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Webhooks, upload notifications and background image processing

May 21, 2013 by Tal Lev-Ami
Web applications and web APIs are usually programmed to perform requests in a synchronous manner. A common web-based access flow will start with a requester accessing a remote service. The remote service in turn will process the request and quickly return the result. 
 
But sometimes a web application will need to perform actions asynchronously in the background. 
 
Consider, for example, a computing intensive web request. Such a request might take a very long time to finish. UI wise, you might not want your users to actively wait so long for this command to finish. Technically, such a long running HTTP request might even time-out completely. 
 
In this case, you will probably want to employ a different access flow. In this flow, when the requester accesses the remote service, the remote service will return immediately with a 'pending' result. The remote service will then continue to perform the action in the background. Finally, when the remote service is finished, it will notify the requester that the required action was completed. 
 
The same concepts apply to Cloudinary's image management APIs. 
 
So far, Cloudinarys APIs were synchronous. For example, if you wanted an image transformed, you would have to wait synchronously until the transformation was finished.
 
In this blog post we wanted to introduce Cloudinary's new notifications and background processing capabilities that further extend the image management solution available when using Cloudinary.
 

Webhooks and upload notifications

Many mobile and web applications upload images and files to Cloudinary. Such uploading can be performed either from these services' backend or directly from their users' browsers or mobile applications. In such cases you might want to make sure your server is notified when an upload is completed. 
 
You can do that by setting the notification_url parameter of Cloudinary's upload API to any valid HTTP (or HTTPS) public URL.
 
For example, in PHP:
$result = \Cloudinary\Uploader::upload("sample.jpg", 
   array("notification_url" => "http://mysite/my_notification_endpoint"));
When the upload is completed, an HTTP POST request will be sent to the notification URL you provided. The post data will contain all upload result details as returned by our upload API (public ID, URLs, image dimensions, semantic data if requested and more). The request will also contain a signature of the sent data so you can verify the sender.
 
Here's a sample POST request with a JSON of the upload result:
POST /my_notification_endpoint HTTP/1.1
X-Cld-Timestamp: 1368881627
X-Cld-Signature: 29a383e289bc569310a8ca9899019a3167b4909e
Content-Type: application/json

{"public_id":"djhoeaqcynvogt9xzbn9","version":1368881626,"width":864,"height":576,"format":"jpg","resource_type":"image","created_at":"2013-05-18T12:53:46Z","bytes":120253,"type":"upload","url":"http://res.cloudinary.com/1233456ab/image/upload/v1368881626/djhoeaqcynvogt9xzbn9.jpg","secure_url":"https://cloudinary-a.akamaihd.net/1233456ab/image/upload/v1368881626/djhoeaqcynvogt9xzbn9.jpg"}
By the way, you can use RequestBin to test notifications received during development.
 
The signature is calculated as follows:     
SHA1-Hex-Digest("{data}{timestamp}{api_secret}")
Your server application can use this notification to update your model and database regarding the uploaded images or to cleanup unused uploaded files.
 
Here's another example in Ruby on Rails for generating a file input field that performs direct uploading from the browser using a jQuery plugin.
<%= cl_image_upload_tag(:picture, 
      :notification_url => "http://mysite/my_notification_endpoint") %>

Eager transformations in the background

By default, when you access Cloudinary delivery URLs, transformed images are generated dynamically if they don't already exist, according to the transformation parameters. You can also use Cloudinary's eager transformations, in which case multiple transformed versions of an image are created eagerly while uploading so they are ready for fast delivery even for the first download request.
 
Sometimes, you might need to create a single time consuming transformation or many eager transformations of an uploaded image. Creating such transformations might take seconds, especially if the original image is very large. In such cases, you probably don't want your user to wait for the process to complete. 
 
Using Cloudinary's asynchronous eager transformations, you can now define multiple eager transformations while uploading. The upload request will return immediately, the transformations will be performed in the background by Cloudinary and you will get notified (if you want) when the transformations are ready.
 
You can enable asynchronous eager transformations by setting the new eager_async upload API parameter to true. In addition, you can set the optional eager_notification_url to receive an HTTP POST request when the transformation generation is completed.
 
The following example in Python (or Django) creates multiple transformations eagerly in the background.
cloudinary.uploader.upload("sample.jpg", 
   eager=[dict(crop="fill", width="150", height="100"), 
          dict(effect="sepia", width="0.5", crop="scale")], 
   eager_async=True, eager_notification_url="http://mysite/my_notification_endpoint")
Here's an example of how the notification post request might look like:
POST /my_notification_endpoint HTTP/1.1
X-Cld-Timestamp: 1368883736
X-Cld-Signature: 09ef8c16f6e0ff85f5345d4813973de8f746448d
Content-Type: application/json

{"batch_id":"c0ed79e610f0636d15a1353a0a866933","notification_type":"eager","eager":[{"width":150,"height":100,"url":"http://res.cloudinary.com/1233456ab/image/upload/c_fill,h_100,w_150/v1368883730/noapoaq60varndxnh2or.jpg","secure_url":"https://cloudinary-a.akamaihd.net/1233456ab/image/upload/c_fill,h_100,w_150/v1368883730/noapoaq60varndxnh2or.jpg"},{"width":432,"height":288,"url":"http://res.cloudinary.com/1233456ab/image/upload/c_scale,e_sepia,w_0.5/v1368883730/noapoaq60varndxnh2or.jpg","secure_url":"https://cloudinary-a.akamaihd.net/1233456ab/image/upload/c_scale,e_sepia,w_0.5/v1368883730/noapoaq60varndxnh2or.jpg"}]}


Background sprites, animated GIFs and PDFs handling 

Cloudinary supports generating sprites: merging multiple images into a single large image for a more efficient browser loading using a generated dynamic CSS. 
 
Sometimes you might want to merge tens or even hundreds of images into a single sprite. 
 
Cloudinary's image manipulation are fast and efficient, but transforming and merging so many images might take more that your API client request can wait. In this case an HTTP request timeout might occur.
 
You can now tell Cloudinary to perform such sprite generations in the background by setting the async API parameter to true. In addition, you can set the notification_url parameter for receiving a webhook request when the process is completed (as explained above).
 
