
53
+ | system | n | description |
54
+ |---|---:|---|
55
+ | `ts` (Train-Ticket) | 320 | Java/Spring Cloud microservice system, 44 application services |
56
+ | `hs` (Hotel Reservation / DeathStarBench) | 142 | Go/gRPC microservice system, 9 application services |
57
+ | `otel-demo` | 38 | OpenTelemetry Demo e-commerce app, 15 polyglot application services |
58
+
59
+ ## Intended use
60
+
61
+ Benchmarking RCA algorithms on microservice fault propagation. Each case
62
+ provides the ground-truth root-cause service(s) and a manifest-derived
63
+ causal graph against which an algorithm's predicted ranking or path can
64
+ be scored.
65
+
66
+ ## Pipeline
67
+
68
+ 1. **Generation** — chaos faults are injected and observed by AegisLab,
69
+ an open-source RCA benchmarking platform. A detector confirms each
70
+ case is observable end-to-end before it enters the candidate pool.
71
+ 2. **Annotation** — for every observable case, a manifest-driven causal
72
+ graph reasoner (rcabench-platform v3 `internal/reasoning`)
73
+ enumerates the fault propagation layer-by-layer from the registered
74
+ fault manifest, producing the `causal_graph.json` ground truth.
75
+ 3. **Curation** — a 1464-case raw pool is reduced to 500 via a greedy
76
+ selector with hard filters (cyclic graphs, lp ≤ 1, frontend-only
77
+ injections) and soft caps on system / chaos-family / root-service.
78
+
79
+ See `README.md` (long form) inside the repo for the full selection
80
+ recipe and reproducibility commands.
81
+
82
+ ## Data layout
83
+
84
+ ```
85
+ ops-lite/
86
+ ├── manifest.jsonl # 500 lines, one JSON record per case
87
+ ├── README.md
88
+ ├── croissant.json # core Croissant + RAI fields
89
+ └── cases/
90
+ └── <case-name>/
91
+ ├── injection.json
92
+ ├── causal_graph.json
93
+ ├── env.json
94
+ ├── result.json
95
+ ├── label.txt
96
+ └── *.parquet # abnormal_* + normal_*
97
+ ```
98
+
99
+ `manifest.jsonl` schema:
100
+
101
+ ```json
102
+ {
103
+ "name": "ts0-ts-order-service-exception-l2bqm5",
104
+ "system": "ts|hs|otel-demo",
105
+ "longest_path": 7,
106
+ "n_svc": 13,
107
+ "n_edge": 21,
108
+ "n_alarm_svc": 2,
109
+ "root_services": ["ts-order-service"],
110
+ "chaos_family": "JVM*|HTTP*|Network*|Pod*|*Stress|DNS|Time|hybrid_clean|hybrid_kill",
111
+ "primary_kind": "<chaos_type or 'hybrid'>",
112
+ "subtypes": ["..."],
113
+ "hybrid": false,
114
+ "has_kill_leg": false
115
+ }
116
+ ```
117
+
118
+ ## Composition
119
+
120
+ | metric | value |
121
+ |---|---:|
122
+ | total cases | 500 |
123
+ | mean `longest_path` | 3.18 |
124
+ | mean `n_edge` | 4.06 |
125
+ | mean `n_svc` | 3.97 |
126
+ | chaos families | 8 |
127
+ | systems | 3 |
128
+
129
+ ## License
130
+
131
+ Apache-2.0. The underlying microservice testbeds (Train-Ticket,
132
+ Hotel Reservation / DeathStarBench, OpenTelemetry Demo) retain their own
133
+ upstream licenses.
134
+
135
+ ## Citation
136
+
137
+ A formal citation will be added on publication.
cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/.done ADDED
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cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/.finished ADDED
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cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/causal_graph.json ADDED
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cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/env.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
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+ "NAMESPACE": "ts5",
3
+ "DB_TIMEZONE": "UTC",
4
+ "NORMAL_START": "1777682622",
5
+ "NORMAL_END": "1777682922",
6
+ "ABNORMAL_START": "1777682922",
7
+ "ABNORMAL_END": "1777683221"
8
+ }
cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/injection.json ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "id": 2590,
3
+ "name": "batch-01KQK2HEA575BTKM4PN7J5RW6T",
4
+ "fault_type": "hybrid",
5
+ "category": "ts",
6
+ "pre_duration": 5,
7
+ "start_time": "2026-05-02T08:48:42+08:00",
8
+ "end_time": "2026-05-02T08:53:41+08:00",
9
+ "state": "inject_success",
10
+ "status": "enabled",
11
+ "benchmark_id": 108,
12
+ "benchmark_name": "clickhouse",
13
+ "pedestal_id": 149,
14
+ "pedestal_name": "ts",
15
+ "created_at": "2026-05-02T08:48:41.859+08:00",
16
+ "updated_at": "2026-05-02T08:53:42.216+08:00",
17
+ "engine_config_summary": [
18
+ {
19
+ "app": "ts-basic-service",
20
+ "chaos_type": "JVMRuntimeMutator",
21
+ "class": "fdse.microservice.controller.BasicController",
22
+ "duration": 5,
23
+ "method": "queryForTravels",
24
+ "mutator_config": "constant:\"/basic/travels\":\"mutated_/basic/travels\"",
25
+ "namespace": "ts5",
26
+ "system": "ts",
27
+ "system_type": "ts",
28
+ "time_offset": 0
29
+ },
30
+ {
31
+ "app": "ts-station-service",
32
+ "chaos_type": "NetworkPartition",
33
+ "direction": "to",
34
+ "duration": 5,
35
+ "namespace": "ts5",
36
+ "system": "ts",
37
+ "system_type": "ts",
38
+ "target_service": "mysql",
39
+ "time_offset": 0
40
+ }
41
+ ],
42
+ "task_id": "2c6e8014-3753-4e7f-8f4f-bf1c58009073",
43
+ "trace_id": "d81e297b-fecb-40dd-8539-eb112a00a9c5",
44
+ "source": "injection",
45
+ "description": "Fault batch for task 2c6e8014-3753-4e7f-8f4f-bf1c58009073 (2 faults)",
46
+ "engine_config": [
47
+ {
48
+ "app": "ts-basic-service",
49
+ "chaos_type": "JVMRuntimeMutator",
50
+ "class": "fdse.microservice.controller.BasicController",
51
+ "duration": 5,
52
+ "method": "queryForTravels",
53
+ "mutator_config": "constant:\"/basic/travels\":\"mutated_/basic/travels\"",
54
+ "namespace": "ts5",
55
+ "system": "ts",
56
+ "system_type": "ts",
57
+ "time_offset": 0
58
+ },
59
+ {
60
+ "app": "ts-station-service",
61
+ "chaos_type": "NetworkPartition",
62
+ "direction": "to",
63
+ "duration": 5,
64
+ "namespace": "ts5",
65
+ "system": "ts",
66
+ "system_type": "ts",
67
+ "target_service": "mysql",
68
+ "time_offset": 0
69
+ }
70
+ ],
71
+ "ground_truth": [
72
+ {
73
+ "service": [
74
+ "ts-basic-service"
75
+ ],
76
+ "pod": [
77
+ "ts-basic-service-67858c87fb-bnlfg"
78
+ ],
79
+ "container": [
80
+ "ts-basic-service"
81
+ ],
82
+ "function": [
83
+ "fdse.microservice.controller.BasicController.queryForTravels"
84
+ ]
85
+ },
86
+ {
87
+ "service": [
88
+ "ts-station-service",
89
+ "mysql"
90
+ ],
91
+ "pod": [
92
+ "mysql-0",
93
+ "ts-station-service-b654d6866-hg4bd"
94
+ ],
95
+ "container": [
96
+ "mysql",
97
+ "ts-station-service"
98
+ ],
99
+ "span": [
100
+ "ALTER table ts",
101
+ "CREATE table ts",
102
+ "INSERT station",
103
+ "INSERT ts.station",
104
+ "SELECT ts",
105
+ "SELECT ts.station",
106
+ "SELECT ts.ts"
107
+ ]
108
+ }
109
+ ],
110
+ "groundtruth_source": "auto"
111
+ }
cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/label.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ attributed
cases/batch-01KQK2HEA575BTKM4PN7J5RW6T/result.json ADDED
The diff for this file is too large to render. See raw diff
 
cases/hs10-rate-pod-failure-6xx86z/causal_graph.json ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "nodes": [
3
+ {
4
+ "timestamp": 1777717656,
5
+ "component": "service|rate",
6
+ "state": [
7
+ "unavailable"
8
+ ]
9
+ },
10
+ {
11
+ "timestamp": 1777717656,
12
+ "component": "span|rate::rate.Rate/GetRates",
13
+ "state": [
14
+ "missing"
