Ive been following the documentation (https://cloud.google.com/endpoints/docs/openapi/get-started-cloud-run#configure_esp)
I am able to load an image (Hello example), create endpoints, and run it as a service.....however, whenever I follow the process to migrate the working services to ESPv2, I get the following:
{"message":"upstream request timeout","code":504}
I've tried this on two different services. Any thoughts/ideas?
Thanks,
Steve
I have solved this issue. I was not aware that ESPv2 is only a proxy that needs to co-exist and point to the original backend service.
As soon as I created a separate service, everything worked.
Related
I've made a pretty simple web application which has a REST API backend service written in Python/Django and a FE service written in JS/React. Both parts are containerized and can be launched locally via docker-compose. They are situated in separate github repositories, and every time a new tag is pushed to the corresponding repo, an image is built and pushed to the corresponding ecr repo via github actions. Until that point everything works smoothly, but the problem is that, I don't know how to properly automate the deployment process to the test and production environments. The goal is to have those environments as similar as possible.
My current solution for test env is to simply upload docker-compose file to the ec2 instance via github actions, then manually run the docker-compose command, which pulls images from ecr.
Even though it's a simple solution, it's not very scalable or automated and requires some work to be done in order to update an application. The desired flow is to have a manual GitHub action in each repository, which would deploy either BE or FE to the test or prod environment without any need to ssh into the server and do any other manipulations with docker.
I was looking at ECS, but it seems that it's a solution for bigger apps, which need several or more instances to run. I want my app to be used by many users, but I'm not sure, when it will happen. So maybe i should stick to something less complicated than ECS. Are there any simpler solutions, which i am missing? Like Elastic beanstack or something from any other provider?
I will be happy to receive a feedback on anything I wrote in this post, thanks!
I am trying to use a development Endpoint to interactively run and edit ETL scripts but there seems to some issues in the development endpoint just after creating it as i am getting errors in scala/python REPL and also unable to do SSH tunnel to remote interpreter.
Let me explain what i did exactly - I created a development endpoint in the AWS console with all the default configurations. While creating the development endpoint i only provided three things 'Development endpoint name' and 'IAM Role' and my 'pub ssh key'. This is how it looks after creation
Then Right After creating the endpoint i am connecting to the spark/python REPL, I am able to connect to them successfully but within couple of minutes of connecting, the REPL starts throwing errors without writing a single line of code. This is happening in all the REPL present in the development endpoints.
Also When I am trying to do SSH tunneling to remote interpreter to connect my Local Zeppelin Notebook it is throwing - "bind: Cannot assign requested address".
Couple of things that are working though -
Able to do ssh to the endpoint.
Created a Sagemaker notebook in the AWS glue that is attached to this development endpoint and this notebook seems to be working fine, although surely it is adding an additional cost and i don't want to continue using it.
Can anyone please help what am i doing wrong? Am I missing any important steps that is needed to be done on the machine right after creating the development endpoint?
Thanks in Advance!
Not very sure about this error but if you are using it smaller datasets then probably you would like to use Docker implementation as it will not add any additional cost and you can go on with your developments.
You can refer this blog on how to set it up
https://towardsdatascience.com/develop-glue-jobs-locally-using-docker-containers-bffc9d95bd1
I don't know much about web development and cloud computing. From what I've read when using Cloud functions as the webhook service for dialogflow, you are limited to write code in just 1 source file. I would like to create a real complex dialogflow agent, so It would be handy to have an organized code structure to make the development easier.
I've recently discovered Cloud run which seems like it can also handle webhook requests and makes it possible to develop a complex code structure.
I don't want to use Cloud Run just because it is inconvenient to write everything in one file, but on the other hand it would be strange to have a cloud function with a single file with thousands of lines of code.
Is it possible to have multiple files in a single cloud function?
Is cloud run suitable for my problem? (create a complex dialogflow agent)
Is it possible to have multiple files in a single cloud function?
Yes. When you deploy to Google Cloud Functions you create a bundle with all your source files or have it pull from a source repository.
