1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/7af619956a0d733870a7ac9264b24106c6e3daec|7af61995>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/a8dbcc36184b2a7bafd4f6ffb1a645d1680b3291|a8dbcc36>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/c3e6e1719c1aabafe2465243cc5c81fe5f664ab1|c3e6e171>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/13be53bdbb02b73be51a214fb3b9e39ece16b305|13be53bd>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/99342541dbe37ae0873b30931890472d0d53ec5a|99342541>

- debug flyteorg/flyte-conference-talks

#1017 Adds documentation on usage for new Secret fields env_var and file Pull request opened by gpgn Adds documentation for the following change: • flyteorg/flytekit#1726 • flyteorg/flytepropeller#589 • flyteorg/flyteidl#423 • #1017 flyteorg/flytesnacks ✅ All checks have passed 2/2 successful checks

#1726 Feat add optional environment variable name to secret Pull request opened by gpgn TL;DR Introduces new fields to the

Secret

object: •

env_var

•

file

Allowing users to directly specify a name or mountPath for the Secret, without having to specify a full PodTemplate(name). The old

mount_requirement

can still be used. Example:

from flytekit import task, workflow, Secret
import flytekit
import os


@task(
    secret_requests=[
        Secret(
            group="user-info",
            key="user_secret",
            mount_requirement=Secret.MountType.FILE,
        ),
        Secret(
            group="user-info",
            key="user_secret",
            mount_requirement=Secret.MountType.ENV_VAR,
        ),
    ]
)
def old() -> None:
    context = flytekit.current_context()
    print("old")

    # mount_requirement=ENV_VAR
    print(context.secrets.get(env_name="_FSEC_USER-INFO_USER_SECRET"))

    # mount_requirement=FILE
    with open('/etc/flyte/secrets/user-info/user_secret', 'r') as infile:
        print(infile.readlines())
    return True

@task(
    secret_requests=[
        Secret(
            group="user-info",
            key="user_secret",
            env_var=Secret.MountEnvVar(name="foo"),
        ),
        Secret(
            group="user-info",
            key="user_secret",
            file=Secret.MountFile(path="/foo"),
        ),
    ]
)

def new() -> None:
    context = flytekit.current_context()
    print("new")

    # env_var=
    print(context.secrets.get(env_name="foo"))

    # file=
    with open('/foo/user_secret', 'r') as infile:
        print(infile.readlines())


@workflow
def training_workflow(hyperparameters: dict) -> None:
    """Put all of the steps together into a single workflow."""
    old()
    new()

Type ☐ Bug Fix ☑︎ Feature ☐ Plugin Are all requirements met? ☑︎ Code completed ☑︎ Smoke tested ☑︎ Unit tests added ☑︎ Code documentation added ☑︎ Any pending items have an associated Issue Complete description How did you fix the bug, make the feature etc. Link to any design docs etc Tracking Issue fixes flyteorg/flyte#3053 Follow-up issue NA flyteorg/flytekit ✅ All checks have passed 2/2 successful checks

#1727 Throw warning for nested @Task functions Pull request opened by oliverhu TL;DR Address flyteorg/flyte#3734 that nested Tasks/Workflows is not warned. Type ☑︎ Bug Fix ☐ Feature ☐ Plugin Are all requirements met? ☑︎ Code completed ☑︎ Smoke tested ☐ Unit tests added ☐ Code documentation added ☐ Any pending items have an associated Issue Complete description In order to detect entities that are nested inside `@task`: 1. During local execution, create a new

FlyteContext

with

LOCAL_TASK_EXECUTION

for

@task

,and

LOCAL_WORKFLOW_EXECUTION

if it is

@workflow

. 2. If

flyte_entity_call_handler

is invoked inside

LOCAL_TASK_EXECUTION

or

TASK_EXECUTION

, that means it is called inside

@task

, warn the users of nested

@tasks/@workflows

. Created a helper function

is_local_execution()

to shorthand the checks. Tracking Issue flyteorg/flyte#3734 Follow-up issue The *call*() function in remote_callable and reference_entity duplicates and can be replaced with

flyte_entity_call_handler

as well in the future. flyteorg/flytekit ✅ All checks have passed 2/2 successful checks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/1e24d3e067a75b11e2019189e88c8e37bdab6a41|1e24d3e0>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/970f3e5b2be237d14dec1b5e8885d697610ee922|970f3e5b>

