@Rahul Mehta - FYI - https://github.com/flyteorg/flytectl/pull/348

@Prafulla Mahindrakar PR please - https://github.com/flyteorg/flytectl/pull/347

Hi everyone! I am completely new to Flyte but starting to set up some of our ML pipelines. We have a usecase where we might want to build some container based upon the output of a workflow. Does this make sens, how can it be done? Is this bad practice. Thanks :)

Hi Flyers, 🕑 Note the time change 🕑 Join our guest speakers from the Schibsted Media Group: • @Paul Beskow, Technical Architect • @Mücahit, Senior Data Engineer • @Björn Schiffler, Staff Data Scientist • @Yini Gao, ML Engineer and • @Oleg Ievtushok, Engineering Manager who will share their experience as they work towards onboarding their ML workflows to Flyte. Tuesday, Aug 23, 12pm PT (alternate time 🕑) Calendar Invite and Zoom Link

Hi Flyers, If you missed our previous community sync, the recordings have been posted to the Flyte YouTube channel. • Community Update: • Moving to ARM on Flyte [@Robert Everson - Lyft]: • Model Monitoring with WhyLogs and Flyte [Murilo Mendonça - WhyLabs]: • ZipRecruiter’s Flyte Path [@Seth Miller - ZipRecruiter] Meeting Notes

We will meet tomorrow at an alternate time of 12pm PT featuring: • KubeRay x Flyte Integration [@Yee - Union.ai] • Machine Learning in Production - How the Schibsted Media Group are planning to onboard their ML Workflows to Flyte [@Paul Beskow, @Mücahit, @Björn Schiffler, @Yini Gao and @Oleg Ievtushok] Calendar Invite & Zoom Link See you then!

I and @eduardo will be in SFO next 2 days. Let me know if any of you are around to catch up

Hi, How to delete the whole project using flytectl?

Hi everyone, I have a question about the deploy workflow As I understand it. To deploy workflow, docker images in the registry must be publicly accessible. I think this may pose a security risk to the project. So, can I use the private registry or is there any solution to make it secure? Thanks all.

Folks we would love a contribution on this - if anyone interested. https://github.com/flyteorg/flyte/issues/2138. There are queries That we need to change. This would make demo cluster even faster

Reminder: Today's community sync will be at 12pm PT.

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👋 Hi everyone!

Hi, I am getting below error in a hello world workflow. • I have created a .py file with exactly same hello world code from flytesnacks. • Then registered the files by running pyflyte register . -d development -p myproject • It registered the workflow and i am able to see it in the console. When launching the workflow , I am facing the below issues. Any one face similar issues?

[1/1] currentAttempt done. Last Error: USER::Pod failed. No message received from kubernetes.
[av6c5trbtctv6nkknd9m-n0-0] terminated with exit code (1). Reason [Error]. Message: 
tar: development/fastca4192cff23d37d3fb985a60de82c186.tar.gz: Cannot open: Not a directory
tar: Error is not recoverable: exiting now
Traceback (most recent call last):
  File "/usr/local/bin/pyflyte-fast-execute", line 8, in <module>
    sys.exit(fast_execute_task_cmd())
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python3.7/site-packages/click/core.py", line 760, in invoke
    return __callback(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/flytekit/bin/entrypoint.py", line 496, in fast_execute_task_cmd
    _download_distribution(additional_distribution, dest_dir)
  File "/usr/local/lib/python3.7/site-packages/flytekit/tools/fast_registration.py", line 117, in download_distribution
    result.check_returncode()
  File "/usr/local/lib/python3.7/subprocess.py", line 444, in check_returncode
    self.stderr)
subprocess.CalledProcessError: Command '['tar', '-xvf', 'development/fastca4192cff23d37d3fb985a60de82c186.tar.gz', '-C', 'development']' returned non-zero exit status 2.

