Customizing your Kaltura CE Remote Storage Profile

Kaltura CE comes with several solutions for Storing and Playing your Video out-of-the-box, but sometimes Kaltura CE Remote Storage doesn’t offer the exact solution to fit your requirements.
If you can’t find a suitable solution from the list of features that come with Kaltura CE, you can always rewrite and enhance the Remote Storage Profile.
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Red5 init Script for Ubuntu

If you’ve read our Installing and Integrating Red5 with Kaltura CE5 post, you have probably encountered several errors when starting or stopping the Red5 Server.

./red5: 14: .: Can't open /etc/rc.d/init.d/functions
./red5: line 30: success: command not found
./red5: line 30: failure: command not found

The above error messages occur because the Red5 init Script is written for CentOS and not for Ubuntu.

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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

The best and fastest way to Deploy Kaltura CE by Panda-OS

Kaltura CE is the best open-source solution for Online Video Management, however building a working Kaltura CE environment is not an easy task.
Here at Panda-OS we have combined our tools, vision, and knowledge of Kaltura in order to quickly deploy, migrate, or rebuild a Kaltura CE environment.

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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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