- update ephemeral storage flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/bac9c47fe022adb3e720670aa148c8325d9474ac|bac9c47f>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/9c14da770a8fcbf827c48a5e3c0eb4f85fa94928|9c14da77>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/90ed27f41eef295542f2e0a2e55159eedd68e6f6|90ed27f4>

- debug flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/3a665bd501f802f19bc4f24acf205a9084179a3a|3a665bd5>

- only run unit tests flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/577b24acd11fd0790616cb2efb841adc1ab7beae|577b24ac>

- remove ephemeral storage flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/90867d2617f5e4158c80d876526f96660f5a75c0|90867d26>

- testing setup flyte sandbox flyteorg/flyte-conference-talks

#1018 Fix merge_sort.py code bug Pull request opened by Future-Outlier If the count variable is set to 25, then the code will only sort the first 24 numbers. flyteorg/flytesnacks ✅ All checks have passed 30/30 successful checks

#5 Add minimal integration test Pull request opened by cosmicBboy flyteorg/flyte-conference-talks ✅ All checks have passed 14/14 successful checks

14 new commits pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/d8d3fa508a4a682c44cf8497a85c04e8023a903e|d8d3fa50>

- wip

<https://github.com/flyteorg/flyte-conference-talks/commit/4a57822cf04f4f6e734d39c7bb56d1c709ce35ad|4a57822c>

- add flytekitplugins envd

<https://github.com/flyteorg/flyte-conference-talks/commit/79a335bd4a9795ab703be3b600036a33bfbd6392|79a335bd>

- wip

<https://github.com/flyteorg/flyte-conference-talks/commit/eaf9dc592ea10fc68ad1eeaeee80985c2d01fb95|eaf9dc59>

- add back integration tests

<https://github.com/flyteorg/flyte-conference-talks/commit/b8215a3dd390ea6978ead9eb35f243d1c8b73e04|b8215a3d>

- debug

<https://github.com/flyteorg/flyte-conference-talks/commit/b7b217c231e5ac3294a755c58989acc5c5db3df4|b7b217c2>

- debug

<https://github.com/flyteorg/flyte-conference-talks/commit/90093ccaf2ff2eb5123b6835e918aae17ff99c11|90093cca>

- matrix

<https://github.com/flyteorg/flyte-conference-talks/commit/a8b3a19d54a2fd8e9c08eae51c47e7ec2e193902|a8b3a19d>

- fix typing Annotated

<https://github.com/flyteorg/flyte-conference-talks/commit/c9ab0da63d161cc2e905d6fd1e84f7ff860b971a|c9ab0da6>

- debug

<https://github.com/flyteorg/flyte-conference-talks/commit/d52f124990c627d0373467664b1706e6fb517ef6|d52f1249>

- debug

<https://github.com/flyteorg/flyte-conference-talks/commit/edad4db0aa0242a9cc6818fa74a23688c7b6e693|edad4db0>

- add poll interval

<https://github.com/flyteorg/flyte-conference-talks/commit/e8ace0157cb92bf160b161388cb072053bf21aea|e8ace015>

- update readme

<https://github.com/flyteorg/flyte-conference-talks/commit/009f7b7969de1425b4cd7c387723a0fdd0ead478|009f7b79>

- add sandbox make command

<https://github.com/flyteorg/flyte-conference-talks/commit/8a8496c7ed19f6b045ca3cf90e508be8cf977c0c|8a8496c7>

- Merge pull request #5 from flyteorg/add-integration-tests flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/1ec3833af373d9350d4ca2b6f16c83d680a3fc1d|1ec3833a>

- update resources, makefile flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte/tree/master|master>

by samhita-alla

<https://github.com/flyteorg/flyte/commit/49868b670e45eba0b72387849f7e172378c5c1a1|49868b67>

