shove 0.11.2

Async tasks via pubsub on steroids. Comes with built-in support for complex queue configurations, audit logs, autoscaling consumer groups and more.
Documentation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
use std::collections::HashMap;
use std::sync::{Arc, Mutex as StdMutex};
use std::time::Duration;

use rdkafka::TopicPartitionList;
use rdkafka::consumer::{BaseConsumer, Consumer as RdkafkaConsumer};
use tokio::sync::Mutex;
use tracing::{debug, info, warn};

use crate::ShoveError;
use crate::autoscaler::{
    Autoscaler, AutoscalerBackend, AutoscalerConfig, ScalingDecision, ScalingMetrics, Stabilized,
    ThresholdStrategy,
};
use crate::error::Result;

use super::client::KafkaClient;
use super::consumer_group::KafkaConsumerGroupRegistry;

/// Queue statistics fetched from Kafka consumer lag.
#[derive(Debug, Clone, Default)]
pub struct KafkaQueueStats {
    pub messages_pending: u64,
    pub messages_in_flight: u64,
}

/// Abstraction over Kafka consumer lag for fetching queue stats.
pub trait KafkaQueueStatsProvider: Send + Sync {
    /// Fetch lag statistics for `queue` under the given `group_id`.
    ///
    /// Both parameters are required: `queue` names the topic, `group_id` is the
    /// Kafka consumer group whose committed offsets are queried. Callers must pass
    /// the actual group ID (e.g. `"{queue}-fifo"` for FIFO groups) rather than
    /// re-deriving it from the queue name — re-derivation is what caused the bug
    /// fixed by arch-K-1.
    fn get_queue_stats(
        &self,
        queue: &str,
        group_id: &str,
    ) -> impl Future<Output = Result<KafkaQueueStats>> + Send;
}

/// Default stats provider that queries Kafka consumer lag.
///
/// perf-K-10: caches one BaseConsumer per group_id so each autoscaler poll
/// reuses the connection + metadata cache instead of doing a fresh broker
/// handshake. Typical deployments have one or two distinct group_ids
/// (`{queue}-consumer` for standard groups, `{queue}-fifo` for FIFO).
pub struct KafkaLagStatsProvider {
    client: KafkaClient,
    consumers: StdMutex<HashMap<String, Arc<BaseConsumer>>>,
}

impl KafkaLagStatsProvider {
    pub fn new(client: KafkaClient) -> Self {
        Self {
            client,
            consumers: StdMutex::new(HashMap::new()),
        }
    }

    fn get_or_create_consumer(&self, group_id: &str) -> Result<Arc<BaseConsumer>> {
        let mut guard = self
            .consumers
            .lock()
            .map_err(|_| ShoveError::Topology("stats consumer cache poisoned".into()))?;
        if let Some(c) = guard.get(group_id) {
            return Ok(Arc::clone(c));
        }
        let consumer: BaseConsumer = self
            .client
            .base_config()
            .set("group.id", group_id)
            .create()
            .map_err(|e| ShoveError::Topology(format!("failed to create stats consumer: {e}")))?;
        let arc = Arc::new(consumer);
        guard.insert(group_id.to_string(), Arc::clone(&arc));
        Ok(arc)
    }
}

impl KafkaQueueStatsProvider for KafkaLagStatsProvider {
    async fn get_queue_stats(&self, queue: &str, group_id: &str) -> Result<KafkaQueueStats> {
        // perf-K-10: reuse a cached BaseConsumer keyed by group_id.
        let consumer = self.get_or_create_consumer(group_id)?;
        let queue = queue.to_string();

        // Fetch metadata to enumerate partitions.
        let partitions: Vec<i32> = {
            let c = Arc::clone(&consumer);
            let q = queue.clone();
            tokio::task::spawn_blocking(move || -> Result<Vec<i32>> {
                let metadata = c
                    .fetch_metadata(Some(&q), Duration::from_secs(5))
                    .map_err(|e| {
                        ShoveError::Connection(format!("failed to fetch metadata for {q}: {e}"))
                    })?;
                let topic_metadata = metadata
                    .topics()
                    .first()
                    .ok_or_else(|| ShoveError::Topology(format!("no metadata for topic {q}")))?;
                Ok(topic_metadata.partitions().iter().map(|p| p.id()).collect())
            })
            .await
            .map_err(|e| ShoveError::Topology(format!("metadata task failed: {e}")))??
        };

