I have a telegram bot with a Postgres DB hosted on Heroku Free dyno. In one stage of my code, I want to save pickled files permanently so that I can access them later. Storing it on a table doesn't feel like a nice idea as it is a nested class with a variable number of inputs.
Problem is that Heroku deletes these files frequently or at least on each restart or push. Is there any way to tackle this problem?
You have to use external services such as AWS S3, GCP Cloud Storage (Buckets), Azure Blob Storage etc.. for that. Or you may consider using an addon such as Felix Cloud Storage, Cloud Cube, Bucketeer, HDrive for easy integration.
Here is what the documentation states:
The Heroku filesystem is ephemeral - that means that any changes to
the filesystem whilst the dyno is running only last until that dyno is
shut down or restarted. Each dyno boots with a clean copy of the
filesystem from the most recent deploy. This is similar to how many
container based systems, such as Docker, operate.
In addition, under normal operations dynos will restart every day in a
process known as "Cycling".
These two facts mean that the filesystem on Heroku is not suitable for
persistent storage of data. In cases where you need to store data we
recommend using a database addon such as Postgres (for data) or a
dedicated file storage service such as AWS S3 (for static files). If
you don't want to set up an account with AWS to create an S3 bucket we
also have addons here that handle storage and processing of static
assets https://elements.heroku.com/addons
Related
Is Google cloud Engine App filesystem ephemerial such as heroku (this link is another stackoverflow question that explains how the ephemerial filesystem works) ?
l would like to deploy a python-django project there and to know if I could use the built-in django database file.
Heroku’s filesystem is both ephemeral and dyno-local, for e.g. if you try to view a saved file via heroku run bash you won't see it (that runs on a one-off dyno, not a running web dyno) and it will be lost within 24 hours due to automatic dyno restarts. You just need a database Heroku has a PostgreSQL service with a free tier that should do more than you need, or pick another data persistence addon.
Coming to App Engine,
App Engine Flexible (Managed VMs), is ephemeral (disk initialized on each VM startup). It scales across many containers so there's no promise that a file you write to one will be accessible later. You
can get away with dealing with some writing to some /tmp files
but not much more. You will be much better off writing any data to something like Cloud Datastore, Cloud SQL, Memcache, or
Cloud Storage.
The App Engine Standard filesystem is not ephemeral but it is
read-only. You cannot write to the filesystem. Python 2.7 and PHP 5.5 don't have write access to the disk whereas Java 8, Java 11, Node.js,Python 3, PHP 7, Ruby, Go 1.11, and Go 1.12+ only have read and write access to the /tmp directory.
You could use Google App Engine Blobstore or BlobProperty in
Datastore to store blobs/files. For using Blobstore (up to 2GB) see
this For using Datastore blobs (only up to 1MB) see this
So I have a bit of a issue, I want to use Heroku to host my flask web app, and then I also want to use Heroku pipeline to link to the GitHub repository where I am housing this project. The issue is that on my website I allow the user to upload files to the server, but I feel that If I were to update the GitHub repository I will lose all the files the user uploaded when the server reloads the new GitHub. I would like to know if this is a real issue and if so is there some way I could fix this?
Storing user-uploaded files to Heroku isn't a good idea because Heroku provides ephemeral filesystem.
The Heroku filesystem is ephemeral - that means that any changes to the filesystem whilst the dyno is running only last until that dyno is shut down or restarted. Each dyno boots with a clean copy of the filesystem from the most recent deploy. This is similar to how many container based systems, such as Docker, operate.
So even if you just restart your app, Users will lose their files. But they provide some alternate options to store these. As you are using python this Addon may help you.
Read More - https://help.heroku.com/K1PPS2WM/why-are-my-file-uploads-missing-deleted
I know that Heroku's dyno gets refreshed each time a deploy is made so is there anyway I can have my files persistent or there's no other way but use services like amazon S3? I use paperclip to handle file upload and most of the files will be in pdf.
It would be best to use S3 or another service.
Ephemeral filesystem
Each dyno gets its own ephemeral filesystem, with
a fresh copy of the most recently deployed code. During the dyno’s
lifetime its running processes can use the filesystem as a temporary
scratchpad, but no files that are written are visible to processes in
any other dyno and any files written will be discarded the moment the
dyno is stopped or restarted. For example, this occurs any time a dyno
is replaced due to application deployment and approximately once a day
as part of normal dyno management.
https://devcenter.heroku.com/articles/dynos#ephemeral-filesystem
I have an e-commerce Django website hosted in Heroku (free acc). I dynamically upload the image and price through the Django admin page. The images were showing up for one day, but from the next day, I am getting an "image not found (404)" error. What's the reason for this error?
Failed to load resource: the server responded with a status of 404 (Not Found)
You can't save (persistantly) media files into Heroku's local filesystem.
The Heroku filesystem is ephemeral - that means that any changes to
the filesystem whilst the dyno is running only last until that dyno is
shut down or restarted. Each dyno boots with a clean copy of the
filesystem from the most recent deploy. This is similar to how many
container based systems, such as Docker, operate.
In addition, under normal operations dynos will restart every day in a
process known as "Cycling".
These two facts mean that the filesystem on Heroku is not suitable for
persistent storage of data. In cases where you need to store data we
recommend using a database addon such as Postgres (for data) or a
dedicated file storage service such as AWS S3 (for static files). If
you don't want to set up an account with AWS to create an S3 bucket we
also have addons here that handle storage and processing of static
assets https://elements.heroku.com/addons
Reference: https://help.heroku.com/K1PPS2WM/why-are-my-file-uploads-missing-deleted
I have never used amazon web services so I apologize for the naive question. I am looking to run my code on a cluster as the quad-core architecture on my local machine doesn't seem to be doing the job. The documentation seems overwhelming and I don't even know which AWS services are going to be used for running my script on EC2. Would I have to use their storage facility (S3) because I guess if I have to run my script, I'm going to have to store it on the cloud in a place where the cluster instance has access to the files or do I upload my files somewhere else while working with EC2? If this is true is it possible for me to upload my entire directory which has all the contents of the files required by my application onto s3. Any guidance would be much appreciated. So I guess my question is do I have to use S3 to store my code in a place accessible by the cluster? If so is there an easy way to do it? Meaning I have only seen examples of creating buckets wherein one file can be transferred per bucket. Can you transfer an entire folder into a bucket?
If we don't require to use S3 then which other service should I use to give the cluster access to my scripts to be executed?
Thanks in advance!
You do not need to use S3, you would likely want to use EBS for storing the code if you need it to be preserved between instance launches. When you launch an instance you have the option to add an ebs storage volume to the drive. That drive will automatically be mounted to the instance and you can access it just like you would on any physical machine. ssh your code up to the amazon machine and fire away.