The following Ruby example requests for a sprite generation to be performed in the background:
Cloudinary::Uploader.generate_sprite("faces", :width => 150, :height => 100, 
   :crop => :fill, :async => true, 
   :notification_url => "http://mysite/my_notification_endpoint")
 => {"status"=>"processing", "batch_id"=>"163a919cde8f9317d6ee0fbfe6375dc4"} 
The API returns immediately with the response below while the later notification will include the final generated sprite details:
POST /my_notification_endpoint HTTP/1.1
X-Cld-Timestamp: 1368882586
X-Cld-Signature: d91bccba5f1bb38905fc6a9284914e8959fb4a7b
Content-Type: application/json

{"batch_id":"f97c6bf03074d9641f1a9c9b6bcebef7","css_url":"http://res.cloudinary.com/1233456ab/image/sprite/c_fill,h_100,w_150/v1368882583/faces.css","image_url":"http://res.cloudinary.com/1233456ab/image/sprite/c_fill,h_100,w_150/v1368882583/faces.png","secure_css_url":"https://cloudinary-a.akamaihd.net/1233456ab/image/sprite/c_fill,h_100,w_150/v1368882583/faces.css","json_url":"http://res.cloudinary.com/1233456ab/image/sprite/c_fill,h_100,w_150/v1368882583/faces.json","version":1368882583,"image_infos":{"face_center_eer8ss":{"width":150,"height":100,"x":0,"y":0},"face_left_b7ikxf":{"width":150,"height":100,"x":152,"y":0},"face_top_usjwvk":{"width":150,"height":100,"x":0,"y":102},"front_face_cywiib":{"width":150,"height":100,"x":152,"y":102}},"notification_type":"sprite"}
You can now create an animated GIF or a multi-page PDF document in a similar fashion. 
 
You can also "explode" a PDF in the background into multiple separated images representing all of its pages. All this is done using Cloudinary's 'multi' and 'explode' methods by setting the async parameter to true and optionally setting a notification_url. Here are some examples in Ruby:
Cloudinary::Uploader.multi("faces", :format => 'gif', :width => 150, :height => 100, 
   :crop => :scale, :async => true, 
   :notification_url => "http://mysite/my_notification_endpoint")
Cloudinary::Uploader.explode("multi_page_pdf", :format => 'png', :width => 200, 
   :height => 300, :crop => :scale, :page => :all, :async => true, 
   :notification_url => "http://mysite/my_notification_endpoint")

Summary 

As always, our goal with Cloudinary is to solve all of your web and mobile app's image management and image manipulation aspects for you and let you focus on your core business logic.
 
As a developer, you are probably familiar with the complexities involved in managing background processing and push notifications yourself. We believe that Cloudinary’s new webhooks and the ability to perform computing intensive image manipulations asynchronously in the background will prove as very useful tools in your image management tool-belt.
 
We're anxious to hear your feedback about these new features. Make sure you drop us a line in the comment thread below!
 

How Mediavine handled image load in a 50M+ page-views Rails site

May 01, 2013 by Itai Lahan
 
We are often asked to share our customer stories with the rest of the Cloudinary community. Whether it's for learning about others experiences managing images with Cloudinary, or just to reaffirm Cloudinary's solution - we love to hear your stories and we're happy to share them.
 
Today, we wanted to introduce you to Mediavine Inc., one of the largest online entertainment networks on the web, and how they utilized Cloudinary to solve their image management needs.
 
 

The customer

Mediavine, Inc. owns and operates some of the web's largest entertainment and lifestyle properties. Mediavine's network of sites include:

       TV Fanatic

     
        Movie Fanatic
         
       Food Fanatic
         

 
 
 
 
 
 
 
 
 
Combined, these websites garner a traffic of nearly 50 million page views a month. 
As modern media outlets go, Mediavine's websites are incredibly image rich. 
 

The challenge

Mediavine's sites run on a custom Ruby on Rails CMS hosted on Heroku. Like many other Rails sites, they started off using the Carrierwave and mini_magick gems to handle their image needs. 
 
However, as their page views and image processing needs grew, they quickly ran into performance problems
 
"No matter how much we optimized image uploads - including moving all version processing to background workers - uploading several high resolution files was just not going to be possible through the dyno manifold." Says Eric Hochberger, founder and head of development at Mediavine. "We knew we needed to go directly to our image store, S3. We looked into rolling out our own solutions, such as carrierwave_direct, but they were far too complex after way too many hours of struggling. And they would still require additional image processing!"
 
 
 

The solution

We asked Eric if he could share his experience with Cloudinary: 
 
"With Cloudinary we got direct upload to the cloud working within minutes. But it didn't just stop there. Cloudinary solved our timeout issue, while greatly speeding up our uploading process, thanks to its easy-to-implement javascript upload." Eric said.
 
"Cloudinary did more than that though. It helped us solve problems we had previously never thought were fixable," Eric added. "Scaling animated gifs worked perfectly without any of our previous imagemagick glitches. As for face detection we thought only the geniuses at Facebook could possess?  Yeah. We have it now. Full ITPC data?  Just try getting that out of mini_magick. Now we can pull locations out of images."
 
What about the integration with Cloudinary? "This all came in ridiculously easy fashion. Really, when it comes to any headaches with dealing with images, Cloudinary has solved them all. Its URLs even solve CDN cache busting. Working with Cloudinary's gem and carrierwave implementation has been a programmer's dream."
 

Recommendation

"It's rare when you can outsource a problem and save money but somehow Cloudinary managed to do that." says Eric. "We were able to knock our direct image hosting costs in half from S3/CloudFront, thanks to Cloudinary's generous pricing and optimization. Even better, we were able to significantly reduce Heroku usage, courtesy of seriously reducing worker dynos with outsourcing thumbnail and version generation. Talk about a win-win."
 
"Even if you have a 'working' solution," continues Eric, "we promise Cloudinary will do it better. Don't worry if you have to migrate from an existing system. They even come with code to help you do that. We had our hundreds of thousands of images migrated in less than an hour. And thanks to the fact they support carrierwave, we had minimal code changes."
 
 

Final words

We were very impressed by just how fast Mediavine managed to wrap their heads around the Cloudinary service, migrate their images and complete the full integration. 
 
We are extremely excited to have Mediavine using Cloudinary, and wanted to thank Eric for taking the time and sharing his experience.
 
Cloudinary users - let us know if you want to share your own unique experience using Cloudinary. We'd love to feature your services here and we're sure that all of Cloudinary's customers will find your insights helpful.
 

A story about production systems, Rails, monitoring and off-hour notifications

Apr 25, 2013 by Nadav Soferman
Cloudinary's image management service is used by thousands of world-wide websites and mobile apps. For many of our clients, Cloudinary has become a central, mission-critical component used for managing image uploads, transformations and delivery.
 