        // Build a single TopicPartitionList for all partitions so we
        // fetch committed offsets in one RPC instead of N.
        let mut tpl = TopicPartitionList::new();
        for &pid in &partitions {
            tpl.add_partition(&queue, pid);
        }

        // perf-K-11: committed_offsets can fail with transient errors (e.g.
        // NotCoordinator) when the group coordinator hasn't been elected.
        // Drive the retry loop with tokio::time::sleep between attempts so
        // we don't hold a spawn_blocking worker across the backoff (the old
        // code used std::thread::sleep, which could pin a worker for up to
        // 5 seconds under coordinator-election races).
        let committed = {
            let mut last_err = None;
            let mut result = None;
            for attempt in 0..5u32 {
                let c = Arc::clone(&consumer);
                let tpl_clone = tpl.clone();
                let r = tokio::task::spawn_blocking(move || {
                    c.committed_offsets(tpl_clone, Duration::from_secs(5))
                })
                .await
                .map_err(|e| ShoveError::Topology(format!("committed task failed: {e}")))?;
                match r {
                    Ok(c) => {
                        result = Some(c);
                        break;
                    }
                    Err(e) => {
                        last_err = Some(e);
                        if attempt < 4 {
                            tokio::time::sleep(Duration::from_millis(500 * (attempt as u64 + 1)))
                                .await;
                        }
                    }
                }
            }
            result.ok_or_else(|| {
                ShoveError::Connection(format!(
                    "failed to get committed offsets for {queue}: {}",
                    last_err.unwrap()
                ))
            })?
        };

        // Per-partition watermark fetch is still serial (perf-K-12 — rdkafka
        // doesn't expose a batched end-watermarks API; staying serial here).
        let total_lag: u64 = {
            let c = Arc::clone(&consumer);
            let q = queue.clone();
            tokio::task::spawn_blocking(move || -> Result<u64> {
                let mut total: u64 = 0;
                for pid in partitions {
                    let (_low, high) = c
                        .fetch_watermarks(&q, pid, Duration::from_secs(5))
                        .map_err(|e| {
                            ShoveError::Connection(format!(
                                "failed to fetch watermarks for {q}/{pid}: {e}"
                            ))
                        })?;
                    if let Some(elem) = committed.find_partition(&q, pid) {
                        let committed_offset = match elem.offset() {
                            rdkafka::Offset::Offset(o) => o,
                            _ => 0,
                        };
                        if high > committed_offset {
                            total += (high - committed_offset) as u64;
                        }
                    } else {
                        total += high as u64;
                    }
                }
                Ok(total)
            })
            .await
            .map_err(|e| ShoveError::Topology(format!("watermarks task failed: {e}")))??
        };

        Ok(KafkaQueueStats {
            messages_pending: total_lag,
            messages_in_flight: 0, // Kafka doesn't expose in-flight count easily
        })
    }
}

/// Backend that adapts a [`KafkaConsumerGroupRegistry`] to the generic [`AutoscalerBackend`] trait.
pub struct KafkaAutoscalerBackend<S: KafkaQueueStatsProvider = KafkaLagStatsProvider> {
    stats_provider: S,
    registry: Arc<Mutex<KafkaConsumerGroupRegistry>>,
}

impl KafkaAutoscalerBackend<KafkaLagStatsProvider> {
    /// Create a backend that talks to Kafka for queue stats.
    pub fn new(client: KafkaClient, registry: Arc<Mutex<KafkaConsumerGroupRegistry>>) -> Self {
        Self {
            stats_provider: KafkaLagStatsProvider::new(client),
            registry,
        }
    }

