curved-petabyte-84246
10/30/2023, 6:03 PM<http://cr.flyte.org/flyteorg/flytekit:py3.10-1.10.1b0|cr.flyte.org/flyteorg/flytekit:py3.10-1.10.1b0>
and I don't know where the list of available images.
2. I wasn't able to configure nodes with a private subnet as described in the walkthrough.
I created the roles described under 01. I then moved to create a cluster. This step assumes "API server endpoint access - public and private". I'm not entirely sure what this is referring to. An EKS cluster can be configured for "public and private". But this can only be set after the cluster is created.
I created a VPC with 2 public and 2 private subnets, and used them when creating the EKS cluster via the given command line.
NODEGROUP - I followed the guide but the nodegroups were NOT created successfully. If I selected all the 4 subnets upon creation, the nodegroup was trying to randomly use 1 when creating nodes. The nodes created on the private subnet couldn't join the EKS cluster. I moved to using only the public subnets and the nodes were starting OK.
The next steps of creating the bucket and databases went through OK. On to the deployment part -
I downloaded the starter yaml (which was missing the database.username
) and deployed Flyte. It was successful, placing 1 pod on the public node.
I noticed that liveness probe failed and then noticed the configuration was wrong (in the chart itself in your repo) - specifying "http" as the port, instead of 8088. I added this configuration on my end. Lastly, I ran port forwarding (needed to run 2 instances because http and grpc are defined as separate services) and successfully accessed Flyte console and triggered a workflow. However, the pod wasn't able to schedule because it requested 2 cpu - sounds like way too much! how can it be configured per task? if at all?
I increased the node size and then was able to schedule but now I'm receiving "containers with unready status: [f830d928e559a4ba7be9-n0-0]|Back-off pulling image "cr.flyte.org/flyteorg/flytekit:py3.10-1.10.1b0" error.proud-answer-87162
10/30/2023, 6:07 PMcurved-petabyte-84246
10/30/2023, 6:14 PMcurved-petabyte-84246
10/30/2023, 6:15 PMproud-answer-87162
10/30/2023, 6:32 PMflytectl update task-resource-attribute --attrFile taskconfig.yaml
where taskconfig.yaml
is:
domain: development
project: flyte-az
defaults:
cpu: "1"
memory: "1Gi"
limits:
cpu: "1"
memory: "1Gi"
average-finland-92144
10/30/2023, 7:17 PMaverage-finland-92144
10/30/2023, 7:19 PMcurved-petabyte-84246
10/31/2023, 11:05 AMcurved-petabyte-84246
10/31/2023, 11:06 AMcurved-petabyte-84246
10/31/2023, 1:05 PMaverage-finland-92144
10/31/2023, 3:54 PM@task(requests=Resources(cpu='2', mem='6Gi'))
For projects, you'd use the task-resource-attribute
and for platform-wide (which controls the defaults any Task can request), you can set it in your values file under `configmap`:
Example
task_resource_defaults:
task_resources:
defaults:
cpu: 1000m
memory: 1000Mi
storage: 1000Mi
limits:
storage: 2000Mi
proud-answer-87162
10/31/2023, 4:14 PMaverage-finland-92144
10/31/2023, 4:19 PMFlyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.
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