This is why we've built Cloudinary from the ground up to be a very robust service. We put a lot of emphasis on availability, scalability and support and we take our users' confidence in us extremely seriously.
 
So far, we've been quite satisfied with our ability to keep Cloudinary at an average of > 99.99% uptime.
 
However, on April 4th, the Cloudinary service experienced outages for a few hours. We wanted to explain what happened, our conclusions and the steps we've taken to make sure this won’t happen again.
 

The upgrade

Cloudinary's core service is built with Ruby on Rails. The service is tested thoroughly and upgrades are handled with uttermost care. This is why we've preferred to stay with Rails v3.0 for a long time rather than rock the boat with an upgrade to the latest Rails 3.2.
 
A few weeks ago a security vulnerability was discovered in Rails. As always, we wanted to apply the security fix as soon as possible. However, the Rails team stopped releasing fixes for Rails 3.0. We had to upgrade to v3.2.
 
We've upgraded to Rails 3.2 in our lab and modified our code to support it (Rails upgrades tend to be non backward compatible and break code built with previous versions). We've tested our code extensively and verified that our thousands of unit tests passed correctly. We've successfully finished a thorough manual QA of the system in our staging environment. It all went quite smoothly.
 
We scheduled the upgrade for April 4th. As usual, we deployed the system gradually to all of our production servers. Deployment went smoothly as well. We performed additional sanity testing after the system was deployed and closely monitored the system during the working day.
 
We went to sleep happy and relaxed.
 

The issues

At about 1am at night things started to shake.
 
Apparently, Rails 3.2 changed the defaults of one simple configuration parameter - response caching was turned on by default when certain cache headers are returned.
 
As a result, after long hours of service requests, the local application disk for some of our servers became full due to the cached responses. This caused certain requests that required disk space to fail, depending on the exact request and the size of the response.
 
Annoyingly enough, the automatic monitoring service that regularly verifies our APIs, was performing a request that required very little disk space and continued to operate regularly. This service is configured to send notifications to our engineering team's mobile phones during the night. But since no errors were detected, no notification was sent.
 
Fortunately for us, our co-founder's toddler woke him up early in the morning. He naturally (?) checked his inbox, understood that something was very wrong. He quickly cleared the disk space and modified Rails 3.2 cache settings. The system was fully working again.
 
It's important to note that during these ~5 hours, all existing images and transformed images were delivered successfully to users through our delivery service and tens of thousands of worldwide CDN edges (Akamai + CloudFront). Still, part of the upload API calls did fail during this time and we are very sorry for this.
 

Going forward

Naturally, we've immediately started to improve our outage prevention mechanisms.
 
We've added additional disk space tests to our QA list and added abnormal disk usage monitoring to our urgent notification service. We're also adding a wider set of API requests to our automatic service monitoring.
 
We've integrated with Twilio to enhance our off-hour notifications. Specifically, our engineering team will now receive automatic voice calls to their mobile phones in addition to our previous notification methods.
 
To make sure we keep you in the know during outages, we've pushed up the priority of a public status page. This page will include automatic monitoring details as well as human written notes.
 

Summary & conclusions 

We are happy that Cloudinary had nearly zero availability issues in almost 2 years of operations. On the other hand, no online service is perfect and every service experienced or will experience outages. 
 
We will continue to enhance our service with additional image-related features. On the same time, we'll continue to work hard on having Cloudinary's uptime as close to 100% as possible.
 
Thank you for trusting us with your images!

Automatic image sharpening and blurring in the cloud

Mar 20, 2013 by Nadav Soferman
Images. Your web (or mobile) application is probably filled to the brim with images. You might be surprised at just how much impact these images have on your visitors. From their graphical appeal to their size and access times - these images determine your visitors browsing experience and ultimately their conversion to repeating visitors and paying clients.
 
Now, while your graphic designer has created a cool graphical concept, many of the images you need to embed inside it are not in your direct control. Social websites contain profile photos uploaded by their users. E-commerce solutions contain many product photos that can't be edited one at a time. Media outlets contain many photographs of different consistency.
 
Having a tool in your belt that offers automatic tweaks and retouches for all these images is quite handy. Here a couple of things you can do with Cloudinary that can really improve your website.

Image sharpening

How can you make your website "pop"? it's easy if you control the exact content across your web application - a great graphics design can make wonders. But what can we do to improve user uploaded images? 
 
Let's look look at the following image uploaded to Cloudinary:
  
 
The photo looks good. But just take a look at what a bit of sharpness can do to it. 
You can add sharpness by setting the effect transformation parameter to sharpen (or e_sharpen for URLs):
 
 
 
Here's the same example in Rails:
<%= cl_image_tag("front_face.jpg", :effect => "sharpen") %>
You can control the strength of the sharpen effect to match your taste. Here's a more intense sharpening of the same image by setting the sharpen level to 300. Quite a nice photographic effect.
 
 

 
Same example in PHP:
<?php echo cl_image_tag("front_face.jpg", array("effect" => "sharpen:300")) ?>
Sharpening is also useful in making text elements in thumbnails clearer. For example, the following screenshot was uploaded to Cloudinary. As you can see the small gray text snippets are not so clear here.
 
 
 
 
Sharpening such an screenshot would make the text more readable. The following example sharpened this image. This time using the unsharp_mask effect that is similar to sharpen but uses a different algorithm. Much more readable:
 
 
 
 
Same example in Django:
img = cloudinary.CloudinaryImage("front_face.jpg")
img.image(effect="unsharp_mask")

Image blurring

Image sharpening is useful for improving images and making them "pop". But sometimes you would want to aim for the opposite effect. Quora, for example, is using dynamically created blurred snippets of text if you're browsing an answer while being logged out. How can you do that using Cloudinary?
 
