VOD File Creation with Open Source Cloud

In a previous blog post we provided a walk-through on how to setup video file transcoding using Open Source Cloud based on SVT Encore and supporting backend services. In this blog post we are extending the setup by adding the creation of video-on-demand streaming files to the pipeline.

In this solution we will add another open source project made available as a service. The Encore Packager is a backend service that creates the VOD file package. It consumes jobs from a Redis queue and creates the VOD file package and uploads the package to an S3 bucket. For the creation of the VOD file package the open source packager Shaka Packager is used. The red box in the diagram below shows what we will add to our solution.

Step 1: Create another Valkey queue

Valkey provides a Redis compatible key / value store and we will create another queue for the packaging jobs. Navigate to the Valkey service in Open Source Cloud and press “Create valkey”. Give the instance a name and press Create.

Note down the IP and port to the Valkey instance card and this is what will be the Redis URL that we will refer to later in this blog. In this example it would be redis://172.232.131.169:10511.

Step 2: Launch another Encore Callback Listener

We will now create a separate service that can be used to monitor a transcoding job in SVT Encore so we know when the file is ready to be packaged. Navigate to the Encore Callback Listener in the web user interface. Click on button “Create callback” and enter the name of the instance, Redis URL (above), URL to the SVT Encore instance that we created last time and the name of the queue. We will call this queue for “package” now.

Important the URL to the SVT Encore instance is without the trailing slash.

Step 3: Create Encore Packager service

We can now move on with creating the Encore Packager service. Enter the name of the instance, Redis URL, name of queue in Redis (Valkey), output S3 URL, OSC token and the AWS credentials for the output S3 bucket. In this example we will have the following values:

Then press Create and wait for the instance to be ready.

Step 4: Submit a job

Now we are ready to try transcoding and creating a VOD package that we have available on an S3 compatible storage. We will create signed URL to the video file we want to transcode. For example:

https://lab-testcontent-input.s3.eu-north-1.amazonaws.com/NO_TIME_TO_DIE_short_Trailer_2021.mp4?SIGNURLSTUFF

Navigate back to the SVT Encore service and press the menu item to open API docs again. Click on the POST /encoreJobs bar and button “Try it out” and enter the following JSON. Here we have changed the progressCallbackUri to point to our Encore Callback Listener for VOD packaging.

{
  "externalId": "blog",
  "profile": "program",
  "outputFolder": "/usercontent/",
  "baseName": "blog",
  "progressCallbackUri": "https://demo-vod.eyevinn-encore-callback-listener.auto.prod.osaas.io/encoreCallback",
  "inputs": [
    {
      "uri": "https://lab-testcontent-input.s3.eu-north-1.amazonaws.com/NO_TIME_TO_DIE_short_Trailer_2021.mp4?SIGNURL",
      "seekTo": 0,
      "copyTs": true,
      "type": "AudioVideo"
    }
  ]
}

And then press button Execute. Now a job is submitted and if you want to see the progress you can go to the Encore Callback Listener service and open the instance logs to check that it is receiving the callbacks.

When the transcoding process is completed it will place a job on the packaging queue that will be picked up by the Encore Packager service. And when the packaging job is completed you will in this example find a VOD package ready for streaming: https://lab.cdn.eyevinn.technology/osc/NO_TIME_TO_DIE_short_Trailer_2021/bb347d8e-c095-43dc-ba5f-914c7e74f13d/index.m3u8.



Conclusion

You now have a fully fledged video transcoding and packaging pipeline for preparing video files for streaming using ´SVT Encore with some supporting services. All based on open source and you don’t have to setup your own infrastructure for this to get started. If you later choose to do so you are free to do it as the code and everything demonstrated here is available as open source.

How Open Source Creators Can Earn Revenue Effortlessly Without Risk

Open source software has revolutionized the tech industry, allowing developers to share their work with the world and collaborate on innovative projects. However, one of the biggest challenges for open source creators is finding a sustainable way to monetize their efforts.

The Problem with Traditional Open Source Monetization
Traditionally, open source creators have struggled with monetization. While their projects may gain popularity and widespread use, turning that success into financial support often requires significant time and resources. Creators need to set up their own infrastructure, manage updates, and handle customer support, which can be daunting and detract from their core development work.

Introducing Eyevinn Open Source Cloud
Eyevinn Open Source Cloud changes the game by providing a platform where open source projects can be offered as a service.

This means that creators can focus on what they do best—developing innovative software—while Eyevinn handles the hosting. The best part? Revenue generated from these services is shared with the creators, providing a stream of income.