But Dialogflow only allows index.js and package.json in the Built-In Editor
For simplicity, the built-in code editor only allows you to edit those two files. But the built-in editor is mostly just meant for basic testing. If you're doing serious coding, you probably already have an environment you prefer to use to code and deploy that code.
Is Cloud Run suitable?
Certainly. The biggest thing Cloud Run will get you is complete control over your runtime environment, since you're specifying the details of that environment in addition to the code.
The biggest downside, however, is that you also have to determine details of that environment. Cloud Funcitons provide an HTTPS server without you having to worry about those details, as long as the rest of the environment is suitable.
What other options do I have?
Anywhere you want! Dialogflow only requires that your webhook
Be at a public address (ie - one that Google can resolve and reach)
Runs an HTTPS server at that address with a non-self-signed certificate
During testing, it is common to run it on your own machine via a tunnel such as ngrok, but this isn't a good idea in production. If you're already familiar with running an HTTPS server in another environment, and you wish to continue using that environment, you should be fine.
This is my first time deploying an application. I have some idea about it but I am not sure if it is correct. How do I go about deploying a play application on google cloud?
1) I have created a package using dist command. I have the zip file now on my local pc. https://www.playframework.com/documentation/2.5.x/Deploying
2) Do I first need to create a compute resource on gcp? What configuration shall I use for the vm? My app is still in test phase so there are no external users at the moment
3) I suppose play uses netty web server. So do I need to install netty on the compute resource? I have looked online a bit but can't find a resource on how to deploy an application on netty.
deploy an application on netty
Netty is not a web server/application server, but an IO framework which can be used to build web servers or any high-performant IO applications.
If you really want to use netty, you need to write an HTTP server yourself, or just use an HTTP framework built on netty.
If you want to build an application using netty, have a look at the examples on https://github.com/netty/netty/tree/4.1/example/src/main/java/io/netty/example/
Deploying a container to the Cloud using Google Cloud Platform and Kubernetes Engine
Kubernetes is a way of orchestrating containers in the Cloud, enabling you to do things like auto-scale, fast deploys and manage running versions of containers. You simply create a container and upload it to a container repository. In this example I used Google’s Container Registry, it’s really simple to use and works brilliantly with their Kubernetes implementation.
follow this tutorial might help you with this
https://medium.com/beyond/deploying-a-container-to-the-cloud-using-google-cloud-platform-and-kubernetes-engine-10d8ee3aba86
I am looking into Cloud Run to host my new app, and I am wondering if it is possible to generate a separate URL for each git branch.
I use Netlify to host my other app. When it is connected to GitHub (or other VCS services), it builds the source code in a branch and deploy it to a URL that is specific to the branch.
Can it be done easily or do I have to write some logic?
Or do you think AWS amplify or some other services are of better fit?
The concept of Cloud Run and URLs is quite simple:
https://<service-name>-<project hash>.<region>.run.app
If your project and region are the same for all the branches, you simply have to deploy a different service for each branch to get a different URL.
That was for Cloud Run. Now, I'm not sure that Netlify is compliant with Cloud Run. I found no documentation on this.
This answer won't be directly useful to you but I think it's relevant and worth mentioning
The open source Knative API (and implementation actually exposes a "tag" feature while splitting the traffic between multiple revisions: https://github.com/knative/docs/blob/master/docs/serving/spec/knative-api-specification-1.0.md#traffictarget
This feature is not currently supported on Cloud Run fully managed, but it will be.
By tagging releases this way, you could define tag: v1 and tag: v2 in your traffic configuration, and you would get new URLs like:
https://v1-SERVICE_NAME...run.app
https://v2-SERVICE_NAME...run.app
that directly go to these specific versions.
And the interesting thing is, these revisions you specified in the traffic: block of the Service object do not have to receive any traffic (you can say traffic percentage: 0) but it would still create a domain name like I showed above to the inactive revisions of your app.
So when Cloud Run fully-managed supports tag fields, you can actually achieve this, although it will be less out-of-the-box experience than Netlify.