I can't delete google compute instance in "console" - google-app-engine

I use node managed vm on google app engine. After I delete google compute instance at console.cloud.google.com , I see instance created automatically in "Operations". (This happens before, I used to delete instances at appengine.google.com which moved to "console" now.) How this happened? And How can I delete it?

When the instance can not be deleted it is because, either when creating an instance the protection against the deletion was checked or because after creating an instance we activated the protection from Gcloud with the following command:
$ gcloud compute instances update < INSTANCE_PATH> --deletion-protection
Sample of Instance path: projects/your-project-265315/zones/us-central1-a/instances/your-instance-v3
Solution:
Active Google Cloud Shell:
Precondition:
Request permission for the user to access the machine (regardless of the SSH connection to the instance) to avoid 403: Insufficient Permission.
$ gcloud auth login
If the deletion of the instance is protected, eliminate the protection.
$ gcloud compute instances update <INSTANCE_PATH> --no-deletion-protection
Then we delete the instance by selecting the zone correctly.
$ gcloud compute instances delete <instance-path>
GL
Preventing accidental vm deletion
Auth login

You have to delete deployed version for Flexible VM. Since it's only one version, you have to deploy another one, for standard vm.
Most simple solution would be to deploy an empty version, w/o any code, just one static file. To do that create following app.yaml:
module: default
runtime: python27
api_version: '1.0'
threadsafe: true
handlers:
- url: /
static_files: index.html
upload: index.html
resources:
cpu: 0.1
memory_gb: 0.5
disk_size_gb: 10
put an empty index.html in same dir. And deploy it using:
gcloud preview app deploy app.yaml
After this, you'll be able to route all traffic to this dummy version, and then delete previous version deployed for Flexible VM.

You need to delete the module from your app description. Otherwise App Engine will keep spinning new instances in accordance with the scale settings in your module description.

Related

How can I pass a variable from github actions workflow to a GAE app.yaml file?

I have a django project I want to put into maintenance mode before I update (migrate) the database.
So, my github workflow
deploys my project with a variable MAINTENANCE_MODE set to true. This new deploy I understand will reboot any running instances, ensuring all instances only show my 'Site down for maintenance' 503.html page and won't be interacting with the database.
I launch a django VM in github actions, run my migrate, run collectstatic.
I set MAINTENANCE_MODE to false, I deploy a second time. This will re-enable production server with new code that now accesses a migrated database.
My question is, I am trying to use a single app.yaml file for both deploys. To pass the MAINTENANCE_MODE variable from github actions workflow to the app.yaml file, how can I do this?
I know you can import secrets like so:
runtime: python38
instance_class: F2
env_variables:
DB_URL: $ {{ secrets.DB_URL }}
But I don't know how to modify a secret in the workflow. Perhaps its not a secret but some other type of variable one can set in the workflow and access in the app.yaml?
So it appears that Google App Engine's yaml files do not support dynamic environment variable substitution. Static substitution (like using github's secrets) works, because github compiles the file with the github environment variable before the workflow runs, but there's no clear way to modify a file with a variable that is going to change during a workflow.
A method however that does work is to compile a new GAE yaml file during the workflow. Here's what I came up with in the end...
- name: Put in Maintenance mode
run: |
MAINTENANCE_MODE=1 envsubst < app_eng_staging.yml.template > app.yaml
cat app.yaml
gcloud app deploy --project staging-project --quiet
- name: Collectstatic and migrate
env:
RUNNING_ENVIRONMENT: 'Staging_Server'
DJANGO_DEBUG: 'False'
run: |
pipenv run python manage.py collectstatic --noinput
pipenv run python manage.py migrate
- name: Turn off Maintenance and Deploy
run: |
MAINTENANCE_MODE=0 envsubst < app_eng_staging.yml.template > app.yaml
gcloud app deploy --project staging-project --quiet
The trick is to use the linux envsubst command. We start with a app_eng_staging.yml.template file, which looks like so:
runtime: python38
instance_class: F2
env_variables:
RUNNING_ENVIRONMENT: 'Staging_Server'
StagingServerDB: $ {{ secrets.STAGINGSERVER_DB }}
MAINTENANCE_MODE: ${MAINTENANCE_MODE}
FRONTEND_URL: $ {{ secrets.STAGING_FRONTEND_URL }}
envsubst then populates ${MAINTENANCE_MODE} with the value 1 and the result is saved to a new file app.yaml.
After we finish working with out database migration, we can use envsubst to create a new app.yaml with MAINTENANCE_MODE set to zero (off), and re-deploy.
Neat huh?
There is a feature in GitHub Action for this called "GAE environment variable compiler"
Please read here