15
+ ]
16
+ },
17
+ {
18
+ "timestamp": 1777717656,
19
+ "component": "span|rate::memcached_get_multi_rate",
20
+ "state": [
21
+ "missing"
22
+ ]
23
+ },
24
+ {
25
+ "timestamp": 1777717670,
26
+ "component": "span|search::rate.Rate/GetRates",
27
+ "state": [
28
+ "missing",
29
+ "healthy"
30
+ ]
31
+ },
32
+ {
33
+ "timestamp": 1777717670,
34
+ "component": "span|search::search.Search/Nearby",
35
+ "state": [
36
+ "missing",
37
+ "healthy"
38
+ ]
39
+ },
40
+ {
41
+ "timestamp": 1777717716,
42
+ "component": "span|frontend::search.Search/Nearby",
43
+ "state": [
44
+ "missing",
45
+ "healthy"
46
+ ]
47
+ },
48
+ {
49
+ "timestamp": 1777717716,
50
+ "component": "span|frontend::HTTP /hotels",
51
+ "state": [
52
+ "erroring",
53
+ "missing"
54
+ ]
55
+ }
56
+ ],
57
+ "edges": [
58
+ {
59
+ "source": "span|search::rate.Rate/GetRates",
60
+ "target": "span|search::search.Search/Nearby"
61
+ },
62
+ {
63
+ "source": "span|search::search.Search/Nearby",
64
+ "target": "span|frontend::search.Search/Nearby"
65
+ },
66
+ {
67
+ "source": "span|rate::memcached_get_multi_rate",
68
+ "target": "span|rate::rate.Rate/GetRates"
69
+ },
70
+ {
71
+ "source": "service|rate",
72
+ "target": "span|rate::rate.Rate/GetRates"
73
+ },
74
+ {
75
+ "source": "span|rate::rate.Rate/GetRates",
76
+ "target": "span|search::rate.Rate/GetRates"
77
+ },
78
+ {
79
+ "source": "span|frontend::search.Search/Nearby",
80
+ "target": "span|frontend::HTTP /hotels"
81
+ },
82
+ {
83
+ "source": "service|rate",
84
+ "target": "span|rate::memcached_get_multi_rate"
85
+ }
86
+ ],
87
+ "root_causes": [
88
+ {
89
+ "timestamp": null,
90
+ "component": "service|rate",
91
+ "state": [
92
+ "unknown"
93
+ ]
94
+ }
95
+ ],
96
+ "alarm_nodes": [
97
+ {
98
+ "timestamp": 1777717656,
99
+ "component": "span|rate::rate.Rate/GetRates",
100
+ "state": [
101
+ "missing"
102
+ ]
103
+ },
104
+ {
105
+ "timestamp": 1777717670,
106
+ "component": "span|search::search.Search/Nearby",
107
+ "state": [
108
+ "missing",
109
+ "healthy"
110
+ ]
111
+ },
112
+ {
113
+ "timestamp": 1777717716,
114
+ "component": "span|frontend::HTTP /hotels",
115
+ "state": [
116
+ "erroring",
117
+ "missing"
118
+ ]
119
+ }
120
+ ],
121
+ "component_to_service": {
122
+ "service|rate": "rate",
123
+ "span|rate::rate.Rate/GetRates": "rate",
124
+ "span|rate::memcached_get_multi_rate": "rate",
125
+ "span|search::rate.Rate/GetRates": "search",
126
+ "span|search::search.Search/Nearby": "search",
127
+ "span|frontend::search.Search/Nearby": "frontend",
128
+ "span|frontend::HTTP /hotels": "frontend"
129
+ }
130
+ }
cases/hs10-rate-pod-failure-6xx86z/env.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "NAMESPACE": "hs10",
3
+ "DB_TIMEZONE": "UTC",
4
+ "NORMAL_START": "1777717356",
5
+ "NORMAL_END": "1777717656",
6
+ "ABNORMAL_START": "1777717656",
7
+ "ABNORMAL_END": "1777717956"
8
+ }
cases/hs8-user-pod-failure-q2q5tv/.done ADDED
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cases/hs8-user-pod-failure-q2q5tv/.finished ADDED
File without changes
cases/hs8-user-pod-failure-q2q5tv/causal_graph.json ADDED
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+ "endDate": "2026-05-03"
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+ },
293
+ "rai:dataAnnotationProtocol": "Ground-truth causal graphs are produced automatically by a manifest-driven fault-propagation reasoner (rcabench-platform v3, internal/reasoning). For each case the reasoner reads the chaos injection's fault contract from a registered fault manifest and enumerates layer-by-layer the services that the contract says can be affected, terminating when no further nodes match the contract's entry signatures. The resulting service graph is what the fault contract itself prescribes as propagation - it is not a post-filtered exhaustive walk. Cases whose resulting graph is cyclic, has longest_path <= 1, or whose injection target is a frontend / load-generator service are dropped. The kept pool is reduced to 500 by a greedy selector with hard caps on system, chaos family, and root service.",
294
+ "rai:dataAnnotationPlatform": "rcabench-platform v3 internal/reasoning module (manifest-driven layer expansion); curation script in the AegisLab repository.",
295