How It Works
Submit Your Repository: Open source creators can submit their GitHub repositories to Eyevinn Open Source Cloud. The platform turns repositories into software as a service (SaaS) offerings.

Revenue Sharing: Once the project is live on the platform, users can subscribe to the service. Creators earn a share of the revenue generated by their software without having to lift a finger.
No Lock-In: One of the key benefits of Eyevinn Open Source Cloud is that it does not lock creators or users into the platform. The source code remains open and can be moved to other infrastructures if needed.

Benefits for Open Source Creators
Effortless Monetization: Creators can earn revenue without the hassle of setting up and maintaining their own infrastructure.
Increased Usage: By lowering the barrier to entry, more users can adopt and provide feedback on the software, leading to continuous improvement.
Sustainable Business Model: The revenue-sharing model ensures that creators have a financial incentive to keep developing and enhancing their projects.

Conclusion
Eyevinn Open Source Cloud offers a way for open source creators to monetize their work effortlessly. By turning open source projects into managed services, creators can focus on innovation while enjoying a stream of revenue. If you are an open source creator looking for a sustainable way to support your work, Eyevinn Open Source Cloud is the solution you’ve been waiting for.
For more information, visit https://www.osaas.io/.

Scheduled MariaDB backup using GitHub action and job in Eyevinn OSC

This blog gives an example on how to run regular database backups of your MariaDB database where the result is uploaded to an S3 compatible bucket.

For the task to perform the database backup and upload the result to S3 we will be using an open source script that is made available in Eyevinn Open Source Cloud. To launch this on a regular basis we will use a scheduled GitHub workflow that uses Eyevinn OSC action to create the jobs in OSC.

Step 1: setup secrets

Navigate to the service called “MariaDB backup to S3” and select the tab “Service Secrets”.

Create a secret for the URL to the database you want to backup. In the screenshot above we have a secret for the MariaDB url that this blog is running on. A URL is in the form mariadb://root:[rootpassword]@[host]:[ip]/[database]

Then we need secrets for the credentials to the AWS S3 bucket where we will place the backup. In this example they are called “eyevinnawskeyid” and “eyevinnawssecret”.

Step 2: create a test job

To test that everything is setup correctly we will manually create a test job.

Press Create and verify that a backup is taken and the result ends up on the S3 bucket.

Step 3: create a GitHub workflow file

In this example we will be using a GitHub workflow schedule to create a backup job in Open Source Cloud.

This workflow uses the GitHub action Eyevinn OSC action available on the GitHub action marketplace.

Conclusion

This provided an example for how you can launch jobs for an open source project that is made available as a service in Eyevinn Open Source Cloud as a step in a GitHub workflow.

From Idea to Online Service in No Time: Leveraging AI and Eyevinn Open Source Cloud

As an entrepreneur, tech enthusiast, or developer, you know how daunting it can be to transform an idea into a functional web service. But with the combination of AI and the Eyevinn Open Source Cloud (https://www.osaas.io/), this journey becomes streamlined and efficient. In this post, I’ll share my experience of creating an online movie recommendation site—and how leveraging AI and Eyevinn Open Source Cloud made it possible in just a few hours.

The Idea: An Online Movie Recommendation Site

I had a simple idea: a website where users could enter a movie name and get two new movie recommendations, using the OpenAI API to generate suggestions. This seemed like a perfect project to test the capabilities of Eyevinn Open Source Cloud.



Step 1: Generating the Code with ChatGPT

To kick things off, I used ChatGPT to help create a Docker container with an HTML frontend and a Node.js backend that communicates with the OpenAI API. It requires an OpenAI API key to be entered when starting the Docker container. This approach let me rapidly build a prototype without needing to dive deep into intricate coding.

Step 2: Running the Code Locally

Next, I took the generated code and ran it locally on my Mac using VS Code, with the help of GitHub Copilot. It is important to make sure that the latest version of software, such as Node.js, is used to ensure security and performance, as the code generated by ChatGPT may not always be up to date. This local testing step was crucial to ensure everything worked smoothly before deployment. Once I confirmed the functionality, I published the code in a public GitHub repository. https://github.com/alexbj75/movierecommendator

Step 3: Deploying on Eyevinn Open Source Cloud



With the code ready, I created an account on Eyevinn Open Source Cloud https://www.osaas.io/ and connected it to my GitHub repository. After submitting the repository URL under “My service inbox”, it went through a quick approval process and then I launched the service.