- Doc: gang-scheduling for kubeflow training-operator (#3851) flyteorg/flyte

#3853 [BUG] loader must define exec_module() when running Databricks task Issue created by rambrus Describe the bug BACKGROUND I'm trying to run a simplified Flyte task using Databricks plugin. PREREQUISITES: • Flyte 1.7.0 installed on EKS cluster • Flyte Databricks plugins is configured as described here: https://docs.flyte.org/en/latest/deployment/plugins/webapi/databricks.html • entrypoint.py is uploaded to DBFS • Databricks cluster is created with the following settings: DBR 11.3 LTS, Python 3.9.5, installed libs: flytekit==1.7.0, flytekitplugins-spark==1.7.0 • A simpliified Flyte workflow is created:

@task(
    task_config=Databricks(
        databricks_conf={
           "run_name": "dbx simplified example",
           "existing_cluster_id": "<my-existing-cluster-id>",
           "timeout_seconds": 3600,
           "max_retries": 1,
       }
    ),
    limits=Resources(mem="2000M"),
    cache_version="1",
)
def print_spark_config():
    spark = flytekit.current_context().spark_session
    print(spark.sparkContext.getConf().getAll())

@workflow
def my_databricks_job():
    print_spark_config()

STEPS: • Run workflow:

pyflyte --verbose run --remote --destination-dir . dbx_simplified_example.py my_databricks_job

ISSUE: Databricks job run triggered and failed with this error: _TypeError: loader must define exec_module()_ ERROR LOG:

TypeError: loader must define exec_module()
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<command--1> in <cell line: 12>()
     11 
     12 with open(filename, "rb") as f:
---> 13   exec(compile(f.read(), filename, 'exec'))
     14 

/tmp/tmptkt83uf9.py in <module>
      4 
      5 import click
----> 6 from flytekit.bin.entrypoint import fast_execute_task_cmd as _fast_execute_task_cmd
      7 from flytekit.bin.entrypoint import execute_task_cmd as _execute_task_cmd
      8 from flytekit.exceptions.user import FlyteUserException

/databricks/python_shell/dbruntime/PythonPackageImportsInstrumentation/__init__.py in import_patch(name, globals, locals, fromlist, level)
    169             # Import the desired module. If you’re seeing this while debugging a failed import,
    170             # look at preceding stack frames for relevant error information.
--> 171             original_result = python_builtin_import(name, globals, locals, fromlist, level)
    172 
    173             is_root_import = thread_local._nest_level == 1

/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/flytekit/__init__.py in <module>
    226 from flytekit.core.workflow import ImperativeWorkflow as Workflow
    227 from flytekit.core.workflow import WorkflowFailurePolicy, reference_workflow, workflow
--> 228 from flytekit.deck import Deck
    229 from flytekit.image_spec import ImageSpec
    230 from flytekit.loggers import logger

/databricks/python_shell/dbruntime/PythonPackageImportsInstrumentation/__init__.py in import_patch(name, globals, locals, fromlist, level)
    169             # Import the desired module. If you’re seeing this while debugging a failed import,
    170             # look at preceding stack frames for relevant error information.
--> 171             original_result = python_builtin_import(name, globals, locals, fromlist, level)
    172 
    173             is_root_import = thread_local._nest_level == 1

/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/flytekit/deck/__init__.py in <module>
     16 
     17 from .deck import Deck
---> 18 from .renderer import TopFrameRenderer

/databricks/python_shell/dbruntime/PythonPackageImportsInstrumentation/__init__.py in import_patch(name, globals, locals, fromlist, level)
    169             # Import the desired module. If you’re seeing this while debugging a failed import,
    170             # look at preceding stack frames for relevant error information.
--> 171             original_result = python_builtin_import(name, globals, locals, fromlist, level)
    172 
    173             is_root_import = thread_local._nest_level == 1

/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/flytekit/deck/renderer.py in <module>
     10     import pyarrow
     11 else:
---> 12     pandas = lazy_module("pandas")
     13     pyarrow = lazy_module("pyarrow")
     14 

/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.9/site-packages/flytekit/lazy_import/lazy_module.py in lazy_module(fullname)
     25     # <https://docs.python.org/3/library/importlib.html#implementing-lazy-imports>
     26     spec = importlib.util.find_spec(fullname)
---> 27     loader = importlib.util.LazyLoader(spec.loader)
     28     spec.loader = loader
     29     module = importlib.util.module_from_spec(spec)