+ "rai:dataAnnotationAnalysis": "Annotation is fully algorithmic and deterministic given the fault manifest, so per-annotator agreement is not applicable. Quality is governed by the manifest itself: every chaos type used in this corpus has an entry signature and propagation rule registered in rcabench-platform's manifest, and the graph for any case can be regenerated from the injection.json and the manifest version. Aggregate graph-shape statistics for the released set are: mean longest_path 3.18, mean n_edge 4.06, mean n_svc 3.97.",
296
+ "rai:annotationsPerItem": "1 (deterministic, manifest-derived).",
297
+ "rai:annotatorDemographics": "Not applicable - annotations are produced by software, not humans.",
298
+ "rai:machineAnnotationTools": [
299
+ "rcabench-platform v3 internal/reasoning (manifest-driven causal-graph reasoner)"
300
+ ],
301
+ "rai:personalSensitiveInformation": "None. The dataset contains only synthetic load and fault telemetry from open-source microservice testbeds running in isolated lab clusters. No real user data, PII, payment data, or production traffic is present. Service / endpoint names come from the public Train-Ticket, Hotel Reservation / DeathStarBench, and OpenTelemetry Demo projects.",
302
+ "rai:dataBiases": "The corpus is biased toward fault types that the AegisLab detector can confirm end-to-end (predominantly latency / error-rate / resource-stress / pod-availability faults). Topology-only or silent-data-corruption faults are under-represented. System coverage is also uneven: ts (Train-Ticket) is over-represented (320 / 500) compared to hs (142) and otel-demo (38), reflecting both the richer fault surface of the Train-Ticket testbed and the manifest reasoner being stricter about JVM / *Stress entry signatures, which disproportionately drops otel-demo cases. Hybrid (multi-leg) cases account for 43 % of the corpus, which is higher than typical production incident distributions.",
303
+ "rai:dataUseCases": "Recommended uses: (1) benchmarking microservice RCA algorithms - root-cause ranking, propagation-path inference, alarm clustering, anomaly detection on service metrics; (2) ablation studies on graph-shape difficulty (longest_path, n_edge); (3) supervision data for graph-structured RCA models. Not recommended: (1) training or evaluating production-incident triage on real customer traffic - the synthetic load and lab setting do not reflect production tail behavior; (2) general-purpose anomaly detection unrelated to microservice fault propagation; (3) any task requiring real user, employee, or business data.",
304
+ "rai:dataLimitations": "Each case captures a single fault window in an isolated lab cluster, so the dataset cannot exercise (a) concurrent independent faults, (b) noisy-neighbour effects from co-tenant workloads, (c) long-running gradual degradations beyond the recording window, or (d) fault propagation through queues / async pipelines that the underlying testbeds do not model. Causal graphs are only as accurate as the manifest's propagation rules - faults whose real-world effect exceeds the manifest's declared contract will have ground-truth graphs that under-represent the actual blast radius. The 500-case sample is intentionally small for fast benchmark turnaround; statistical claims based on this corpus alone should be treated as evaluation evidence, not population estimates.",
305
+ "rai:dataSocialImpact": "The dataset is intended to advance reproducible RCA research for microservice systems. Risks are low: there is no human or operational data. Possible indirect risk: an RCA algorithm tuned only on this benchmark may transfer poorly to production fault distributions, potentially giving operators false confidence. Users are encouraged to report any observed gaps between benchmark performance and production performance via the dataset's HF discussion page.",
306
+ "rai:dataReleaseMaintenancePlan": "Versioned releases on Hugging Face under anon-ops/ops-lite. The pipeline that produced this release (chaos injection in AegisLab + manifest-driven reasoner in rcabench-platform v3) is open-source, so any reissue can be reproduced from the same fault manifest commit. We plan to refresh the corpus when the fault manifest gains new chaos families. No deprecation timeline is set; older versions remain accessible via repo history."