In no time, my movie recommendation site was live and accessible here https://ej75hotmal-alex.alexbj75-movierecommendator.auto.prod.osaas.io.



Advantages of Eyevinn Open Source Cloud

Rapid Development and Deployment: Eyevinn Open Source Cloud and AI tools enabled me to take my idea from conception to a live web service in under three hours, which is impressive for someone who hasn’t written code in 24 years. This rapid turnaround is a game-changer for anyone looking to innovate quickly.

Easy Deployment Without Building or Hosting Software: Eyevinn Open Source Cloud simplifies the process of deploying services by removing the need to build or host the software yourself. This makes launching a project much easier.

Cost Savings: Leveraging open-source software eliminates expensive licensing fees, making it a cost-effective solution. Eyevinn Open Source Cloud also has no lock-in because the source code is always available on GitHub, ensuring full transparency and flexibility. This makes launching a project much easier.

Community-Driven Innovation: By using open-source tools, you benefit from the collective expertise of a global developer community that continuously enhances the software. Eyevinn Open Source Cloud also encourages community-driven innovation through revenue-sharing, contributing back to the community.

Conclusion

Eyevinn Open Source Cloud, combined with AI, is a powerful tool for entrepreneurs, tech enthusiasts, and developers who want to bring their ideas to life quickly and affordably. My experience of creating an online movie recommendation site—even after not having programmed for 24 years—is proof of how accessible this platform is. If you have a web service idea, I highly recommend giving Eyevinn Open Source Cloud a try. You might be surprised by how fast your idea can come to life.

Deploy Your Web Apps with Eyevinn Open Source Cloud

The Hello World repository I created is available on GitHub https://github.com/ernestocarocca/hello-world

If you’re looking for a fast and seamless way to deploy your apps in the cloud, Eyevinn Open Source Cloud (OSC) is the perfect choice.

Here’s a step-by-step guide to deploying a basic “Hello World” app using OSC.

Eyevinn Open Source Cloud web page

insert your repo, then press launch.

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After logging in, you’ll be directed to My Inbox, where the repository you uploaded will be listed. If your app requires environment variables, you’ll see how simple and visually clear it is to add them. Just input the required variables in the designated fields and Add new repository.

Once the process is complete and the repository is approved, you can simply search for it by the name you gave it. Press the “Hello World” card.

Decorative Images

Here’s where the magic begins! Press on “Create example”.

Decorative Images.

Fill in the desired name and environment variables. End press on the “Create”

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But if, for any reason, you’re unsure about certain terms or settings, don’t worry! There’s an AI assistant available to answer any questions you have regarding the process.

Decorative Images.

Then you see a card created that looks like this. Just press on the card.

 Decorative Images.

After just a few seconds, I had a fully deployed web app.

 Decorative Images.

Trim video file on an S3 compatible bucket using open source

In this blog post I will describe how to trim a video file on an S3 compatible bucket using ffmpeg without having to download it first, process it and then upload the result.

For trimming the video we will use the open source tool ffmpeg and a script that handles uploading the result to an S3 bucket. This open source script is available as a service in Open Source Cloud.

Step 1: Login to Eyevinn Open Source Cloud

Go to www.osaas.io and login. Sign up for an account if you don’t already have one. It is free to get started and you don’t even have to enter a credit card to try this out.

Step 2: Setup access to S3 bucket

Go to the service in Open Source Cloud called “FFmpeg to S3” using the search bar on the browse page. Click on the card “FFmpeg to S3 to go to the service.

Then click on the tab named “Service secrets”

Get the S3 access key credentials from your administrator of your S3 buckets. You need at minimum the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY. Create a service secret for each of these credentials.

Step 3: Generate signed URL to the video to trim

Now we need to generate a signed URL for the video that you want to trim.

Copy the presigned URL to the clipboard

Step 4: Create a ffmpeg trim job

As an example we will extract the first 30 seconds of the video file and the ffmpeg command for that is:

ffmpeg -ss 0 -t 30 -c:v copy -c:a copy

Go back to the FFmpeg to S3 service page in Open Source Cloud and click on button “Create job”.

Enter the following in the settings dialog:

Name: “tutorial”
CmdLineArgs:
Replace [SIGNED_URL] from clipboard and lab-testcontent-input with the name of your bucket:

-i [SIGNED-URL] -d s3://lab-testcontent-input/tutorial-30sec.mp4 "-ss 0 -t 30 -c:v copy -c:a copy"

AwsAccessKeyId and AwsSecretAccessKey: reference to the service secrets created
Region: Location of the S3 bucket

Now press Create and wait for the job to be completed. When the job is completed you should have a file called tutorial-30sec.mp4 on the bucket you provided and 30 seconds duration.