To blur images, you can use Cloudinary's blur effect (e_blur for URLs). Here's an example: 
 
 
 
 
You can also make the blurring more intense by passing a numeric level. The following example applies the blur effect with a 400 intensity on the sample image:
 
 
 
In the following example, we blurred the image intensely and also reduced its opacity. Then we added a text overlay that calls users to sign up to your site if they want to view the full content:
 
 
 
Sample example in Rails:
<%= cl_image_tag("front_face.jpg", 
                 :overlay => "text:bold_dark:Sign up to see more",
                 :gravity => :center,  
                 :transformation => {:effect => "blur:500", :opacity => 50}) %>
Sometimes you want to blur only a certain region of an image. You can use the blur_region effect together with exact coordinates specified by x, y, width and height parameters. Here's an example that blurs only part of an uploaded screenshot:
 
 
 
Same example in Node.js:
cloudinary.image("front_face.jpg", { effect: "blur_region", x: 0, y: 0.5, w: 1.0 });
You can also automatically blur all faces detected in an image using Cloudinary's blur_faces. In the following example the face was automatically detected and blurred using the default level:
 
 
 
Same example in .NET:
string url = cloudinary.Api.UrlImgUp.Transform(
  new CloudinaryDotNet.Transformation().Effect("blur_faces")).BuildUrl("front_face.jpg");


Summary

Automatic image sharpening and blurring can do wonders to a website. For static assets, you can do that manually using your favorite image manipulation software. With Cloudinary such effects can be automatically applied to millions of user-uploaded images with ease. And if you decide to spruce up the graphical effects in your site's images, you can simply modify the transformation parameters in your development framework of choice. All images will be regenerated on the fly using the updated effect and will be served to your users optimized through a fast CDN.
 
It would be great if you try out the new filters and tell us when you think. If you don't have a Cloudinary account yet, you can create one for free.
 

cloudControl PaaS add-on for cloud-based image management

Jan 23, 2013 by Itai Lahan
More and more developers are getting to know the power of the cloud. In today's web application development world you can leverage the cloud to build large scale applications so quickly and easily that it's simply mind-boggling that you get all of this while still keeping on a very reasonable budget. 
 
For many developers, it took quite some time to overcome the natural not-invented-here syndrome and start trusting cloud services over the traditional in-house solutions. But it seems that we've already pass this hurdle and most recent web and mobile apps are counting heavily on cloud services to deliver them great solutions that cover important features, save crucial dev & support time, reduce dev costs and remove unnecessary development challenges.
 
Platform-as-a-Service (PaaS) is an a example of such a great cloud-based solution. In the PaaS case - moving your application deployment to the cloud. Simply write the code of your core application, run a command or two and you a have a fully working and scalable application available online. 
 
cloudControl is a popular european PaaS provider. Founded in 2009 in Germany, cloudControl provides a great solution for development and deployment of web applications in PHP, Ruby, Python and Java. 
 
 
Developers that manage their applications in a PaaS still needs to manage the image pipeline of their applications. This is where Cloudinary comes in. Today we are excited to announce that Cloudinary's add-on for cloudControl is available for the general public. Ruby on Rails developers? Django experts? PHP programmers? You can now develop and deploy your applications using cloudControl and use Cloudinary as an add-on in a single click or a simple command line.
 
With Cloudinary's add-on for cloudControl you can upload all your images to a highly available, safe and secured, backed-up cloud storage, perform various image transformation and manipulation in the cloud without installing any complex software and get all your images optimized and delivered to your users through a fast content delivery network (CDN) employing advanced caching techniques.
 
The add-on can be installed through cloudControl's portal:
 
 
We've prepared a detailed documentation for using Cloudinary as an add-on for cloudControl. Check out this documentation page for overview of the Cloudinary service, add-on installation and usage instructions, and integration guides for cloudControl's PHP, Ruby and Python platforms.
 
One of our targets is to make Cloudinary available to as many platforms as possible in the easiest-to-use way as possible. Today we are happy to add cloudControl to our family of high-end platform providers. It would be great if you try out cloudControl and Cloudinary's add-on. We'd appreciate your feedback.

Image opacity manipulation and dynamic watermark generation

Jan 17, 2013 by Nadav Soferman
Modifying an image opacity so the image is semi-transparent is a common requirement when implementing modern graphics design. Reducing image opacity allows background images to feel less dominant. Reducing opacity also allows layering of multiple images one on top of the other, an important step when adding watermarks, badges and textual overlays to images.
 
Modern web browsers support opacity manipulation via CSS directives. This however does not solve the problem completely. Watermarks need to be embedded as part of the original image and can't be added on the client's side. In addition, manipulating the opacity of the image itself allows for a consistent view across all your service's mediums - website, mobile application, emails (notifications) and PDFs (reports). Emails in particular do not support many of the modern CSS directives.
 
In this blog post we wanted to show how you can use Cloudinary's cloud-based image transformations to easily manipulate the opacity of images and how to use this technique to add watermarks to images.
 

Dynamically changing Image Opacity

Let's look at the following image the was uploaded to the cloud using the 'mountain' public ID.
 
 
You might want to use an image like the one above as a background image for a section of your web or mobile application. Simply set the 'opacity' parameter (or 'o' for URLs) to the desired percentage and Cloudinary will automatically modify the opacity of the image on-the-fly. As always, the resulting image is stored persistently in the cloud  and delivered optimized and cached to your worldwide users through a fast CDN.
 
The following example reduced the mountain image opacity to 20%. Now you can safely place text and other graphical elements above this image.
 
 
 
Below are examples of generating a transformation URL with modified opacity using our client libraries for Rails, PHP, Django and Node.js
<%= cl_image_tag("mountain.jpg", :opacity => 20) %>
<?php echo cl_image_tag("mountain.jpg", array("opacity" => 20)) ?>
import cloudinary
img = cloudinary.CloudinaryImage("mountain.jpg")
img.image(opacity=20)
cloudinary.image("mountain.jpg", { opacity: 20 });
 

Grayed-out Logos

Another common graphic design practice is to display a list of logos of customers and partners in your web site. Instead of the original, colorful logos, many web designers prefer to display semi-transparent grayed versions of these logos so they don't take attention from the website's messaging. 
 
With Cloudinary you can dynamically gray out images, and easily modify them in case your graphic designer has a change of heart.
 
In the following example, we've uploaded multiple logos to Cloudinary. We've went further and used Cloudinary's sprite-generation capabilities to merge these logos into a single sprite image for better performance:
 
 
 
By simply setting the 'effect' parameter (or 'e' for URLs) to 'grayscale' and setting the 'opacity' parameter ('o' for URLs), Cloudinary generates a semi-transparent gray-scale version of the logos for embedding in your website:
 

 

Generating Watermarks

In a previous blog post, we've shown how you can easily add overlays to images. Such overlays could be used to add watermarks to images using a previously uploaded semi-transparent PNG image of such watermark. With the new opacity manipulation transformation, you can upload your non-transparent watermark image and manipulate its opacity dynamically to make it semi-transparent, ready for adding as a watermark overlay.
 
