Status of testing Providers that were prepared on October 06, 2026 #74459

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1. potiuk

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   kind:metaHigh-level information important to the communityHigh-level information important to the community

   testing statusStatus of testing releasesStatus of testing releases

   on Oct 8, 2026
2. jingi723 commented on Oct 8, 2026

   

   jingi723

   on Oct 8, 2026

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   Verified my changes in apache-airflow-providers-amazon==9.38.0rc1 for #73756 and #73881 using the PyPI wheel, with Airflow 3.3.2 / Python 3.12.14 on Linux ARM64. Updated with live AWS verification in ap-northeast-2.

   • Keep S3 Dag bundle downloads within the configured directory #73756: All 8 checks pass against a real S3 bucket: bundle initialization and repeated refresh with directory prefixes with/without trailing slashes, sibling-prefix objects, and objects whose key equals the configured prefix. Verified downloaded contents, stale-file/directory cleanup, and preservation of excluded remote objects.
   • Handle plain Step Functions execution errors #73881: All 9 checks pass using actual Standard Step Functions executions and DescribeExecution responses. Plain, Unicode, and malformed-JSON error strings are returned correctly; JSON-valued errors and successful output retain their types. In the live empty-string ErrorPath case, AWS omitted the error field and the operator correctly returned None.

   The 17 live-AWS checks all passed. Running the same checks with provider 9.37.0, using the same bucket and executions, reproduced 7 failures (4 S3, 3 Step Functions); reinstalling 9.38.0rc1 restored all 17 passes. Temporary buckets, state machines, and execution roles were deleted and their absence confirmed.

   The earlier 20 local checks using Moto/synthetic HTTP responses also passed (8 failures on 9.37.0), including explicit error: "", malformed success output, and service-error propagation. Those additional cases remain simulated. pip check passed, both merged commits are in the RC tag, and the relevant installed sources match the wheel and tag.

   Scope: the live checks make real AWS calls from the installed bundle/operator/hook. Operator execution is invoked directly, with UI extra-link persistence mocked; this does not cover scheduler/task-runner/XCom end-to-end behavior, an IAM-policy matrix, or the whole Amazon provider.

   👍React with 👍1Reacted by Jarek Potiuk
3. Andrushika commented on Oct 8, 2026

   

   Andrushika

   on Oct 8, 2026

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   #73652 tested in common.ai 0.11.0rc1, works as expected.
   Thanks for preparing the release, Jarek.

   ❤️React with ❤️1Reacted by Jarek Potiuk
4. ColtenOuO commented on Oct 8, 2026

   

   ColtenOuO

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   #73384 tested in common-ai 0.11.0rc1, works as expected too!

   Thanks for preparing the release, looking forward to the rapid development of common-ai ahead!
5. pankajkoti commented on Oct 8, 2026

   

   pankajkoti

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   #74017 tested that it's included in common-ai 0.11.0rc1 and works as expected.
   Thank you for preparing the release
6. zozo123 commented on Oct 8, 2026

   

   zozo123

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   #71676 and #74191 tested on rc1, works.

   • Add OpenSandbox backend for sandbox tools #71676 (common.ai 0.11.0rc1): I ran the PyPI wheel on Airflow 3.3.2 / Python 3.12 against a local OpenSandbox server. The PR's system-test Dag and its 64 unit tests pass, and command timeouts and sandbox cleanup behave as expected. One caveat, for a docs follow-up: when the server's egress sidecar runs in its default dns mode, a deny-all SandboxSpec() only blocks DNS, so direct-IP connections still get out. With [egress] mode = "dns+nft" they are blocked too, and everything above still passes. The backend can't tell the two modes apart on policy read-back.
   • Notify downstream Dags when COPY INTO writes a Unity (Databricks) table #74191 (databricks 7.22.0rc1): on a real SQL warehouse, COPY INTO emitted the canonical Unity table asset event and triggered the downstream Dag. Wrong table, wrong workspace and failed SQL emitted no event.

   ---

   Drafted-by: Claude Code (Opus 5.5) (no human review before posting)
7. divyanshus2404 commented on Oct 8, 2026

   

   divyanshus2404

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   #71711 tested in apache-spark 6.3.3rc1, works as expected.

   Verified against the RC in a clean venv: all masking forms produce the expected output (key=value, key value, quoted values spanning tokens, uppercase keys, tab- and multi-space-separated values, and a sensitive flag with no value), and a multiline value no longer swallows the log lines that follow it.

   The scanner that replaced the regex also closes the complexity gap raised in review on my PR — "secret" * 10000, which still backtracked quadratically in my version (~2.4s), now completes in 0.16ms. 50k single token: 0.66ms.

   Thanks for preparing the release.

   ---

   Drafted-by: Claude Code; reviewed by @divyanshus2404 before posting
8. aaron-y-chen commented on Oct 8, 2026

   

   aaron-y-chen

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   #73509 tested with apache-airflow-providers-amazon==9.38.0rc1 (Airflow 3.3.2, common-messaging 2.1.1), works as expected :)
9. subhramit commented on Oct 8, 2026

   

   subhramit

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   Have tested my changes

   • Add dedicated InfluxDB 3 sensor #73522 [influxdb: 2.13.0rc1]
   • Fix Elasticsearch and OpenSearch response wrapper bugs #73725 [elasticsearch: 6.9.2rc1] and [opensearch: 1.14.0rc1]

   using my agent, looks good:

   

   Thanks!
10. yuseok89 commented on Oct 9, 2026

    

    yuseok89

    on Oct 9, 2026

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    #72892 tested in amazon 9.38.0rc1 and #73880 tested in google 22.7.0rc1, both work as expected.
11. SEPURI-SAI-KRISHNA commented on Oct 9, 2026

    

    SEPURI-SAI-KRISHNA

    on Oct 9, 2026

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    Tested both of the changes I am listed for. Both work as expected.