Not sure, why the flytectl says that the file taken from flytesnacks as invalid files when trying to register. Even the pyflyte package is not recognizing the file. Any idea? My local:

flyte]$ tree workflows/

workflows/
├── hello_world.py
├── __init__.py
└── __pycache__
    ├── hello_world.cpython-37.pyc
    └── __init__.cpython-37.pyc
1 directory, 5 files

serializing using pyflyte which creates tar.gz file:

flyte]$ pyflyte register workflows/hello_world.py -d development  -p cloudops-max-flyte-demo

Output given as None, using a temporary directory at /tmp/tmplbj3dq0o instead
{"asctime": "2022-08-23 23:56:57,913", "name": "flytekit.remote", "levelname": "WARNING", "message": "Uploading /tmp/tmplbj3dq0o/fastd2800a4ca5d77817f85af258a1ca4eff.tar.gz to https://<my_bucket>.<http://s3.amazonaws.com/io/cloudops-max-flyte-demo/development/MKBVMY42N6USXMYOHFXIKC2DAI%3D%3D%3D%3D%3D%3D/fastd2800a4ca5d77817f85af258a1ca4eff.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=XXXXXXXXXXXXXXXXXXXXXXXXX-Amz-SignedHeaders=content-md5%3Bhost&X-Amz-Signature=XXXXXXXXXXXXXXXXXXXXX|s3.amazonaws.com/io/cloudops-max-flyte-demo/development/MKBVMY42N6USXMYOHFXIKC2DAI%3D%3D%3D%3D%3D%3D/fastd2800a4ca5d77817f85af258a1ca4eff.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=XXXXXXXXXXXXXXXXXXXXXXXXX-Amz-SignedHeaders=content-md5%3Bhost&X-Amz-Signature=XXXXXXXXXXXXXXXXXXXXX> native url s3://<my_bucket>/io/cloudops-max-flyte-demo/development/MKBVMY42N6USXMYOHFXIKC2DAI======/fastd2800a4ca5d77817f85af258a1ca4eff.tar.gz"}
Loading packages ['workflows.hello_world'] under source root /home/kkanagar/cloudops-max-flyte-demo/flyte
Successfully serialized 3 flyte objects

Registering using flytectl:

flyte]$ flytectl register files /tmp/tmplbj3dq0o/fastd2800a4ca5d77817f85af258a1ca4eff.tar.gz  -d development  -p cloudops-max-flyte-demo --archive

{"json":{},"level":"error","msg":"failed to initialize token source provider. Err: failed to fetch auth metadata. Error: rpc error: code = Unimplemented desc = unknown service flyteidl.service.AuthMetadataService","ts":"2022-08-23T23:57:19Z"}
{"json":{},"level":"warning","msg":"Starting an unauthenticated client because: can't create authenticated channel without a TokenSourceProvider","ts":"2022-08-23T23:57:19Z"}
Error: input package have some invalid files. try to run pyflyte package again [/tmp/register3231572267/workflows/__init__.py /tmp/register3231572267/workflows/hello_world.py]
{"json":{},"level":"error","msg":"input package have some invalid files. try to run pyflyte package again [/tmp/register3231572267/workflows/__init__.py /tmp/register3231572267/workflows/hello_world.py]","ts":"2022-08-23T23:57:19Z"}

@Ketan (kumare3) Is there a documentation for writing plugins for flyte. I could see that there are backend plugins for AWS, spark etc....

I have IBM LSF cluster on which jobs execute and would like to understand the plugin API document so that I can start looking at how this could be done

Hello, i am extending flytekit to create a custom plugin and i want to define some custom code when the pod gets terminated. are there any handlers that needs to be defined? 🧵

This message was deleted.

Hello, flyte team! Do I permit some specific users can access projects which have permission of them. Because I have troubles to control resource management per projects, only permitted users have to use the specified projects. but I have no idea how to give authentication to users (I am using keycloacks) Thank you!

Infrastructure orchestration doesn’t have to be so hard. Learn how to use Ray from within Flyte without changing the core of your code in this blog by Union.ai Backend Systems Engineer @Kevin Su. "With Ray native support in Flyte, users can easily transition from prototyping to production and rely on Flyte to automatically manage the Ray cluster lifecycle." - Keshi Dai (Spotify) Ray and Flyte: Distributed Computing and Orchestration

Hello.. running into some sort of variable binding bug. Can anyone help me fix this? I have a task which takes in a

Dict

as input. One of the values in that

Dict

is returned from previous task and Flyte is not able to bind the value. I get this AssertionError

AssertionError: this should be a Dictionary type and it is not: <class 'dict'> vs union_type {
  variants {
    map_value_type {
      simple: STRING
    }
    structure {
      tag: "Typed Dict"
    }
  }
  variants {
    simple: NONE
    structure {
      tag: "none"
    }
  }
}

