When your video platform starts getting thousands of concurrent viewers, playback performance can quickly turn into a challenge. Streams that once ran perfectly may begin buffering or fail during peak load. To keep playback stable for every viewer (no matter how many are watching), you need a system built to scale globally.

Kaltura Video Platform as a Service (VPaaS) provides exactly that. It gives you API-level control over uploading, transcoding, delivery, and analytics while automatically handling scaling through its CDN-backed infrastructure. You focus on content and integration; Kaltura manages performance, capacity, and distribution.

Getting Started with Kaltura VPaas

To scale video delivery, you first need to set up an account on Kaltura Video Platform as a Service, or VPaas for short. This platform lets you handle videos in the cloud, making it easier to reach more viewers without overloading your own servers.

Step 1: Sign up on the Kaltura VPaaS portal and create an account.

Step 2: Obtain your Partner ID, Admin Secret, and API key from the dashboard—these will authenticate all API requests.

Step 3: Install one of Kaltura’s SDKs (available for Node.js, Python, PHP, Java, and others) or connect directly via REST API.

Once authenticated, you can create, manage, and deliver content purely through API calls rather than manual upload tools.

Uploading and Preparing Your Videos

In VPaaS, video preparation is handled programmatically. You can upload files using the Media Service API. Each uploaded video entry can then be associated with predefined transcoding profiles, known as “flavors” to create renditions optimized for multiple bitrates and resolutions.

Step 1: Obtain an upload token using the uploadtoken.add API.

Step 2: Upload your media file (for example, .mp4, .mov, or .mkv) to that token endpoint.

Step 3: Create a media.add entry referencing the completed upload.

Step 4: Assign a suitable transcoding profile to generate adaptive renditions.

Step 5: Wait for the entry.status to move to “Ready.”

Configuring Delivery Settings for Scale

Kaltura’s delivery pipeline is backed by multiple global Content Delivery Networks (CDNs), such as Akamai and CloudFront. You don’t need to configure servers or manage edge nodes manually.

However, you can optimize delivery behavior:

Step 1: Use the Playback API to fetch dynamically generated playback URLs for different formats (HLS, DASH, MP4).

Step 2: Embed videos using Kaltura Player, which automatically selects the best CDN edge and quality level.

Step 3: For private or restricted content, secure playback using KS tokens (Kaltura Sessions) and signed URLs.

Step 4: Optionally integrate your own CDN or delivery gateway through custom delivery profiles.

All these settings ensure content delivery remains smooth when audience size surges globally.

Handling High Traffic with Built-in Tools

Kaltura VPaaS handles high traffic automatically through its multi-CDN network and elastic streaming architecture. You don’t need to set viewer limits or manual scale thresholds; backend scaling occurs dynamically across edge nodes.

Step 1: Create a live stream entry using liveStream.add.

Step 2: Retrieve the RTMP or SRT ingest endpoint provided by Kaltura.

Step 3: Stream your feed from an encoder such as OBS, Wirecast, or Elemental Live.

Step 4: Kaltura automatically distributes streams across CDN edges for load balancing.

Step 5: Viewers receive adaptive HLS or DASH playback optimized for their connection speed.

This architecture removes the need for setting manual viewer limits or scaling thresholds; traffic spikes are handled automatically across global edges.

Monitoring Performance and Making Adjustments

Kaltura’s Analytics API provides insights into user engagement, playback behavior, and delivery performance. Monitoring these metrics helps identify when to adjust encoding or improve user experience.

Step 1: Query the Analytics API to get viewer counts, buffering stats, and average bitrates.

Step 2: Review error reports (e.g., “start-up delay” or “stall ratio”) to locate performance bottlenecks.

Step 3: Adjust transcoding profiles if specific renditions are underperforming.

Step 4: Use data to fine-tune bitrate ladders and improve adaptive usability for mobile or low-bandwidth viewers.

Because VPaaS operates on elastic infrastructure, scaling adjustments happen automatically once your encoding and playback configurations are well tuned.