gcloud app deploy does not terminate even when service is running

I am deploying a node.js server to Google App Engine from Bitbucket pipeline environment and the last command in the script is: gcloud -q app deploy app.yaml --no-promote --verbosity=debug
The logs show that the service is deployed successfully but the script is not terminating, this is the last part of the log:
> DEBUG: Reading GCS logfile: 206 (read 10 bytes) PUSH DONE DEBUG:
> Operation [...] complete. Result: {...} DEBUG: Reading GCS logfile:
> 416 (no new content; keep polling)
> -------------------------------------------------------------------------------- DEBUG: Converted YAML to JSON: "{...}" DEBUG: Operation [...] not
> complete. Waiting to retry. Updating service [default] (this may take
> several minutes)... .DEBUG: Operation [...] not complete. Waiting to
> retry. ......DEBUG: Operation [...] not complete. Waiting to retry.
> .......DEBUG: Operation [...] not complete. Waiting to retry.
> ......DEBUG: Operation [...] not complete. Waiting to retry.
> .......DEBUG: Operation [...] not complete. Waiting to retry.
> .......DEBUG: Operation [...] not complete. Waiting to retry.
I tried to add readiness_check and liveness_check to app.yml but it didn't change the behaviour.
readiness_check:
path: "/api/public/logout"
check_interval_sec: 5
timeout_sec: 4
failure_threshold: 2
success_threshold: 2
app_start_timeout_sec: 300
liveness_check:
path: "/api/public/logout"
check_interval_sec: 30
timeout_sec: 4
failure_threshold: 2
success_threshold: 2
The main unknown here is what criteria does gcloud app deploy uses to determine termination condition?
Also, is there any bypass to this problem?
Update
The problem happens also when running the gcloud app deploy command from local environment (my laptop).
The problem does NOT happen when removing the --no-promote flag.
The gcloud app deploy command expects a well-formed and valid app.yml file, this is what determines its termination condition.
As you confirmed the deployment worked without the --no-promote flag, it could mean that something in the configuration expects the application to be already deployed and running, thus preventing the script to complete.
Another possible cause would be that the Google Cloud SDK version specified in bitbucket-pipelines.yml is an older one. Make sure you work with the latest. This consideration applies extensively to all dependencies in package.json, which might be conflicting with one another, especially when using older versions of Node.js.
This guide can help at building a sound configuration for Bitbucket-based deployments; although the example given is with Python, it might as well be used as a template for processing a Node.js pipeline.
Nb. in this solution, the Google Cloud SDK version is an older one (127.0.0), which will make this deployment fail, so it should be replaced with the latest (228.0.0 or higher). Also the guide omits another required API activation: Cloud Build API. I've notified the team to amend the solution.
I've tested several scenarios with a simple Node.js server, and could not reproduce the issue. Check my Github repository for the code.
For further help on this topic, please provide more hints, such as the content of the app.yml, bitbucket-pipelines.yml, and package.json files, as well as a description of the state of App Engine (services, versions).
In order to deploy the test repository to App Engine from Bitbucket, make sure the following is done on the project:
Enable API's:
App Engine Admin
Cloud Build
Create a Service Account with following permissions, and generate an API Key:
App Engine: Admin
Cloud Build: Editor
Storage: Object Admin