/usr/lib/python3.9/importlib/util.py in __init__(self, loader)
    280 
    281     def __init__(self, loader):
--> 282         self.__check_eager_loader(loader)
    283         self.loader = loader
    284 

/usr/lib/python3.9/importlib/util.py in __check_eager_loader(loader)
    271     def __check_eager_loader(loader):
    272         if not hasattr(loader, 'exec_module'):
--> 273             raise TypeError('loader must define exec_module()')
    274 
    275     @classmethod

TypeError: loader must define exec_module()

Expected behavior Databricks job triggered, workflow successfully completed. Additional context to reproduce I suspect the entrypoint.py referred in Databricks Plugin Setup guide is not compatible with Flyte 1.7.0. Screenshots No response Are you sure this issue hasn't been raised already? ☑︎ Yes Have you read the Code of Conduct? ☑︎ Yes flyteorg/flyte

#3854 [Core feature] Support termination of individual task/subworkflow Issue created by leonlnj Motivation: Why do you think this is important? Currently the UI only allow termination of the entire execution. To exhibit a similar behaviour to external workflow, for task/sub-workflow. Why is it helpful to fail a particular task/sub-workflow • Allow parallel tasks to continue running while stopping one chain of tasks to stop • Ability to recover pipeline later and allow dependent/parallel tasks output to be reused The task could be not failing naturally due to upstream store issue or data quality related issue and rerunning the entire pipeline could be expensive. Goal: What should the final outcome look like, ideally? Ability to abort a task from the UI Describe alternatives you've considered It is possible to do it by extracting all the workflow as External Workflow and adding caching mechanism. However there add a lot of complexity for large pipeline with many subworkflows to make all of them an external workflow and cachable. Propose: Link/Inline OR Additional context No response Are you sure this issue hasn't been raised already? ☑︎ Yes Have you read the Code of Conduct? ☑︎ Yes flyteorg/flyte

#1019 add a note specifying the supported kuberay version Pull request opened by samhita-alla This PR adds a note to the kuberay docs specifying the version supported by the plugin. Fixes flyteorg/flyte#3763 flyteorg/flytesnacks GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/whylogs_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/type_system) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/sql_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/sagemaker_training_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/sagemaker_pytorch_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/ray_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/pima_diabetes) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/papermill_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/pandera_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/onnx_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/nlp_processing) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/modin_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/mnist_classifier) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/mlflow_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/kftensorflow_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/kfpytorch_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/kfmpi_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/k8s_spark_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/k8s_pod_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/k8s_dask_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/image_spec) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/house_price_prediction) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/greatexpectations_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/forecasting_sales) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/feast_integration) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/exploratory_data_analysis) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/duckdb_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/dolt_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/dbt_plugin) GitHub Actions: Serialize & Register Flytesnacks workflow / Serialize Example (examples/databricks_plugin) ✅ No checks have passed 0/30 successful checks

#3855 [BUG] Flyte task keeps running forever when running a Databricks job Issue created by rambrus Describe the bug BACKGROUND: I'm trying to run a simplified Flyte task using Databricks plugin. PREREQUISITES: • Flyte 1.5.0 installed on EKS cluster • Flyte Databricks plugins is configured as described here: https://docs.flyte.org/en/latest/deployment/plugins/webapi/databricks.html • entrypoint.py is uploaded to DBFS • Databricks cluster is created with the following settings: DBR 11.3 LTS, installed libs: flytekit==1.5.0, flytekitplugins-spark==1.5.0 • A simplified Flyte workflow is created:

@task(
    task_config=Databricks(
        databricks_conf={
           "run_name": "dbx simplified example",
           "existing_cluster_id": "<my-existing-cluster-id>",
           "timeout_seconds": 3600,
           "max_retries": 1,
       }
    ),
    limits=Resources(mem="2000M"),
    cache_version="1",
)
def print_spark_config():
    spark = flytekit.current_context().spark_session
    print(spark.sparkContext.getConf().getAll())

@workflow
def my_databricks_job():
    print_spark_config()