If we have an already containerized Spark job we would like to run as a raw container using ContainerTask(), can we use this task in a workflow and ensure this gets submitted to the Spark Operator to run in cluster mode? cc: @Vasu Upadhya

📣 Contributors of the Month 📣 August has been an ML 🤖, Jupyter :jupyter:, and Helm :helm: month, thanks to Evan, Calvin, and Sujith! • @Evan Sadler has been an active member of the Flyte and UnionML communities. Evan worked on adding a custom flyte type for spark pipelines, and a hugging face 🤗 datasets plugin of his is in the works. • @Calvin Leather has been doing some work on the jupyter infrastructure. Calvin worked on adding flyte deck to papermill plugin that renders output html as a flyte deck automatically on setting a param. • @Sujith Samuel added a helm chart for on-prem which has the keycloak IDP and TLS ingress config. All contributors of the month are available on flyte.org.

Hi, I need to run some tasks on a different execution host, namely IBM LSF. I am able to run the docker container there, and thus I can start the flyte built container, and so inputs are consumed from s3 and then pyflyte-execute runs the task there. Currently I'm not extending the flyte backend, rather I'm using a python decorator for these tasks, so there is a node on Flyte which is waiting for the execution on LSF side to finish. My question is, is there a way to let the serialized output from the container which ran on LSF become the outputs of the node which runs on flyte (with the decorated task), or will I have to deserialize on that flyte node somehow? I would like to not consume any extra memory on flyte side

Is there a particular reason that named executions are capped at 20 characters?

Error: rpc error: code = InvalidArgument desc = size of name exceeded length 20 : test-named-workflow-2

This appears to be hard-coded here: https://github.com/flyteorg/flyteadmin/blob/7b48c856e3a1e12c57f1abbf535bf6c29fa59d74/pkg/manager/impl/validation/execution_validator.go#L19. Would folks be open to bumping that to 64 (to match the max length for an argo workflow's name)

Hi everyone! We created a #random channel where you can post content that doesn’t fit anywhere else — memes, articles, bootcamps, or just about anything. Hop in!😮pen-door:

Team, when i am executing this command pyflyte run --remote -p flytetester --image <AWC_ACCOUNT>.dkr.ecr.us-east-1.amazonaws.com/flyte-pyspark:latest flyte/workflows/spark_example.py my_spark --triggered_date 2022-08-29 getting below exception.

[3/3] currentAttempt done. Last Error: SYSTEM::Traceback (most recent call last): File "/opt/venv/lib/python3.8/site-packages/flytekit/exceptions/scopes.py", line 165, in system_entry_point return wrapped(*args, **kwargs) File "/opt/venv/lib/python3.8/site-packages/flytekit/core/base_task.py", line 463, in dispatch_execute new_user_params = self.pre_execute(ctx.user_space_params) File "/opt/venv/lib/python3.8/site-packages/flytekitplugins/spark/task.py", line 124, in pre_execute self.sess = sess_builder.getOrCreate() File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/session.py", line 228, in getOrCreate sc = SparkContext.getOrCreate(sparkConf) File "/opt/spark/python/lib/pyspark.zip/pyspark/context.py", line 392, in getOrCreate SparkContext(conf=conf or SparkConf()) File "/opt/spark/python/lib/pyspark.zip/pyspark/context.py", line 146, in init self._do_init(master, appName, sparkHome, pyFiles, environment, batchSize, serializer, File "/opt/spark/python/lib/pysSupport.java:471) at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleGet(OperationSupport.java:453) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.handleGet(BaseOperation.java:947) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.getMandatory(BaseOperation.java:221) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.get(BaseOperation.java:187) at io.fabric8.kubernetes.client.dsl.base.BaseOperation.get(BaseOperation.java:86) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$driverPod$1(ExecutorPodsAllocator.scala:79) at scala.Option.map(Option.scala:230) at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.<init>(ExecutorPodsAllocator.scala:78) at org.apache.spark.scheduler.cluster.k8s.KubernetesClusterManager.createSchedulerBackend(KubernetesClusterManager.scala:118) at org.apache.spark.SparkContext$.org$apache$spark$SparkContext$$createTaskScheduler(SparkContext.scala:2973) ... 14 more SYSTEM ERROR! Contact platform administrators.