Setting Up Kaltura S3 Cloudfront CDN – CE 9 External Storage With CDN Delivery

Hi,

Today I was asked by one of our clients to install a Kaltura cluster with Amazon S3 storage Cloudfront CDN. Kaltura S3 Cloudfront is a popular setup among our customers. For assistance, I used our old blogpost (posted about a year ago): SETTING UP KALTURA CE 5.0 AMAZON S3 STORAGE CLOUDFRONT CDN – EXTERNAL STORAGE WITH CDN DELIVERY which explains very well how to set up Kaltura CE Amazon S3 Storage and Cloudfront CDN. Although it was very helpful, I found a bit of a difference between Kaltura CE 5.0 and CE 9.X versions. I thought that an updated post regarding this issue would be a good idea.
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The Panda Kaltura AWS Cluster – S3 and Cloudfront

In the previous posts we have discussed the various Amazon AWS services and how we use them for operating Kaltura CE clusters. In this post, we will discuss the last part of our cluster: the video storage and streaming. A Kaltura deployment usually stores the videos locally on the file system. While this is good for small installations, sometimes you want the flexibility and durability of a remote storage.
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Delete Kaltura Entries from Amazon S3 Bucket

Delete Kaltura Entries from S3 Bucket Automatically

When setting up a Kaltura cluster, you usually want to store the entries on a remote storage like an Amazon S3 bucket. The problem is that when deleting entries using the Kaltura KMC, they are not deleted from the bucket, which can cost you money.

We have previously written about using S3 with Kaltura, which included several fixes to the Kaltura database. To delete Kaltura Entries from S3 Bucket automatically, we need to perform several code and database fixes which are described below. Continue reading

Introduction to the Panda Kaltura AWS Cluster

We are excited to launch a new post series about the Panda Kaltura AWS cluster. Kaltura is an open source video platform loaded with features. The platform can be partitioned into multiple machines for scalability, performance and robustness. However, deploying, installing and scaling is not an easy task, and many changes and configurations have to be made manually.

Amazon AWS is a cloud computing platform launched in 2006. It includes dozens of services which integrate well with each other and enable a lot of flexibility. Services include CloudFront (content delivery network), S3 (object store), EBS (persistent storage), EC2 (computing) Load Balancing, Elastic IPs and more.

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Deploy a Kaltura CE5 Cluster on AWS

The Kaltura CE5 video server can be deployed as a stand alone server, but to serve many users a distributed setup is required. Setting up a Kaltura CE5 cluster on AWS also enables adding more servers when needed with no impact on availability.

At PandaOS we wrote a web interface for making such deployments automatic and easy with using Amazon Web Services. Below I describe the setup required on AWS to install a distributed Kaltura environment.

Before you start the installation, you need to create an AMI (Amazon image) of a machine with Kaltura installed on it. Then you can use that image to launch all your Kaltura instances.

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