STEPS: • Run workflow:

pyflyte --verbose run --remote --destination-dir . dbx_simplified_example.py my_databricks_job

ISSUE: Databricks job run triggered and successfully completed, but the Flyte job status is not updated, it is stuck in

RUNNING

state. Expected behavior Flyte job status keeps updated. Additional context to reproduce Please note that we tried to upgrade Flyte to v1.7.0: • when I also upgraded the Flyte packages on the Databricks cluster to 1.7.0 -> #3853 • when I used the 1.5.0 Flyte packages on the Databricks cluster -> same issue - Databricks job successfully completed, but Flyte job keeps running forever Screenshots No response Are you sure this issue hasn't been raised already? ☑︎ Yes Have you read the Code of Conduct? ☑︎ Yes flyteorg/flyte

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/4b020a1e75dd2de91f3c29d686615b8a30b81ad3|4b020a1e>

- update readme flyteorg/flyte-conference-talks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/1b1d33eff5140c8a3c4a3c5821ec522000decafd|1b1d33ef>

- update readme flyteorg/flyte-conference-talks

#1020 update docs around pyflyte run Pull request opened by samhita-alla This PR updates docs around the

pyflyte run

to indicate that it is no longer limited to single-script execution. flyteorg/flytesnacks GitHub Actions: Docs Warnings ✅ 2 other checks have passed 2/3 successful checks

#1728 update docs around pyflyte run Pull request opened by samhita-alla TL;DR This PR updates docs around the pyflyte run command to indicate that it is no longer limited to single-script execution. Type ☐ Bug Fix ☐ Feature ☐ Plugin Are all requirements met? ☐ Code completed ☐ Smoke tested ☐ Unit tests added ☐ Code documentation added ☐ Any pending items have an associated Issue Complete description How did you fix the bug, make the feature etc. Link to any design docs etc Tracking Issue Fixes flyteorg/flyte#3757 Follow-up issue NA OR https://github.com/flyteorg/flyte/issues/ flyteorg/flytekit GitHub Actions: build-plugins (3.8, flytekit-kf-tensorflow) GitHub Actions: build-plugins (3.8, flytekit-kf-pytorch) GitHub Actions: build-plugins (3.8, flytekit-kf-mpi) GitHub Actions: build-plugins (3.8, flytekit-k8s-pod) GitHub Actions: build-plugins (3.8, flytekit-huggingface) GitHub Actions: build-plugins (3.8, flytekit-hive) GitHub Actions: build-plugins (3.8, flytekit-greatexpectations) GitHub Actions: build-plugins (3.8, flytekit-envd) GitHub Actions: build-plugins (3.8, flytekit-duckdb) GitHub Actions: build-plugins (3.8, flytekit-dolt) GitHub Actions: build-plugins (3.8, flytekit-deck-standard) GitHub Actions: build-plugins (3.8, flytekit-dbt) GitHub Actions: build-plugins (3.8, flytekit-data-fsspec) GitHub Actions: build-plugins (3.8, flytekit-dask) GitHub Actions: build-plugins (3.8, flytekit-bigquery) GitHub Actions: build-plugins (3.8, flytekit-aws-sagemaker) GitHub Actions: build-plugins (3.8, flytekit-aws-batch) GitHub Actions: build-plugins (3.8, flytekit-aws-athena) GitHub Actions: build (windows-latest, 3.11) GitHub Actions: build (windows-latest, 3.9) GitHub Actions: build (windows-latest, 3.8) GitHub Actions: build (ubuntu-latest, 3.11) GitHub Actions: build (ubuntu-latest, 3.10) GitHub Actions: build (ubuntu-latest, 3.9) GitHub Actions: build (ubuntu-latest, 3.8) GitHub Actions: docs GitHub Actions: Docs Warnings ✅ 2 other checks have passed 2/29 successful checks

1 new commit pushed to

<https://github.com/flyteorg/flyte-conference-talks/tree/main|main>

by cosmicBboy

<https://github.com/flyteorg/flyte-conference-talks/commit/d9f1da172272786ebd8b1f10a57312abc7d68758|d9f1da17>

- update resource reqs for example 10 flyteorg/flyte-conference-talks