Elasticsearch deployment on google app engine flex

Is it possible to deploy Elasticsearch on App engine flex environment using a docker image.
I have tried the following
My files on the local machine
Folder : elasticsearch
app.yaml
Dockerfile
docker-entrypoint.sh
config folder(containing elasticsearch.yml)file
Contents of app.yaml
runtime: custom
env: flex
Dockerfile and docker-entrypoint.sh copied from https://github.com/GoogleCloudPlatform/elasticsearch-docker/tree/master/5/5.2.0
Modifications to the Dockerfile
replaced EXPOSE 9200 9300 to EXPOSE 8080
Modification to the elasticsearch.yml
cluster.name: "beaconinside-docker-cluster"
path.data: /usr/share/elasticsearch/data
http.host: 0.0.0.0
http.port: 8080
discovery.zen.minimum_master_nodes: 1
I build a container using the docker file on my local machine
docker build -t elasticdemo .
Then, I run the container
docker run -p 8080:8080 elasticdemo
I am able to access elasticsearch on 0.0.0.0:8080
Problem:
I am trying to deploy elasticsearch as an app to Google app engine flex environment
gcloud app deploy app.yaml --version elasticdocker --project myproject
The deployment fails with the following error
Updating service [default]...failed.
ERROR: (gcloud.app.deploy) Error Response: [9]
I was expected elasticsearch to deploy as an app and be available on the deployed url.
Could you please provide pointers/help/suggestions with this approach?
While you can deploy ES to App Engine Flexible environment it's not particularly useful. The VMs hosting GAE Flexible containers are restarted regularly as part of maintenance and whatever data is stored on the local disk will be lost on restart. If you want to use local disk for long term storage, I'd suggest to deploy the GCE VM's (or alternatively use a solution from the GCP Marketplace) or deploy to GKE which supports persistent disks
As for the actual question: you probably don't have a health check handler and therefore App Engine Flexible environment doesn't consider your app healthy after deploying it. The error message is useless, I agree.
From the GAE Flexible docs for building custom images:
"A health check is an HTTP request to the URL /_ah/health. A healthy application should respond with status code 200."
Alternatively you can turn off health checks by adding into app.yaml
enable_health_check: False

How to deploy a GAE project in flexible environment without billing?

I've been developing some REST service using Flask and other third party libraries and I want to deploy it to GAE in the flexible environment. I usually deploy to the GAE standard environment but I wanted to try the new flexible environment. At the moment I wish to deploy to flexible environment without enabling billing, and the Google support assured me that it was possible to deploy over GAE flexible environment without enabling billing.
Running my code locally works fine, and have the following yaml file:
runtime: python
env: flex
entrypoint: gunicorn -b :$PORT whereismybus230.starter:app
runtime_config:
python_version: 3
So I created a new project on through the Google cloud console web page (as usual), and created a new gcloud profile on my local machine so I deploy it to this new project.
Then I run:
gcloud app deploy --verbosity=info
I get that a docker image is being build and at some point it will be pushed to a Compute Engine but it fails after a few minutes here:
Successfully built sophiabus230 aniso8601 future docopt itsdangerous MarkupSafe
Installing collected packages: Werkzeug, click, MarkupSafe, Jinja2, itsdangerous, Flask, jsonschema, pytz, six, python-dateutil, aniso8601, flask-restplus, beautifulsoup4, future, sophiabus230, coverage, requests, docopt, coveralls
Successfully installed Flask-0.12 Jinja2-2.9.4 MarkupSafe-0.23 Werkzeug-0.11.15 aniso8601-1.2.0 beautifulsoup4-4.5.3 click-6.7 coverage-4.3.4 coveralls-1.1 docopt-0.6.2 flask-restplus-0.9.2 future-0.16.0 itsdangerous-0.24 jsonschema-2.5.1 python-dateutil-2.6.0 pytz-2016.10 requests-2.12.5 six-1.10.0 sophiabus230-0.4
---> 3e3438680079
Removing intermediate container bd9f8ccb6f4a
Step 8 : ADD . /app/
---> bde0915f6720
Removing intermediate container e3193eb4ef70
Step 9 : CMD gunicorn -b :$PORT whereismybus230.starter:app
---> Running in 022d38d769f8
---> 36893d0a549a
Removing intermediate container 022d38d769f8
Successfully built 36893d0a549a
PUSH
The push refers to a repository [us.gcr.io/whereismy230/appengine/default.20170120t131841]
e5f488ee94c5: Preparing
8d27ce27f03c: Preparing
3d5800d45c36: Preparing
06ba8a2a8ec3: Preparing
c0fb81dae3c6: Preparing
2e4eabdbeed3: Preparing
b5d474284f52: Preparing
c307273999be: Preparing
d73750730c30: Preparing
63bbaf04cf0b: Preparing
badb9b2d625b: Preparing
40c928fd4dcc: Preparing
dfcf8dbe47e1: Preparing
6d820e13990c: Preparing
2e4eabdbeed3: Waiting
b5d474284f52: Waiting
c307273999be: Waiting
d73750730c30: Waiting
63bbaf04cf0b: Waiting
badb9b2d625b: Waiting
40c928fd4dcc: Waiting
dfcf8dbe47e1: Waiting
6d820e13990c: Waiting
denied: Unable to create the repository, please check that you have access to do so.
The push refers to a repository [us.gcr.io/whereismy230/appengine/default.20170120t131841]
...
ERROR: (gcloud.app.deploy) Error Response: [2] Build failed; check build logs for details
Using the IAM service, I made sure my account was the owner of the project, and even checked all permissions.
Since the flexible environment relies on the Compute Engines (VMs), I tried to check from the web page and it's telling me that I need to enable billing to be able to use this functionality.
Am I doing something wrong ?
Thanks !
From App Engine Pricing:
Instances within the standard environment have access to a daily
limit of resource usage that is provided at no charge defined by a set
of quotas. Beyond that level, applications will incur charges as
outlined below. To control your application costs, you can set a
spending limit. To estimate costs for the standard environment,
use the pricing calculator.
Go to the pricing calculator
For instances within the flexible environment, services and APIs are
priced as described below.
And from Flexible environment instances:
Applications running in the App Engine flexible environment are
deployed to virtual machine types that you specify. This table
summarizes the hourly billing rates of the various computing
resources:
US
Resource Unit Unit cost
vCPU per core hour $0.0526
Memory per GB hour $0.0071
Persistent disk per GB per month $0.0400
Unlike the standard env, the flex env has no free quota. Which is inline with your observation that the developer console requires billing to be enabled to run GAE flex instances.
Without billing enabled you might be able to deploy your app (but without actually launching a GAE instance for it, so unsure of its usefulness, since you want to try it) by using the --no-promote option:
--promote
Promote the deployed version to receive all traffic.
True by default. To change the default behavior for your current
environment, run:
$ gcloud config set app/promote_by_default false
Overrides the default promote_by_default property value for this
command invocation. Use --no-promote to disable.
Side note: when you encounter problems you may also want to use --verbosity=debug to potentially get more relevant info about the failures.