    /// Convenience constructor that wires up a fully-configured autoscaler with
    /// [`Stabilized<ThresholdStrategy>`] from a single [`AutoscalerConfig`].
    pub fn autoscaler(
        client: KafkaClient,
        registry: Arc<Mutex<KafkaConsumerGroupRegistry>>,
        config: AutoscalerConfig,
    ) -> Autoscaler<Self, Stabilized<ThresholdStrategy>> {
        let strategy = Stabilized::new(
            ThresholdStrategy {
                scale_up_multiplier: config.scale_up_multiplier,
                scale_down_multiplier: config.scale_down_multiplier,
            },
            config.hysteresis_duration,
            config.cooldown_duration,
        );
        let backend = Self::new(client, registry);
        Autoscaler::new(backend, strategy, config.poll_interval)
    }
}

impl<S: KafkaQueueStatsProvider> KafkaAutoscalerBackend<S> {
    /// Create a backend with an explicit stats provider (useful for testing).
    pub fn with_stats_provider(
        stats_provider: S,
        registry: Arc<Mutex<KafkaConsumerGroupRegistry>>,
    ) -> Self {
        Self {
            stats_provider,
            registry,
        }
    }
}

impl<S: KafkaQueueStatsProvider> AutoscalerBackend for KafkaAutoscalerBackend<S> {
    type GroupId = String;

    async fn list_groups(&self) -> Result<Vec<Self::GroupId>> {
        let reg = self.registry.lock().await;
        Ok(reg.groups().keys().cloned().collect())
    }

    async fn fetch_metrics(&self, group: &Self::GroupId) -> Result<ScalingMetrics> {
        let (queue, group_id, prefetch, active) = {
            let reg = self.registry.lock().await;
            let g = reg
                .groups()
                .get(group)
                .ok_or_else(|| ShoveError::Topology(format!("group not found: {group}")))?;
            (
                g.queue().to_owned(),
                g.group_id().to_owned(),
                g.config().prefetch_count(),
                g.active_consumers(),
            )
        };

        let stats = self
            .stats_provider
            .get_queue_stats(&queue, &group_id)
            .await?;

        debug!(
            group = %group,
            queue = %queue,
            messages_pending = stats.messages_pending,
            messages_in_flight = stats.messages_in_flight,
            active_consumers = active,
            "fetched Kafka metrics"
        );

        Ok(ScalingMetrics::new(
            stats.messages_pending,
            stats.messages_in_flight,
            active as u16,
            prefetch,
        ))
    }

    async fn scale(&self, group: &Self::GroupId, decision: ScalingDecision) -> Result<()> {
        let mut reg = self.registry.lock().await;
        let g = reg
            .groups_mut()
            .get_mut(group)
            .ok_or_else(|| ShoveError::Topology(format!("group not found: {group}")))?;

        match decision {
            ScalingDecision::ScaleUp(n) => {
                for _ in 0..n {
                    if !g.scale_up() {
                        warn!(group = %group, "scale-up requested but already at max consumers");
                        break;
                    }
                }
                info!(group = %group, consumers = g.active_consumers(), "Kafka scaled up");
            }
            ScalingDecision::ScaleDown(n) => {
                for _ in 0..n {
                    if !g.scale_down() {
                        debug!(group = %group, "scale-down requested but already at min consumers");
                        break;
                    }
                }
                info!(group = %group, consumers = g.active_consumers(), "Kafka scaled down");
            }
            ScalingDecision::Hold => {}
        }

        Ok(())
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::autoscaler::{Autoscaler, Stabilized, ThresholdStrategy};
    use std::collections::HashMap;
    use std::time::Duration;

    use crate::backend::ConsumerOptionsInner as ConsumerOptions;
    use crate::backends::kafka::constants::consumer_group_id;
    use crate::backends::kafka::consumer_group::{KafkaConsumerGroup, KafkaConsumerGroupConfig};
    use tokio_util::sync::CancellationToken;

    struct MockKafkaStatsProvider {
        stats: HashMap<String, KafkaQueueStats>,
    }

    impl MockKafkaStatsProvider {
        fn new() -> Self {
            Self {
                stats: HashMap::new(),
            }
        }
    }