    Environment: clean virtualenv on Python 3.11, installed from PyPI, apache-airflow 3.3.2. No dbt Cloud account or GCP project involved, since everything below is observable before the first API call. In each case I also checked the previous stable release to confirm the result depends on the change rather than passing either way.

    dbt.cloud 4.11.0rc1, Apply hook_params to deferred dbt Cloud job runs (#74199)

    Walking the installed wheel, the DbtCloudRunJobTrigger construction in operators/dbt.py now passes hook_params; on 4.10.0 it does not. In both releases the trigger already accepted it, kept it across serialize() and built its hook with **self.hook_params, so the operator's call site was the only gap and nothing else had to change.

    	4.10.0	4.11.0rc1
    hook_params passed at the defer site	absent	present

    Checked at runtime with hook_params={"retry_limit": 7, "retry_delay": 3.5}: the operator retains them, its own hook honours them, and a trigger built with them serializes them intact.

    google 22.7.0rc1, Apply impersonation_chain to deferred BigQuery existence checks (#71648)

    Both deferral sites in sensors/bigquery.py now pass impersonation_chain, one for BigQueryTableExistenceTrigger and one for BigQueryTablePartitionExistenceTrigger; on 22.6.0 neither does. As above, the triggers accepted and serialized the argument in both releases, so only the sensors needed the change.

    	22.6.0	22.7.0rc1
    BigQueryTableExistenceTrigger	absent	present
    BigQueryTablePartitionExistenceTrigger	absent	present

    Confirmed the trigger accepts impersonation_chain and serializes it as given.

    Import smoke check

    Importing every module of both providers: all 12 dbt Cloud modules import, and 297 of 333 google modules. The 36 that do not are all missing optional peers in this environment, other providers plus paramiko, kubernetes, apache-beam, cassandra, oracledb and similar, each failing with an explicit message naming what is absent. Nothing failed for a reason internal to either release.
12. FrankYang0529 commented on Oct 9, 2026

    

    FrankYang0529

    on Oct 9, 2026

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    Tested apache.kafka 2.1.0rc1 and it works as expected:

    • Add KafkaSharedStreamProducer and KafkaSharedStreamTrigger #68625: I ran two AssetWatchers with KafkaSharedStreamTrigger on the same topic. The two triggers share one Kafka consumer. Both assets get every message. Offsets are committed per partition only after the asset events are stored. After a restart, committed messages are not delivered again. A connection without enable.auto.commit=false is refused. On Airflow 3.1.8 and 2.11.2, importing the shared-stream triggers raises AirflowOptionalProviderFeatureException.

    I found some issues for following providers:

    • google 22.7.0rc1
      • Add GKEPodExecOperator for existing Pods #72577: operators/kubernetes_engine.py now imports KubernetesPodExecOperator at module level. KubernetesPodExecOperator only exists in cncf-kubernetes 10.22.0 and later (https://airflow.apache.org/docs/apache-airflow-providers-cncf-kubernetes/10.22.0/changelog.html). With an older cncf-kubernetes, importing operators/kubernetes_engine.py raises AirflowOptionalProviderFeatureException. So every GKE operator fails to import, not only GKEPodExecOperator. Should we update the GKE module like the EKS module? In Add EKS operator for commands in existing Pods #72542, if eks.py cannot import KubernetesPodExecOperator, it defines a fallback class with the same name. The __init__ of that fallback class raises the same exception that the GKE module raises on import. The other EKS operators still import, and only creating EksPodExecOperator fails. I can create a follow-up PR for this.
    • dbt.cloud 4.11.0rc1
      • Apply hook_params to deferred dbt Cloud job runs #74199: A DbtCloudRunJobOperator with deferrable=True that works on 4.10.0 fails on 4.11.0rc1 when hook_params holds retry_args with tenacity objects. Created a follow-up PR for it Fix deferred dbt Cloud tasks failing with tenacity retry_args #74489.
13. SEPURI-SAI-KRISHNA commented on Oct 9, 2026

    

    SEPURI-SAI-KRISHNA

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    Correcting my earlier comment: my verification of #74199 in dbt.cloud 4.11.0rc1 was wrong.

    I checked that hook_params survives serialize(), but I used {"retry_limit": 7, "retry_delay": 3.5}, two JSON serializable scalars. hook_params is a free form dict and the one key whose documented values are Python objects is retry_args, so my input could not exercise the case that matters. With a tenacity object in retry_args the task fails when it defers, and it fails after the dbt Cloud job has already started, which leaves the run orphaned.

    Thanks to @FrankYang0529 for catching it and for the fix in #74489.

    Treating that as a release blocker for dbt.cloud 4.11.0: shipping rc1 as is would regress any deferrable DbtCloudRunJobOperator whose hook_params carries retry_args, which worked on 4.10.0. The google 22.7.0rc1 item I reported is unaffected and my result there stands.
14. r3wretrhy commented on Oct 9, 2026

    

    r3wretrhy

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    Checked apache-airflow-providers-apache-beam 6.3.1rc1: #72510 is included and the async hook now launches pipelines via create_subprocess_exec without a shell. Works as expected.