The following example adds the previously uploaded image 'cloudinary_icon' as a 200 pixels wide overlay above the mountain image:
 
 
 
Now, by setting opacity to 40%, the overlay becomes semi transparent:
 
 
 
 
 
You can also apply an effect or filter on the overlay. In the following example we've increased the brightness of the overlay to make it white and reduced opacity to 30%:
 
 
 
The code samples below detail how to build the same URL in Ruby, PHP, Django and Node.js:
 
<%= cl_image_tag("mountain.jpg", :opacity => 30, :effect => "brightness:20", 
                  :width => 200, :overlay => "cloudinary_icon") %>
<?php echo cl_image_tag("mountain.jpg", array("opacity" => 30, 
  "effect" => "brightness:20", "width" => 200, "overlay" => "cloudinary_icon")) ?>
import cloudinary
img = cloudinary.CloudinaryImage("mountain.jpg")
img.image(opacity=30, effect="brightness:20", width=200, overlay="cloudinary_icon")
cloudinary.image("mountain.jpg", 
  { opacity: 30, effect: "brightness:20", width: 200, overlay: "cloudinary_icon" });
 

Summary

Dynamic opacity manipulation and watermark generation are some of the newest Cloudinary capabilities in your image manipulation tool-belt. These capabilities further simplify your web and mobile applications tedious image management tasks. 
 
With a simple URL (or one line of code) you can generate images that match your ever evolving graphic requirements and deliver them quickly to your users. You don't have to deal with complex non-standard CSS directives and you don't have to use over-qualified graphical software like Photoshop to generate images in your desired color balance and opacity.
 
Please share your thoughts and let us know how we can further improve Cloudinary's growing feature set.

Advanced image transformations in the cloud with CarrierWave & Cloudinary

Dec 20, 2012 by Nadav Soferman
In a previous post we've shown how you can easily manage your Ruby on Rails image uploads with CarrierWave and Cloudinary. Many of our Rails readers found this very useful, as it depicted a powerful image management solution that is trivial to integrate - use the popular CarrierWave GEM together with the Cloudinary GEM, add a single 'include' line to your code and that's it. All your images are automatically uploaded to the cloud and delivered through a fast CDN. Better yet, all image transformations defined in your CarrierWave uploader class are generated in the cloud by Cloudinary. No need to install and setup any image processing library (goodbye RMagick, ImageMagick, GraphicsMagick, MiniMagick, etc.). You also don't need to worry any more about CPU power, storage space, image syncing between multiple servers, backup and scale.
 
In this post, we wanted to show how you can use all of Cloudinary's additional cool image management and manipulation features together with CarrierWave - apply effects and filters, face detection based cropping, JPG quality modification, adding watermarks and more.
 

Custom and dynamic transformations 

Cloudinary's plugin for CarrierWave supports all of CarrierWave's standard resize and cropping capabilities. In addition, you can apply any custom transformation supported by Cloudinary by using the cloudinary_transformation method. You can call cloudinary_transformation in conjunction with the standard resize and crop methods. 
 
The following uploader class shows a common usage example with custom transformations:
class PictureUploader < CarrierWave::Uploader::Base
  include Cloudinary::CarrierWave

  # Generate a 164x164 JPG of 80% quality 
  version :simple do
    process :resize_to_fill => [164, 164, :fill]
    process :convert => 'jpg'
    cloudinary_transformation :quality => 80
  end

  # Generate a 100x150 face-detection based thumbnail,
  # round corners with a 20-pixel radius and increase brightness by 30%.
  version :bright_face do
    cloudinary_transformation :effect => "brightness:30", :radius => 20,
        :width => 100, :height => 150, :crop => :thumb, :gravity => :face
  end

end
 

Chained Transformations 

You can take this further by applying chained transformations. Any set of transformations can be applied as an incoming transformation while uploading or as part of the different versions that are generated lazily or eagerly during upload. 
 
The following uploader class includes chained transformations applied using the transformation parameter of the cloudinary_transformation method.
class PictureUploader < CarrierWave::Uploader::Base      
  include Cloudinary::CarrierWave
 
  # Apply an incoming chained transformation: limit image to 1000x1200 and 
  # add a 30-pixel watermark 5 pixels from the south east corner.   
  cloudinary_transformation :transformation => [
      {:width => 1000, :height => 1200, :crop => :limit}, 
      {:overlay => "my_watermark", :width => 30, :gravity => :south_east, 
       :x => 5, :y => 5}
    ]        
  
  # Eagerly transform image to 150x200 with a sepia effect applied and then
  # rotate the resulting image by 10 degrees. 
  version :rotated do
    eager
    cloudinary_transformation :transformation => [
        {:width => 150, :height => 200, :crop => :fill, :effect => "sepia"}, 
        {:angle => 10}
      ]
  end
end
Some websites have a graphic design that forces them to display the same images in many different dimensions. Formally defining multiple uploader's versions might become cumbersome. In this case, you can still utilize CarrierWave while leveraging Cloudinary's dynamic transformations by applying any desired transformation while building your view. 
 
Any version can be generated dynamically from your view without depending on CarrierWave versions. Simply use the full_public_id attribute with cl_image_tag to build cloud-based transformation URLs for the uploaded images attached to your model.
cl_image_tag(post.picture.full_public_id, :format => "jpg", 
             :width => 100, :height => 200,  :crop => :crop, 
             :x => 20, :y => 30, :radius => 10)


Custom coordinates based cropping

If you allow your users to manually select their images cropping areas, we recommend you keep these crop coordinates persistently in your model. This way you'll be able to crop the original images differently in the future. 
 
The following uploader class fetches the custom coordinates from attributes of the model object. The custom_crop method in this example simply returns a Hash of additional Cloudinary transformation parameters to apply.
class PictureUploader < CarrierWave::Uploader::Base  
  include Cloudinary::CarrierWave  
 
  version :full do    
    process :convert => 'jpg'
    process :custom_crop
  end    
  
  def custom_crop      
    return :x => model.crop_x, :y => model.crop_y, 
      :width => model.crop_width, :height => model.crop_height, :crop => :crop      
  end
end
If you want to store only the cropped version of the image, you can use the incoming transformation of Cloudinary's upload API. This way only the cropped image is stored in the cloud. You can then use additional transformations to resize the cropped image. 
 