    impl KafkaQueueStatsProvider for MockKafkaStatsProvider {
        async fn get_queue_stats(&self, queue: &str, _group_id: &str) -> Result<KafkaQueueStats> {
            self.stats
                .get(queue)
                .cloned()
                .ok_or_else(|| ShoveError::Topology(format!("not found: {queue}")))
        }
    }

    type TestSpawner = Arc<dyn Fn(ConsumerOptions) -> tokio::task::JoinHandle<()> + Send + Sync>;

    fn make_test_group(
        queue: &str,
        config: KafkaConsumerGroupConfig,
        started: bool,
    ) -> KafkaConsumerGroup {
        let group_token = CancellationToken::new();
        let spawner: TestSpawner = Arc::new(|options: ConsumerOptions| {
            tokio::spawn(async move {
                options.shutdown.cancelled().await;
            })
        });

        let queue_str: String = queue.into();
        let group_id = consumer_group_id(&queue_str);
        let mut group = KafkaConsumerGroup {
            queue: queue_str,
            group_id,
            consumers: Vec::with_capacity(config.max_consumers() as usize),
            config,
            spawner,
            group_token,
            error_count: Arc::new(std::sync::atomic::AtomicUsize::new(0)),
            panic_count: Arc::new(std::sync::atomic::AtomicUsize::new(0)),
        };
        if started {
            group.start();
        }
        group
    }

    fn make_single_group_registry(
        min: u16,
        max: u16,
        prefetch: u16,
        started: bool,
    ) -> Arc<Mutex<KafkaConsumerGroupRegistry>> {
        let config = KafkaConsumerGroupConfig::new(min..=max).with_prefetch_count(prefetch);
        let group = make_test_group("test-queue", config, started);

        let mut groups = HashMap::new();
        groups.insert("test-group".to_string(), group);

        Arc::new(Mutex::new(KafkaConsumerGroupRegistry::from_groups(groups)))
    }

    #[tokio::test]
    async fn kafka_backend_list_groups() {
        let registry = make_single_group_registry(1, 5, 10, false);
        let backend =
            KafkaAutoscalerBackend::with_stats_provider(MockKafkaStatsProvider::new(), registry);
        let groups = backend.list_groups().await.unwrap();
        assert_eq!(groups, vec!["test-group".to_string()]);
    }

    #[tokio::test]
    async fn kafka_backend_fetch_metrics() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let mut stats_provider = MockKafkaStatsProvider::new();
        stats_provider.stats.insert(
            "test-queue".into(),
            KafkaQueueStats {
                messages_pending: 42,
                messages_in_flight: 7,
            },
        );

        let backend = KafkaAutoscalerBackend::with_stats_provider(stats_provider, registry);
        let metrics = backend
            .fetch_metrics(&"test-group".to_string())
            .await
            .unwrap();

        assert_eq!(metrics.messages_ready, 42);
        assert_eq!(metrics.messages_in_flight, 7);
        assert_eq!(metrics.active_consumers, 1);
        assert_eq!(metrics.prefetch_count, 10);
    }

    #[tokio::test]
    async fn kafka_backend_scale_up() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let backend = KafkaAutoscalerBackend::with_stats_provider(
            MockKafkaStatsProvider::new(),
            registry.clone(),
        );

        backend
            .scale(&"test-group".to_string(), ScalingDecision::ScaleUp(1))
            .await
            .unwrap();

        let count = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(count, 2);
    }

    #[tokio::test]
    async fn kafka_backend_scale_down() {
        let registry = make_single_group_registry(1, 5, 10, true);
        {
            let mut reg = registry.lock().await;
            reg.groups_mut().get_mut("test-group").unwrap().scale_up();
        }
        assert_eq!(
            registry
                .lock()
                .await
                .groups()
                .get("test-group")
                .unwrap()
                .active_consumers(),
            2
        );

        let backend = KafkaAutoscalerBackend::with_stats_provider(
            MockKafkaStatsProvider::new(),
            registry.clone(),
        );
        backend
            .scale(&"test-group".to_string(), ScalingDecision::ScaleDown(1))
            .await
            .unwrap();

        let count = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(count, 1);
    }

