amazon-eks-machine-learning-with-terraform-and-kubeflow | Distributed TensorFlow training using Kubeflow on Amazon EKS | AWS library
kandi X-RAY | amazon-eks-machine-learning-with-terraform-and-kubeflow Summary
kandi X-RAY | amazon-eks-machine-learning-with-terraform-and-kubeflow Summary
Distributed TensorFlow training using Kubeflow on Amazon EKS
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Trending Discussions on AWS
QUESTION
I am trying to get a Flask and Docker application to work but when I try and run it using my docker-compose up
command in my Visual Studio terminal, it gives me an ImportError called ImportError: cannot import name 'json' from itsdangerous
. I have tried to look for possible solutions to this problem but as of right now there are not many on here or anywhere else. The only two solutions I could find are to change the current installation of MarkupSafe and itsdangerous to a higher version: https://serverfault.com/questions/1094062/from-itsdangerous-import-json-as-json-importerror-cannot-import-name-json-fr and another one on GitHub that tells me to essentially change the MarkUpSafe and itsdangerous installation again https://github.com/aws/aws-sam-cli/issues/3661, I have also tried to make a virtual environment named veganetworkscriptenv
to install the packages but that has also failed as well. I am currently using Flask 2.0.0 and Docker 5.0.0 and the error occurs on line eight in vegamain.py.
Here is the full ImportError that I get when I try and run the program:
...ANSWER
Answered 2022-Feb-20 at 12:31I was facing the same issue while running docker containers with flask.
I downgraded Flask
to 1.1.4
and markupsafe
to 2.0.1
which solved my issue.
Check this for reference.
QUESTION
I'm trying to push my first docker image to ECR. I've followed the steps provided by AWS and things seem to be going smoothly until the final push which immediately times out. Specifically, I pass my aws ecr credentials to docker and get a "login succeeded" message. I then tag the image which also works. pushing to the ecr repo I get no error message, just the following:
...ANSWER
Answered 2022-Jan-02 at 14:23I figured out my issue. I wasn't using the correct credentials. I had a personal AWS account as my default credentials and needed to add my work profile to my credentials.
EDIT
If you have multiple aws profiles, you can mention the profile name at the docker login as below (assuming you have done aws configure --profile someprofile
at earlier day),
QUESTION
If i search the same question on the internet, then i'll get only links to vscode website ans some blogs which implements it.
I want to know that is jsconfig.json
is specific to vscode
or javascript/webpack
?
What will happen if we deploy the application on AWS / Heroku, etc. Do we have to make change?
...ANSWER
Answered 2021-Aug-06 at 04:10This is definitely specific to VSCode.
The presence of jsconfig.json file in a directory indicates that the directory is the root of a JavaScript Project. The jsconfig.json file specifies the root files and the options for the features provided by the JavaScript language service.
Check more details here: https://code.visualstudio.com/docs/languages/jsconfig
You don't need this file when deploy it on AWS/Heroku, basically, you can exclude this from your commit if you are using git repo, i.e., add jsconfig.json
in your .gitignore
, this will make your project IDE independent.
QUESTION
...Nothing to install, update or remove Generating optimized autoload files Class App\Helpers\Helper located in C:/wamp64/www/vuexylaravel/app\Helpers\helpers.php does not comply with psr-4 autoloading standard. Skipping. > Illuminate\Foundation\ComposerScripts::postAutoloadDump > @php artisan package:discover --ansi
ANSWER
Answered 2022-Feb-13 at 17:35If you are upgrading your Laravel 8 project to Laravel 9 by importing your existing application code into a totally new Laravel 9 application skeleton, you may need to update your application's "trusted proxy" middleware.
Within your app/Http/Middleware/TrustProxies.php file, update use Fideloper\Proxy\TrustProxies as Middleware to use Illuminate\Http\Middleware\TrustProxies as Middleware.
Next, within app/Http/Middleware/TrustProxies.php, you should update the $headers property definition:
// Before...
protected $headers = Request::HEADER_X_FORWARDED_ALL;
// After...
QUESTION
Using AWS Lambda functions with Python and Selenium, I want to create a undetectable headless chrome scraper by passing a headless chrome test. I check the undetectability of my headless scraper by opening up the test and taking a screenshot. I ran this test on a Local IDE and on a Lambda server.