The following example calls process :custom_crop in the class itself, instead of in a 'version', while the custom-coordinates are kept as transient attributes on the model (defined with attr) instead of storing them persistently.
class PictureUploader < CarrierWave::Uploader::Base  
  include Cloudinary::CarrierWave  
 
  process :custom_crop
 
  version :thumbnail do    
    process :convert => 'jpg'
    resize_to_fill(120, 150, 'North')
  end    
  
  def custom_crop      
    return :x => model.crop_x, :y => model.crop_y, 
      :width => model.crop_width, :height => model.crop_height, :crop => :crop      
  end
end


Private images and eager transformations 

Cloudinary supports uploading private images to the cloud. These images won't be accessible to your users. See our blog post for more details. Together with the Strict Transformations feature, you can specify that only certain transformations (e.g., low resolution thumbnails, watermarked images) are available for your users.
 
For uploading images as private, simply add 'make_private' to your uploader class. This will also make all generated delivery URLs to access the private images correctly. 
 
The versions you define in your uploader class should use only named or dynamic transformations marked as Allowed. Alternatively, you can tell Cloudinary to eagerly generate all transformed versions while uploading. This way you can keep all your transformations as strict (disallowed).
 
The following uploader class shows how to use private images and eager transformations:
class PictureUploader < CarrierWave::Uploader::Base      
  include Cloudinary::CarrierWave
  make_private
  
  # Generate a 164x164 JPG of 80% quality 
  version :simple do
    process :resize_to_fill => [164, 164, :fill]
    process :convert => 'jpg'
    cloudinary_transformation :quality => 80
    eager
  end
  
  version :thumbnail do
    resize_to_fit(50, 50)
    eager
  end
 
end


Summary

If you are a Ruby on Rails developer, you should definitely consider using CarrierWave (if you haven't done so already). Together with Cloudinary you can reach a powerful image management, manipulation and delivery solution with almost zero efforts and code changes.
 
If you're looking for a CarrierWave alternative, make sure you check out the brand new Attachinary Ruby GEM. Attachinary provides a modern image attachment solution to your Rails application while employing Cloudinary for cloud-based storage, image transformations and delivery. Read more about it here.
 
We've mentioned 'Ruby on Rails' quite a lot, though both CarrierWave and the Cloudinary plugin support a standard ActiveRecord model as well as a Mongoid model. In addition, some of our customers use this solution for their non-Rails frameworks, such as Sinatra.
 
For more details, see our documentation.
 
If you have additional thoughts on how we can make your life easier when managing images and attachments in your Rails applications, make sure you tell us about them. If you don't have a Cloudinary account already, you can sign up for a free account in seconds.

Adding borders to images

Nov 28, 2012 by Nadav Soferman
Graphic designers often contemplate whether to add borders to their website elements. The decision of whether to add borders around frames, buttons and text elements really depends on the feeling the designer is trying to convey through the design. 
 
In this blog post we wanted to tell you about a new cloud-based transformation available through Cloudinary - adding borders to images. Yes, you can use CSS3 or image masks to simulate borders around images, but the first is supported only on modern browsers and the latter clutters the HTML. In addition, if you plan on embedding images in emails or documents you can pretty much say goodbye to borders (certainly for images with rounded corners). For such cases, you can use Cloudinary's extremely simple image transformation API to add borders directly to the original image.
 
Consider the following photo. It was uploaded to Cloudinary using 'autumn_leaves' as its public ID:
 
 
Adding a border around the image is straightforward. Simply specify the 'border' parameter ('bo' for URLs) using a CSS-like format. In the following example '4px_solid_black' means a 4 pixels wide black border.
 
 
 
 
Same example in Ruby on Rails:
<% cl_image_tag("autumn_leaves.jpg", :width => 0.15, :crop => :scale, 
                :border => { :width => 4, :color => 'black' }) %>
 
The border's color component also accepts RGB format. The following example rounds the corners of the image using the 'radius' parameter ('r' for URLs) and adds a 6 pixels solid green border ('#00390b').
 
 
 
Same example in PHP:
<?php echo cl_image_tag("autumn_leaves.jpg", array("width" => 0.15, "crop" => "scale", 
       "radius" => 20, "border" => array("width" => 6, "color" => "#00390b"))) ?>
 
Cloudinary also supports adding semi-transparent borders. This is accomplished using the RGBA color format. The Alpha hex value ranges between 00 (fully transparent), to FF (opaque). The following example generates a semi transparent 10 pixels wide green border. We also use Cloudinary's chained transformations to make the image elliptic ('max' radius), rotate the image by 5 degrees and add an underlay blue background image (while resizing it and increasing its brightness).
 
 
 
Same example in Django:
import cloudinary
img = cloudinary.CloudinaryImage("autumn_leaves.jpg")
img.image(transformation=[
          dict(width=0.15, crop='scale', radius='max', 
               border=dict(width=10, color='#00390b60')), 
          dict(angle=5), 
          dict(underlay='site_bg', width=250, height=200, effects='brightness:50')])
And one last example - the following URL generates an image based on a Facebook profile picture that was automatically fetched by Cloudinary. The image is resized and rounded, and a black border is added. We then use an overlay to add Cloudinary's logo with a semi-transparent wide border. As with all of the Cloudinary managed images, the resulting image is persistently stored in the Cloud and then delivered and cached through a fast CDN.
 
 
 
By the way, you can also add the border as an incoming transformation so the original image is stored in the cloud already with the border. Here's such an incoming transformation, this time in Node.js:
cloudinary.image("itail.jpg", { type: 'facebook', transformation: [
                 { crop: 'fill', width: 150, height: 180, radius: 10, 
                   border: { width: 2, color: 'black'}},
                 { overlay: 'cloudinary_logo_white', width: 90, 
                   gravity: 'south_east', radius: 5, y: 7, x: 7, 
                   border: { width: 6, color: '#afcee990'}}]})

Summary

If you are a regular reader of our blog, you know that Cloudinary keeps enhancing on various fronts. One of these fronts is our ever increasing set of image manipulation capabilities. In this blog we introduced a cool new enhancement that you might find useful. We have more in our pipeline. If you want to see a new image manipulation capability added to Cloudinary, just drop us a line.

API for extracting semantic image data - colors, faces, Exif data and more

Nov 21, 2012 by Nadav Soferman
When images are involved, web developers have a large set of relevant tools at their disposal. You can display images in your web sites and mobile applications. You can manipulate and transform such images using image editing and manipulation software or cloud-based solutions like Cloudinary. But there are other types of data embedded in image files that can add unique semantic information to the images and are hardly ever used.
 