    #[tokio::test]
    async fn kafka_backend_scale_up_clamped_at_max() {
        let registry = make_single_group_registry(1, 2, 10, true);
        let backend = KafkaAutoscalerBackend::with_stats_provider(
            MockKafkaStatsProvider::new(),
            registry.clone(),
        );

        backend
            .scale(&"test-group".to_string(), ScalingDecision::ScaleUp(10))
            .await
            .unwrap();

        let count = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(count, 2, "should be clamped at max=2");
    }

    #[tokio::test]
    async fn kafka_backend_full_autoscaler_round_trip() {
        let registry = make_single_group_registry(1, 5, 10, true);

        let mut stats_provider = MockKafkaStatsProvider::new();
        stats_provider.stats.insert(
            "test-queue".into(),
            KafkaQueueStats {
                messages_pending: 100,
                messages_in_flight: 0,
            },
        );

        let config = AutoscalerConfig {
            hysteresis_duration: Duration::ZERO,
            cooldown_duration: Duration::ZERO,
            ..AutoscalerConfig::default()
        };

        let mut autoscaler = Autoscaler::new(
            KafkaAutoscalerBackend::with_stats_provider(stats_provider, registry.clone()),
            Stabilized::new(
                ThresholdStrategy {
                    scale_up_multiplier: config.scale_up_multiplier,
                    scale_down_multiplier: config.scale_down_multiplier,
                },
                config.hysteresis_duration,
                config.cooldown_duration,
            ),
            config.poll_interval,
        );

        let before = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(before, 1);

        autoscaler.poll_and_scale().await;

        let after = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(after, 2, "expected scale-up after poll_and_scale");
    }

    #[tokio::test]
    async fn kafka_backend_scale_hold_is_noop() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let backend = KafkaAutoscalerBackend::with_stats_provider(
            MockKafkaStatsProvider::new(),
            registry.clone(),
        );

        backend
            .scale(&"test-group".to_string(), ScalingDecision::Hold)
            .await
            .unwrap();

        let count = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(count, 1, "Hold should not change consumer count");
    }

    #[tokio::test]
    async fn kafka_backend_fetch_metrics_unknown_group_fails() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let backend =
            KafkaAutoscalerBackend::with_stats_provider(MockKafkaStatsProvider::new(), registry);

        let result = backend
            .fetch_metrics(&"nonexistent-group".to_string())
            .await;
        assert!(
            result.is_err(),
            "fetch_metrics for unknown group should fail"
        );
    }

    #[tokio::test]
    async fn kafka_backend_scale_unknown_group_fails() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let backend =
            KafkaAutoscalerBackend::with_stats_provider(MockKafkaStatsProvider::new(), registry);

        let result = backend
            .scale(
                &"nonexistent-group".to_string(),
                ScalingDecision::ScaleUp(1),
            )
            .await;
        assert!(result.is_err(), "scale for unknown group should fail");
    }

    #[tokio::test]
    async fn kafka_backend_scale_down_clamped_at_min() {
        let registry = make_single_group_registry(1, 5, 10, true);
        let backend = KafkaAutoscalerBackend::with_stats_provider(
            MockKafkaStatsProvider::new(),
            registry.clone(),
        );

        backend
            .scale(&"test-group".to_string(), ScalingDecision::ScaleDown(5))
            .await
            .unwrap();

        let count = registry
            .lock()
            .await
            .groups()
            .get("test-group")
            .unwrap()
            .active_consumers();
        assert_eq!(count, 1, "should stay at min=1");
    }

    // -- arch-K-1: autoscaler uses the group's actual consumer group ID --

    fn make_group_registry_with_group_id(
        queue: &str,
        group_id: &str,
    ) -> Arc<Mutex<KafkaConsumerGroupRegistry>> {
        let config = KafkaConsumerGroupConfig::new(1..=5).with_prefetch_count(10);
        let group_token = CancellationToken::new();
        type TestSpawner =
            Arc<dyn Fn(ConsumerOptions) -> tokio::task::JoinHandle<()> + Send + Sync>;
        let spawner: TestSpawner = Arc::new(|options: ConsumerOptions| {
            tokio::spawn(async move {
                options.shutdown.cancelled().await;
            })
        });
        let group = KafkaConsumerGroup {
            queue: queue.into(),
            group_id: group_id.into(),
            consumers: Vec::with_capacity(config.max_consumers() as usize),
            config,
            spawner,
            group_token,
            error_count: Arc::new(std::sync::atomic::AtomicUsize::new(0)),
            panic_count: Arc::new(std::sync::atomic::AtomicUsize::new(0)),
        };