Implementation:I will be using a python library called selenium-stealth and will follow their basic configuration:
...ANSWER
Answered 2021-Dec-18 at 02:01WebGL is a cross-platform, open web standard for a low-level 3D graphics API based on OpenGL ES, exposed to ECMAScript via the HTML5 Canvas element. WebGL at it's core is a Shader-based API using GLSL, with constructs that are semantically similar to those of the underlying OpenGL ES API. It follows the OpenGL ES specification, with some exceptions for the out of memory-managed languages such as JavaScript. WebGL 1.0 exposes the OpenGL ES 2.0 feature set; WebGL 2.0 exposes the OpenGL ES 3.0 API.
Now, with the availability of Selenium Stealth building of Undetectable Scraper using Selenium driven ChromeDriver initiated google-chrome Browsing Context have become much more easier.
selenium-stealthselenium-stealth is a python package selenium-stealth to prevent detection. This programme tries to make python selenium more stealthy. However, as of now selenium-stealth only support Selenium Chrome.
Code Block:
QUESTION
I was using pyspark on AWS EMR (4 r5.xlarge as 4 workers, each has one executor and 4 cores), and I got AttributeError: Can't get attribute 'new_block' on . Below is a snippet of the code that threw this error:
...
ANSWER
Answered 2021-Aug-26 at 14:53I had the same error using pandas 1.3.2 in the server while 1.2 in my client. Downgrading pandas to 1.2 solved the problem.
QUESTION
Just today, whenever I run terraform apply
, I see an error something like this: Can't configure a value for "lifecycle_rule": its value will be decided automatically based on the result of applying this configuration.
It was working yesterday.
Following is the command I run: terraform init && terraform apply
Following is the list of initialized provider plugins:
...ANSWER
Answered 2022-Feb-15 at 13:49Terraform AWS Provider is upgraded to version 4.0.0 which is published on 10 February 2022.
Major changes in the release include:
- Version 4.0.0 of the AWS Provider introduces significant changes to the aws_s3_bucket resource.
- Version 4.0.0 of the AWS Provider will be the last major version to support EC2-Classic resources as AWS plans to fully retire EC2-Classic Networking. See the AWS News Blog for additional details.
- Version 4.0.0 and 4.x.x versions of the AWS Provider will be the last versions compatible with Terraform 0.12-0.15.
The reason for this change by Terraform is as follows: To help distribute the management of S3 bucket settings via independent resources, various arguments and attributes in the aws_s3_bucket
resource have become read-only. Configurations dependent on these arguments should be updated to use the corresponding aws_s3_bucket_*
resource. Once updated, new aws_s3_bucket_*
resources should be imported into Terraform state.
So, I updated my code accordingly by following the guide here: Terraform AWS Provider Version 4 Upgrade Guide | S3 Bucket Refactor
The new working code looks like this:
QUESTION
I have an ECS task running on Fargate on which I want to run a command in boto3 and get back the output. I can do so in the awscli just fine.
...ANSWER
Answered 2022-Jan-04 at 23:43Ok, basically by reading the ssm session manager plugin source code I came up with the following simplified reimplementation that is capable of just grabbing the command output:
(you need to pip install websocket-client construct
)
QUESTION
I am not using AWS AppSync for this app. I have created Graphql schema, I have made my own resolvers. For each create, query, I have made each Lambda functions. I used DynamoDB Single table concept and it's Global secondary indexes.
It was ok for me, to create an Book item. In DynamoDB, the table looks like this: .
I am having issue with the return Graphql queries. After getting the Items
from DynamoDB table, I have to use Map function then return the Items
based on Graphql type
. I feel like this is not efficient way to do that. Idk the best way query data. Also I am getting null both author and authors query.
This is my gitlab-branch.
This is my Graphql Schema
...ANSWER
Answered 2022-Jan-09 at 17:06TL;DR You are missing some resolvers. Your query resolvers are trying to do the job of the missing resolvers. Your resolvers must return data in the right shape.
In other words, your problems are with configuring Apollo Server's resolvers. Nothing Lambda-specific, as far as I can tell.