Consider what new designs can appear if your graphics designer could assume that only blue themed user uploaded photos will be featured on your homepage. What about featuring only photos that show your users' faces? How about photos taken with new DSLR model cameras rather than older pocket ones? Only photos taken in the GPS vicinity of your website visitor? We believe that such capabilities can offer a new, important tool for web design and development. 
 
Unfortunately, such semantic data is usually locked safely within the images and rarely utilized by developers and designers. We hope that we can change that by introducing a new Cloudinary API that allows you to easily extract rich information regarding your website and mobile application's photos. Using this information you can search, sort and classify your images in amazing new ways.
 

Predominant Colors & Color Histogram

Image search services such as Google Image Search allow you to filter your image search to show only images of a certain color. How is it done? Each image is analyzed and the colors of the images are mapped to one or more leading colors.
 
Cloudinary now supports finding the leading colors of a given image using a standard palette of 12 main colors. Since Cloudinary is a cloud-based service, all image processing is done online and no software installation is required on your side.
 
Finding the predominant colors in an image is also useful for stock-photo sites that wants to allow you to narrow photo searching by colors (see our previous post of how-to quickly build a stock-photo site with Cloudinary) and for e-commerce sites. For example: if you have a fashion site, and you want your users to browse only blue or red shirts.
 
For example, the following image with the public ID 'fashion1' was uploaded to Cloudinary:
 
 
 
Using Cloudinary's Admin API, you can extract the photo's main colors by setting the 'colors' parameter to true (see reference documentation). Here are examples for Ruby, PHP, Node.js and Python:
Cloudinary::Api.resource('fashion1', :colors => true)
$api->resource("fashion1", array("colors" => TRUE));
cloudinary.api.resource('fashion1',  
                        function(result)  { console.log(result) }, { colors: true });
cloudinary.api.resource("fashion1", colors = True)
 
Below is the JSON result of this API call. It seems that the main colors of this image are white (50.7%) and blue (27.8%), with touches of gray and brown. Cool.
{
  "public_id": "fashion1",
  "width": 225,
  "height": 380,
  ...
  "predominant": {
    "google": [
      [ "white", 50.7 ],
      [ "blue",  27.8 ],
      [ "gray", 11.2 ],
      [ "brown", 5.1]
    ]
  }
}
Using this info, you can keep the color mapping in your model and allow clothes to be searched based on colors. Searching for blue clothes should return this product.
 
Another result you get as part of the color information API is a histogram of 32 RGB colors that best represent the image. The following JSON snippet was also included in the result of the API call.
{
  "public_id": "fashion1",
  ...
  "colors": [["#FFFFFF", 50.7], ["#011B43", 5.8], ["#5077A7", 4.9], ["#031235", 4.3], ["#F4CBB4", 3.3], ["#3A6498", 1.9], ["#6284AF", 1.9], ["#2D5E95", 1.9], ["#30578B", 1.8], ["#080918", 1.8], ["#E5B09D", 1.8], ["#36262F", 1.7], ["#264876", 1.6], ["#281A25", 1.5], ["#486A99", 1.4], ["#E3D6CF", 1.4], ["#4D3135", 1.4], ["#07264F", 1.2], ["#664E55", 1.1], ["#6E443C", 1.0]]
}
As you can see, you get RGB format and percentage breakdown of the 32 colors that best represent the image. '#FFFFFF' is white, representing around half of the image, followed by multiple blue shades (e.g., '#011B43' is 5.8%).
 

Face detection info 

Cloudinary supports face detection based cropping and pixelation. Either a single face or multiple faces can be automatically detected. Our API now supports returning additional information regarding the detected faces in an uploaded photo. 
 
Simply set the 'faces' parameter to true in the same method we showed above for 'colors'. Note that you can enable multiple flags in a single call for fetching all information at once. The result includes the exact coordinates of all detected faces, allowing you to easily find out how many faces are available in the photo and their exact positions.
 
The following Ruby command asks for the faces information of the 'fashion1' image:
Cloudinary::Api.resource('fashion1', :faces => true)
Here is the JSON result:
{
  "public_id": "fashion1",
  ...
  "faces": [[99, 21, 64, 87]]
}
 
As you can see, a single face was correctly detected. It is positioned in the 99,21 - 64,87 rectangle of the original image.
 
Same works for images with multiple faces:
 
{
  ...
  "faces":  [ [513, 19, 38, 52], [409, 26, 40, 54], [79, 31, 43, 59], [232, 32, 40, 54], [321, 33, 41, 57], [160, 37, 43, 59], [211, 153, 43, 59], [503, 151, 43, 59], [113, 162, 40, 54], [427, 160, 45, 61], [307, 172, 48, 65] ]
}
Note that face detection does not achieve 100% accuracy. If you need better accuracy, human moderation is recommended.
 

Camera information - Exchangeable image file format (Exif)

Modern digital cameras and smartphones store additional metadata as part of the image files you shoot. Such information includes picture orientation, timestamps, camera model information, photo exposure, GPS location and more.
 
By setting the 'exif' parameter to true, Cloudinary's API can return the image's metadata (see our reference documentation). In the sections above we've shown how to use the Admin API for fetching information of previously uploaded images. You can also request this information while uploading the photos, so it is returned as part of an upload response.
 
For example, the following PHP command uploaded to Cloudinary a photo that was taken by an iPhone 4 in a portrait orientation.
\Cloudinary\Uploader::upload("exif_sample.jpeg", 
   array("public_id" => "exif_sample", "colors" => TRUE, "exif" => TRUE))
 