        let mut groups = HashMap::new();
        groups.insert("test-group".to_string(), group);
        Arc::new(Mutex::new(KafkaConsumerGroupRegistry::from_groups(groups)))
    }

    #[tokio::test]
    async fn fetch_metrics_passes_stored_group_id_to_stats_provider() {
        // Standard group: group_id defaults to "{queue}-consumer". Regression
        // test for arch-K-1 on the standard path — without it the FIFO test
        // alone left the default-derivation case uncovered.
        let queue = "orders";
        let expected_group_id = format!("{queue}-consumer");
        let registry = make_group_registry_with_group_id(queue, &expected_group_id);

        struct AssertGroupIdProvider {
            expected_group_id: String,
            stats: KafkaQueueStats,
        }
        impl KafkaQueueStatsProvider for AssertGroupIdProvider {
            async fn get_queue_stats(
                &self,
                _queue: &str,
                group_id: &str,
            ) -> Result<KafkaQueueStats> {
                assert_eq!(
                    group_id, self.expected_group_id,
                    "autoscaler must pass the stored group_id to the stats provider"
                );
                Ok(self.stats.clone())
            }
        }

        let backend = KafkaAutoscalerBackend::with_stats_provider(
            AssertGroupIdProvider {
                expected_group_id,
                stats: KafkaQueueStats {
                    messages_pending: 10,
                    messages_in_flight: 0,
                },
            },
            registry,
        );

        let metrics = backend
            .fetch_metrics(&"test-group".to_string())
            .await
            .unwrap();
        assert_eq!(metrics.messages_ready, 10);
    }

    #[tokio::test]
    async fn fetch_metrics_uses_fifo_group_id_for_fifo_groups() {
        // FIFO group: group_id = "{queue}-fifo", NOT "{queue}-consumer".
        // Before the arch-K-1 fix, the autoscaler always derived group_id as
        // "{queue}-consumer", so committed offsets for the FIFO group were never
        // found and the fallback path reported the full partition watermark as lag.
        let queue = "orders";
        let fifo_group_id = format!("{queue}-fifo");
        let registry = make_group_registry_with_group_id(queue, &fifo_group_id);

        // Provider keyed by queue name; we verify the group_id forwarded to it.
        let mut stats = HashMap::new();
        stats.insert(
            queue.to_string(),
            KafkaQueueStats {
                messages_pending: 5,
                messages_in_flight: 0,
            },
        );

        // Use a provider that only answers when called with the FIFO group_id —
        // if the autoscaler passes "{queue}-consumer" instead, the call succeeds
        // because MockKafkaStatsProvider ignores group_id; so we use a dedicated
        // mock that enforces the group_id.
        struct AssertGroupIdProvider {
            expected_group_id: String,
            stats: KafkaQueueStats,
        }
        impl KafkaQueueStatsProvider for AssertGroupIdProvider {
            async fn get_queue_stats(
                &self,
                _queue: &str,
                group_id: &str,
            ) -> Result<KafkaQueueStats> {
                assert_eq!(
                    group_id, self.expected_group_id,
                    "autoscaler must pass the FIFO group_id to the stats provider"
                );
                Ok(self.stats.clone())
            }
        }

        let backend = KafkaAutoscalerBackend::with_stats_provider(
            AssertGroupIdProvider {
                expected_group_id: fifo_group_id,
                stats: KafkaQueueStats {
                    messages_pending: 5,
                    messages_in_flight: 0,
                },
            },
            registry,
        );

        let metrics = backend
            .fetch_metrics(&"test-group".to_string())
            .await
            .unwrap();
        assert_eq!(metrics.messages_ready, 5);
    }
}