Time out error when trying to create Google managed vm

I'm trying to create a managed vm for my node 4 application using google custom runtime.
I created the following Dockerfile:
FROM node:4.2.1
ENV PORT 8080
ADD package.json package.json
RUN npm install
ADD . .
CMD [ "npm", "start" ]
Along with this app.yaml:
# [START runtime]
runtime: custom
vm: true
api_version: 1
# [END runtime]
health_check:
enable_health_check: false
skip_files:
- ^(.*/)?#.*#$
- ^(.*/)?.*~$
- ^(.*/)?.*\.py[co]$
- ^(.*/)?.*/RCS/.*$
- ^(.*/)?\..*$
- ^(.*/)?.*/node_modules/.*$
- ^(.*/)?.*\.log$
I deploy the app using gcloud preview command:
gcloud preview app deploy app.yaml --promote
It seems like the docker is being built correctly but the at the end of the process I get this message:
Copying files to Google Cloud Storage...
Synchronizing files to [gs://staging.my-project-id.appspot.com/].
Updating module [default]...\Deleted [https://www.googleapis.com/compute/v1/projects/my-project-id/zones/us-central1-f/instances/gae-builder-vm-20151030t142257].
Updating module [default]...failed.
ERROR: (gcloud.preview.app.deploy) Error Response: [4] Timed out creating VMs.
I have my deployment working now. I have had to troubleshoot the same problem before, for another project, but I didn't have the code on hand, so I had to work through the problems again.
The deployment ran smoothly up until the last steps, where updating the module would timeout. This made me think it was something to do with the application starting up on VM and not responding appropriately, so the final hook would time out.
You'll find a lot of information here - https://cloud.google.com/appengine/docs/managed-vms/config . I checked the following things:
logging - ensure that you are writing to the correct log file. See https://cloud.google.com/appengine/docs/managed-vms/custom-runtimes#logging
ensure you have a .dockerignore file and are skipping files in app.yaml so you are not asking the process to copy across unneeded node_modules or log files
turn off health checking if you are not using it, or ensure you have the correct express.js routes configured for it
check that your environment variables are set and match what GAE can use. This was my final step - GAE will let you bind to a VM port on 8080. I had to pass through a NODE_ENV flag in my app.yaml which told the app to use 8080 and not 3000.
Lift the resources of the GAE instance in app.yaml. I specified two logical CPUs and made the ram 2 gig.
Good luck.

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