307
+ }
manifest.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
update_croissant.py ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ Refresh ops-lite/croissant.json after data files are uploaded.
3
+
4
+ Usage:
5
+ HF_TOKEN=hf_xxx python update_croissant.py [--repo anon-ops/ops-lite]
6
+
7
+ What it does:
8
+ 1. Pulls the auto-generated Croissant from
9
+ https://huggingface.co/api/datasets/<repo>/croissant
10
+ 2. Loads the hand-authored croissant.json from the repo
11
+ (which carries the RAI fields and the manual recordSet schema).
12
+ 3. Splices auto-Croissant's `distribution` (with real sha256 hashes
13
+ and the actual file list) into the hand-authored skeleton, so we
14
+ keep the rich descriptions + RAI fields but get accurate hashes.
15
+ 4. Re-uploads the merged file.
16
+
17
+ Run after every data push that changes file content or count.
18
+ """
19
+ from __future__ import annotations
20
+
21
+ import argparse
22
+ import json
23
+ import os
24
+ import sys
25
+ import tempfile
26
+ from pathlib import Path
27
+
28
+ import httpx
29
+ from huggingface_hub import HfApi, hf_hub_download
30
+
31
+ DEFAULT_REPO = "anon-ops/ops-lite"
32
+
33
+
34
+ def fetch_auto_croissant(repo: str) -> dict:
35
+ url = f"https://huggingface.co/api/datasets/{repo}/croissant"
36
+ r = httpx.get(url, timeout=30, follow_redirects=True)
37
+ r.raise_for_status()
38
+ return r.json()
39
+
40
+
41
+ def load_repo_croissant(repo: str, token: str) -> dict:
42
+ path = hf_hub_download(
43
+ repo_id=repo, repo_type="dataset",
44
+ filename="croissant.json", token=token,
45
+ )
46
+ return json.loads(Path(path).read_text())
47
+
48
+
49
+ def splice_distribution(manual: dict, auto: dict) -> dict:
50
+ """Replace manual.distribution with auto's, carrying over manual descriptions where ids match."""
51
+ manual_by_id = {d.get("@id") or d.get("name"): d for d in manual.get("distribution", [])}
52
+ spliced = []
53
+ for d in auto.get("distribution", []):
54
+ key = d.get("@id") or d.get("name")
55
+ if key in manual_by_id and "description" in manual_by_id[key]:
56
+ d.setdefault("description", manual_by_id[key]["description"])
57
+ spliced.append(d)
58
+ if spliced:
59
+ manual["distribution"] = spliced
60
+ return manual
61
+
62
+
63
+ def main() -> int:
64
+ ap = argparse.ArgumentParser()
65
+ ap.add_argument("--repo", default=DEFAULT_REPO)
66
+ args = ap.parse_args()
67
+
68
+ token = os.environ.get("HF_TOKEN")
69
+ if not token:
70
+ print("ERROR: HF_TOKEN env var not set", file=sys.stderr)
71
+ return 2
72
+
73
+ print(f"[1/4] fetching auto-Croissant for {args.repo} ...")
74
+ auto = fetch_auto_croissant(args.repo)
75
+
76
+ print(f"[2/4] downloading hand-authored croissant.json ...")
77
+ manual = load_repo_croissant(args.repo, token)
78
+
79
+ print(f"[3/4] splicing distribution ({len(auto.get('distribution', []))} items) ...")
80
+ merged = splice_distribution(manual, auto)
81
+
82
+ api = HfApi()
83
+ with tempfile.NamedTemporaryFile("w", suffix=".json", delete=False) as f:
84
+ json.dump(merged, f, indent=2, ensure_ascii=False)
85
+ out = f.name
86
+
87
+ print(f"[4/4] uploading merged croissant.json ...")
88
+ api.upload_file(
89
+ path_or_fileobj=out,
90
+ path_in_repo="croissant.json",
91
+ repo_id=args.repo,
92
+ repo_type="dataset",
93
+ commit_message="Refresh Croissant (core from auto + manual RAI)",
94
+ token=token,
95
+ )
96
+ print("done.")
97
+ return 0
98
+
99
+
100
+ if __name__ == "__main__":
101
+ raise SystemExit(main())