Create a job from command line

You might want to automate or script the creation of these ffmpeg jobs and to facilitate that there is an open source SDK and command line tool for Eyevinn OSC. The command line tool is a Node.js script.

Follow the instructions on how to install Node.js if you don’t already have it installed.

Then install the CLI


% npm install -g @osaas/cli

Obtain the personal access token by going to Settings in OSC and the tab API. Here you find the personal access token that you copy to your clipboard. Set this token as an environment variable in your shell.


% export OSC_ACCESS_TOKEN=token

Now you can create the same job with the following command (replace [SIGNED-URL] and s3 bucket):


% osc create eyevinn-ffmpeg-s3 tutorialcli -o awsAccessKeyId="{{secrets.eyevinnawskeyid}}" -o awsSecretAccessKey="{{secrets.eyevinnawssecret}}" -o cmdLineArgs='-i [SIGNED-URL] -d s3://lab-testcontent-input/tutorial-30sec.mp4 "-ss 0 -t 30 -c:v copy -c:a copy"'

Conclusion

This was an example of how you can run ffmpeg to process a video file on an S3 bucket and output the result back to an S3 bucket without having to develop your own script for it as a script already existed that is open source and made available as a service in Eyevinn Open Source Cloud.

How to create a FAST channel in Open Source Cloud

Creating Free Ad-Supported Streaming TV (FAST) channels is becoming increasingly popular among content creators and broadcasters aiming to reach a wider audience without the need for a subscription model.

With the rise of open-source technologies and cloud platforms, launching your own FAST channel is more accessible than ever. The Open Source Cloud, with its array of tools and services, offers a comprehensive environment to deploy a FAST Channel Engine. This article guides you through the process of setting up a FAST channel using the FAST Channel Engine within the Open Source Cloud using already transcoded videos.

The base for the virtual channel is transcoded and packaged HLS VoD assets stored on an origin. The advantage with virtual channels is that you only prepare and encode the content once.

Prerequisites

As a prerequisite for creating a linear channel using the FAST Channel Engine, you need to have your VOD assets transcoded into HLS format. These assets should be properly segmented and stored on an origin server or accessible file storage system.

Ensuring that your media files are in HLS format and readily accessible allows the channel engine to seamlessly retrieve and stream the content according to your schedule.

Prepare a playlist, in other words a URL pointing to a text file containing a list of .m3u8 URLs, each representing a streamable video segment. One way to do this is to use gist.

– Go to https://gist.github.com
– Enter a name of the playlist in Filename (e.g. playlist.txt)
– Enter a list of URL to HLS manifests (one per line), for example:

https://demo.osc.technology/fast_1/manifest.m3u8
https://demo.osc.technology/fast_2/manifest.m3u8
https://demo.osc.technology/fast_3/manifest.m3u8

– Press Create public gist (green button)
– Press “Raw” on your created playlist file
– Copy the URL to the created playlist file e.g. https://gist.github.com/xxx/playlist.txt

Create a channel

Open your web browser and go to https://app.osaas.io/ and login using your credentials. Once logged in, locate the “Subscriptions” item in the menu on the left-hand side of your screen and click on it. This will take you to the page where you can manage and explore available services.

On the Subscriptions page, look for the card labeled “FAST Channel Engine.” This represents the service you’ll use to create your FAST channel. Next to the service title, there’s a drop-down menu symbolized by three dots. Click on this menu to reveal more options and select “Create channel.”

Enter a meaningful name for your channel. This name will help you identify it among other channels you may create. In this example the type “Playlist” is used. This option indicates that your channel will play content sequentially from a playlist you provide.

Enter the URL to your playlist in the “URL” field, e.g. the playlist created earlier (https://gist.github.com/xxx/playlist.txt). Make sure your playlist is correctly formatted and accessible online.

After entering all necessary information, press the “create” button. The platform will now process your request and start setting up your channel based on the playlist provided. This process may take a few moments. You can monitor the progress directly on the platform.

Once your channel is successfully created, find the channel’s drop-down menu (again, symbolized by three dots). Click on it and select “Copy URL” to copy the channel URL to your clipboard.