Here is the JSON of the upload response including the requested Exif and Colors information:
{ 
  "public_id": "exif_sample",
  "width": 2592,
  "height": 1936,
  ...
  "exif": {
    "ApertureValue": "4281/1441",
    "ColorSpace": "1",
    "ComponentsConfiguration": "1, 2, 3, 0",
    "Compression": "6",
    "DateTime": "2010:12:27 11:17:34",
    "DateTimeDigitized": "2010:12:27 11:17:34",
    "DateTimeOriginal": "2010:12:27 11:17:34",
    "ExifImageLength": "1936",
    "ExifImageWidth": "2592",
    "ExifOffset": "204",
    "ExifVersion": "48, 50, 50, 49",
    "ExposureMode": "0",
    "ExposureProgram": "2",
    "ExposureTime": "1/4309",
    "Flash": "24",
    "FlashPixVersion": "48, 49, 48, 48",
    "FNumber": "14/5",
    "FocalLength": "77/20",
    "GPSAltitude": "20723/924",
    "GPSAltitudeRef": "0",
    "GPSImgDirection": "42155/344",
    "GPSImgDirectionRef": "T",
    "GPSInfo": "574",
    "GPSLatitude": "21/1, 768/100, 0/1",
    "GPSLatitudeRef": "N",
    "GPSLongitude": "86/1, 4500/100, 0/1",
    "GPSLongitudeRef": "W",
    "GPSTimeStamp": "17/1, 17/1, 3326/100",
    "ISOSpeedRatings": "80",
    "JPEGInterchangeFormat": "870",
    "JPEGInterchangeFormatLength": "9932",
    "Make": "Apple",
    "MeteringMode": "1",
    "Model": "iPhone 4",
    "Orientation": "6",
    "ResolutionUnit": "2",
    "SceneCaptureType": "0",
    "SensingMethod": "2",
    "Sharpness": "2",
    "ShutterSpeedValue": "4781/396",
    "Software": "4.2.1",
    "SubjectArea": "1295, 967, 699, 696",
    "WhiteBalance": "0",
    "XResolution": "72/1",
    "YCbCrPositioning": "1",
    "YResolution": "72/1"
  },
  "colors":[["#CBC9C5",10.2],["#C4BCB4",9.0],["#1888AB",6.0],["#202618",6.0],["#226391",5.4],["#223A62",4.3],["#B9B4AD",3.8],["#2F88A1",3.5],["#C9C3BA",3.4],["#7492B2",3.4],["#157193",3.1],["#96ABCC",2.9],["#C8B495",2.8],["#4F97AB",2.8],["#484033",2.7],["#669FAD",2.5],["#A0A29E",2.4],["#38A7C8",2.3],["#57A5B7",2.3],["#2D8FAF",2.2],["#ACCADC",2.1],["#073554",2.0],["#60AFC7",2.0],["#1D4A6F",2.0],["#A39477",1.9],["#D1C4A0",1.8],["#296F96",1.7],["#4F6E91",1.5],["#5F5F57",1.4],["#90AECB",1.0]],
  "predominant": {"google":[["teal",41.7],["brown",35.6],["blue",12.1],["green",8.4]]
}
By the way, you can also use Cloudinary's Exif-based automatic rotation by setting the 'angle' parameter ('a' for URLs) to 'exif'. For example:
 
 
 

Summary

With the additional knowledge of image metadata and semantic information, you can enhance your image rich web and mobile applications with little effort, while Cloudinary does all the heavy lifting for you. These additional layers of information adds an important aspect that allows Cloudinary to offer a better than ever cloud-based solution to all your online image management and manipulation needs. 
 
All these new features were requested by Cloudinary's users and we thank all of you for that. We have plenty more ideas for enhancing Cloudinary's capabilities in this area and would love to hear your feedback and suggestions.
 
The ability to fetch Exif, FacesPredominant colors and Color histogram is now available to all of Cloudinary's plans, free and paid. Click here to setup a free Cloudinary account.

Engine Yard add-on for cloud-based image management

Oct 31, 2012 by Itai Lahan
When we first started working on Cloudinary we had a very simple goal in mind - offer a complete alternative to a set of rudimentary, repetitive, universally common web dev tasks. Tasks related to a website's image management needs.
 
As a web developer, you surely found yourself spending considerable time performing the same routine asset management tasks over and over again. Managing image uploads, transformations, manipulations, optimizations, caching and back-ups. Configuring a fast, highly available asset delivery solution. Same tasks, over and over again.
 
Cloudinary was built to streamline all of the above and we're very proud with what we've accomplished with Cloudinary so far. What started as a simple concept, turned out to be a great service that completely solves all your online image management tasks.
 
The fact that took us by surprise was the diversity of frameworks used by our customers. It sometimes felt that each new user has utilized his own web development stack. Ruby developers using Rails or Sinatra, PHP developer using one of the countless PHP frameworks, Python and Django developers, Node.js, Perl, Java, ASP, .NET, iOS, Android and many others.
 
It turns out that as complicated it is to build a highly scalable, highly usable service like Cloudinary, it's still only half of the story. The other half is offering our users a solution that is easy to integrate with their web dev platform of choice. 
 
Lately, we've been hard at work adding client side Cloudinary integration libraries for every major web dev platform and programming language. We've also kept a close eye on the state-of-the-art platform-as-a-service solutions that offered their users a single click integration solutions for a vast array of cloud-based services. Today, we've taken another important step on making Cloudinary even more accessible and easy to use.
 
Without further ado, we're happy to announce our partnership with Engine Yard. 
 
Engine Yard is a senior player in the PaaS field and one of the pioneers of the approach that took cloud computing a step forward: developers take care of the application development only, while Engine Yard takes care of the production platform. You no longer need to manage production servers and complex database architecture. Engine Yard is unique in this field in providing a full management solution for large scale platforms and high-end sites and applications.
 
 
With Engine Yard you have your application deployed in the cloud. Together with Cloudinary, your asset management is also moved into the cloud: upload images, automatically perform smart image resizing, cropping, overlay, watermark, apply effects, rotations, format conversions, without installing any complex software. All your images are then seamlessly delivered through a fast CDN, optimized and using industry best practices. Cloudinary offers comprehensive APIs and administration capabilities and is easy to integrate with new and existing web and mobile applications.
 
Together with Engine Yard, Cloudinary offers a very useful solution for a wide array of use-cases from simple websites, through early stage startups to large scale enterprise applications. If you are already an Engine Yard user, simply add Cloudinary's add-on to your Ruby, PHP and Node.js applications. Cloudinary’s account setup is done automatically for you and billing is handled through your standard Engine Yard payment method. Cloudinary offers a free Starter plan with plenty of room to grow, making it very straightforward to try it out.
 
 

Engine Yard users - want to start using Cloudinary?

  • Go to https://cloud.engineyard.com/addons or navigate to 'Add-ons' in Engine Yard Cloud and click on Cloudinary and start managing your images in the cloud!
  • Engine Yard automatically sets up the correct settings for using your Cloudinary account using the CLOUDINARY_URL variable. 
Ruby on Rails users - simply add the ey_config GEM to your project and add an initializer for Cloudinary's settings:
Cloudinary.config_from_url(EY::Config.get(:cloudinary, 'CLOUDINARY_URL'))
We will soon add additional documentation and sample code for simplifying the Cloudinary - Engine Yard integration even further. Any feedback on our new image management add-on for Engine Yard would be highly appreciated!
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