Write and register the missing resolvers.GraphQL doesn't know how to "resolve" an author's books, for instance. Add a Author {books(parent)}
entry to Apollo Server's resolver map. The corresponding resolver function should return a list of book objects (i.e. [Books]
), as your schema requires. Apollo's docs have a similar example you can adapt.
Here's a refactored author
query, commented with the resolvers that will be called:
QUESTION
I've run into this issue today, and it's only started today. Ran the usual sequence of installs and pushes to build the app...
...ANSWER
Answered 2021-Nov-20 at 19:28I am following along with the Amplify tutorial and hit this roadblock as well. It looks like they just upgraded the react components from 1.2.5 to 2.0.0 https://github.com/aws-amplify/docs/pull/3793
Downgrading ui-react
to 1.2.5 brings back the AmplifySignOut and other components used in the tutorials.
in package.json:
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Install amazon-eks-machine-learning-with-terraform-and-kubeflow
In eks-cluster directory, execute: ./install-kubectl-linux.sh to install kubectl on Linux clients. For non-linux operating systems, install and configure kubectl for EKS, and install aws-iam-authenticator and make sure the command aws-iam-authenticator help works.
Install Terraform. Terraform configuration files in this repository are consistent with Terraform v0.13.0 syntax.
In eks-cluster/terraform/aws-eks-cluster-and-nodegroup folder, execute: terraform init The next command requires an Amazon EC2 key pair. If you have not already created an EC2 key pair, create one before executing the command below: terraform apply -var="profile=default" -var="region=us-west-2" -var="cluster_name=my-eks-cluster" -var='azs=["us-west-2a","us-west-2b","us-west-2c"]' -var="k8s_version=1.19" -var="key_pair=xxx"
Helm is package manager for Kubernetes. It uses a package format named charts. A Helm chart is a collection of files that define Kubernetes resources. Install helm version 3.x or later according to instructions here.
In the charts folder, deploy Kubeflow MPIJob CustomResouceDefintion using mpijob chart:.
In the charts folder, deploy Kubeflow MPIJob CustomResouceDefintion using mpijob chart: helm install --debug mpijob ./mpijob/ # (Helm version 3.x)
You have three options for training Mask-RCNN model: a) To train TensorPack Mask-RCNN model, customize values.yaml in the charts/maskrcnn directory. At a minimum, set image to Tensorpack Mask-RCNN training image ECR URI you built and pushed in a previous step. Set shared_fs and data_fs to efs, or fsx, as applicable. Set shared_pvc to the name of the k8s persistent volume claim you created in relevant k8s namespace. To test the trained model using a Jupyter Lab notebook, customize values.yaml in the charts/maskrcnn/charts/jupyter directory. At a minimum, set image to Tensorpack Mask-RCNN testing image ECR URI you built and pushed in a previous step. b) To train AWS Mask-RCNN optimized model, customize valuex.yaml in charts/maskrcnn-optimized directory. At a minimum, set image to the AWS Mask-RCNN ECR training image URI you built and pushed in a previous step. Set shared_fs and data_fs to efs, or fsx, as applicable. Set shared_pvc to the name of the k8s persistent volume claim you created in relevant k8s namespace. To test the trained model using a Jupyter Lab notebook, customize values.yaml in the charts/maskrcnn-optimized/charts/jupyter directory. At a minimum, set image to AWS Mask-RCNN testing image ECR URI you built and pushed in a previous step. c) To create a brand new Helm chart for defining a new MPIJOb, copy maskrcnn folder to a new folder under charts. Update the chart name in Chart.yaml. Update the namespace global variable in values.yaml to specify a new K8s namespace.
In the charts folder, install the selected Helm chart, for example: helm install --debug maskrcnn ./maskrcnn/ # (Helm version 3.x)
Execute: kubectl get pods -n kubeflow to see the status of the pods
Execute: kubectl logs -f maskrcnn-launcher-xxxxx -n kubeflow to see live log of training from the launcher (change xxxxx to your specific pod name).
Model checkpoints and logs will be placed on the shared_fs file-system set in values.yaml, i.e. efs or fsx.
If you used the quick start option above to create the EKS cluster and worker node group, then in eks-cluster/terraform/aws-eks-cluster-and-nodegroup fodler, execute terraform destroy with the same arguments you used with terraform apply above.
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