Open a new tab in your browser or launch a web player that supports .m3u8 streaming, safari or https://web.player.eyevinn.technology. Paste the copied URL into the player’s input field to start streaming your channel. This step is crucial for ensuring everything is working correctly and allows you to preview your channel’s content as your audience would.

Conclusion

Creating a FAST channel using the FAST Channel Engine in the Open Source Cloud is a powerful way to reach audiences with your content. By leveraging open-source technologies and cloud infrastructure, content creators can deploy scalable, high-performance streaming channels supported by ads.

This approach enable content distribution, allowing creators to broadcast their content globally without the need for heavy infrastructure investments.

Video File Transcoding with Open Source Cloud

SVT Encore is a powerful open-source video transcoder specifically designed for the cloud. It forms the backbone of the transcoding process in the media supply chain, taking raw video inputs and converting them into multiple formats and bitrates suitable for adaptive streaming. The transcoding process involves breaking down video files into different resolutions and bitrates, allowing viewers to receive the best possible quality based on their device and network conditions.

To reduce the barrier to get started with SVT Encore we have added their project to Open Source Cloud together with some supporting backend services that we have added. This blog gives you a walk-through on how to setup video file transcoding using Open Source Cloud.

Prerequisites

  • If you have not already done so, sign up for an OSC account.
  • 5 remaining services on your subscription plan or individually purchased the services included in this solution.
  • S3 compatible object storage solution

This solution is based on the following open source projects made available as a service:

  • SVT Encore
  • Valkey
  • Encore Callback Listener
  • Encore Transfer
  • Retransfer

After completed this tutorial you will be able to transcode a video file on an S3 compatible storage and the output is placed on another S3 compatible storage when the processing is completed.

Step 1: Create Encore Queue

Go to the web user interface and navigate to the service called SVT Encore. Click on the button “Create queue” and give the queue a name.

You can leave the Profiles URL empty for now and then press Create.

Now you have an instance of SVT Encore running with one single queue and ready to receive transcoding jobs for processing. You can try this out by clicking on the menu item Open API docs to access the online REST API documentation and submit a job.

However, to automatically get transcoded files out from SVT Encore and transferred to the output storage we need a few more help services. So that we will setup now. Start by take a note of the URL to the SVT Encore instance.

Remove the trailing slash an keep it for later use. In this case it is https://demo-blog.encore.prod.osaas.io.

Step 2: Create Valkey queue

Valkey provides a Redis compatible key / value store and this i what we will use to manage the queue for transferring files out from Encore and to out output bucket.

Navigate to the Valkey service in Open Source Cloud and press “Create valkey”. Give the instance a name and press Create.

Note down the IP and port to the Valkey instance card and this is what will be the Redis URL that we will refer to later in this blog. In this example it would be redis://172.232.131.169:10507.

Step 3: Launch Encore Callback Listener

Now we need something that monitors a transcoding job in SVT Encore so we know when the file is ready to be transferred. For that you navigate to the Encore Callback Listener in the web user interface. Click on button “Create callback” and enter the name of the instance, Redis URL (above), URL to the SVT Encore instance and the name of the transfer queue. We call it “transfer” in this example.

Important the URL to the SVT Encore instance is without the trailing slash.

Press Create and you are done with this step for now.

Step 4: Setup secrets

Now we have the Callback Listener service running that will monitor transcoding job and place completed jobs in the transfer queue. Now we need a service that picks up a job from the transfer queue and actually transfers the file out from SVT Encore and to our destination bucket.

First we need to configure the transfer job service with API secrets needed for the access to the S3 bucket. Navigate to the Retransfer service in Open Source Cloud and click on the tab Secrets.

Create the secrets containing the Access Key Id and Secret Access Key for the destination storage access. Note down the name of these secrets as you will be using it later.


awsaccesskeyid
awssecretaccesskey

Now navigate to the Encore Transfer service in the web user interface and click on the tab Secrets. Add a secret with your personal access token (OSC token) that you find under Settings and the tab API.

Step 5: Create Encore Transfer service

When the service is created and saved we can now move on with creating the Encore Transfer service. Enter the name of the instance, Redis URL, name of queue in Redis (Valkey), output URL, OSC token and the name of the access key secrets in the Retransfer service. In this example we will have the following values:

Then press Create and wait for the instance to be ready.

Step 6: Submit a job

Now we are ready to try transcoding a video file that we have available on an S3 compatible storage. We will create signed URL to the video file we want to transcode. For example:


https://lab-testcontent-input.s3.eu-north-1.amazonaws.com/NO_TIME_TO_DIE_short_Trailer_2021.mp4?SIGNURLSTUFF

Navigate back to the SVT Encore service and press the menu item to open API docs again.

Click on the POST /encoreJobs bar and button Try it out and enter the following JSON

{
  "externalId": "blog",
  "profile": "program",
  "outputFolder": "/usercontent/blog",
  "baseName": "blog",
  "progressCallbackUri": "https://demo-blog.eyevinn-encore-callback-listener.auto.prod.osaas.io/encoreCallback",
  "inputs": [
    {
      "uri": "https://lab-testcontent-input.s3.eu-north-1.amazonaws.com/NO_TIME_TO_DIE_short_Trailer_2021.mp4?SIGNURL",
      "seekTo": 0,
      "copyTs": true,
      "type": "AudioVideo"
    }
  ]
}


And then press button Execute. Now a job is submitted and if you want to see the progress you can go to the Encore Callback Listener service and open the instance logs to check that it is receiving the callbacks.

When the transcoding process is completed it will place a job on the transfer queue that will be picked up by the Encore Transfer service. And when all the transfer jobs are completed you will in this example find a set of files in your output bucket where you have set of different variants with different resolutions and bitrates.

Conclusion

You now have a fully fledged video transcoding pipeline for preparing video files for streaming using ´SVT Encore with some supporting services. All based on open source and you don’t have to setup your own infrastructure for this to get started. If you later choose to do so you are free to do it as the code and everything demonstrated here is available as open source.

Configuration backend service for mobile applications

To provide your mobile applications with centrally controlled configuration you need a backend service that can provide the applications with this. I developed and open sourced a backend service that provide this functionality, and this code is now made available as a service in Open Source Cloud.

This means that you don’t have to have your own cloud infrastructure to get started but you always have the option to do so as it is open source. In this blog post I will walk you through how you setup this service in Open Source Cloud.

Step 1: Create an account

If you already have an account at Open Source Cloud you can skip this step.

Head over to www.osaas.io and create a free account. Follow the procedure and create a new tenant.

Step 2: Create a Key / Value Store

To store the configuration variables we will use a Redis compatible key/value store called Valkey. This is also open source and has been made available as a service in Open Source Cloud.

There is of course nothing preventing you from using a Redis cloud service for this instead but in this post we will use services available in Open Source Cloud.

When you have logged on to the platform and created your tenant, go to browse and search for “valkey” and click on the card in the search result.

Click on the button “Create valkey” and give this instance a name. What name you choose is not important now.

Write down the IP and port found on the instance card for the Valkey instance that you just created.

Step 3: Create a configuration backend

Now it is time to create the configuration service backend. Navigate back to browse and search for “application config” and click on the card named “Application Config Service”.

Now press button “Create config-service” and enter a name of the config backend service and the Redis URL to the Valkey instance you created. Construct the Redis URL using the prefix redis:// and the IP and port you noted down earlier.

Wait until the service is ready and status “running” and then you can click on the instance card.

Insert a new configuration value by clicking on the Add new button in the top right corner. As an example we create a configuration variable called “hello” and with the value “world”.

Press create button and you will find the variable in the list.

Step 4: Use the configuration in your application

To get the address to the configuration value click on the “Copy to clipboard” icon and you can use this address in your application to fetch the variable.

As an example we can write this simple web application (entered in codepen.io):

Conclusion

You no longer need to build and host your own backend to provide the applications with configuration variables with this open source project available as a service in Open Source Cloud.

Fast and simple QR-code implementation

QR code usage has sky-rocket the last years. From occasional usage to almost mandatory, can you get a ticket today without it having a QR code on it?

While QR codes are not the hardest thing to add it might be tedious if you have to do it all the time!

I’m sure there are a few tools out there to handle QR-code creation but let me tell you about the QR-code generator on Open Source Cloud!

Head over to www.osaas.io and create a free account.

osaas landing page

When you have logged on to the platform and created your tenant, go to browse and search for QR and click on the card in the search result.

Search result for QR

Click on Create qr-generator


Now you need to give your generator a name and provide a url to where you want to redirect with your QR-code.

Form fields for QR code generator

You could provide a logo if you’d like, it should be in a square format for best result.



Click on create and wait for the instance to be created.



Now you have your QR-code!



Implement it in your web apps by simply add the url from the instance card in a img-tag src attribute.

img tag example

Here I have just created a boilerplate react app with VITE and added the img-tag and provided the url in the src attribute

Example of implementation