Live Broadcast Streaming: Professional Workflows with Vajra Cast

The Broadcast Challenge

Live broadcast production demands absolute reliability. Whether you are delivering a daily news program, a sports event, or a corporate webcast, the requirements are the same: the stream must arrive at the right place, at the right time, without interruption. A single dropped feed during a live broadcast is a failure visible to every viewer.

Professional broadcast workflows involve multiple cameras, multiple destinations, protocol conversion, failover, and real-time monitoring. Traditional broadcast infrastructure handles this with expensive dedicated hardware. Vajra Cast provides the same capabilities in software, running on standard servers and deployable anywhere.

A Typical Broadcast Workflow

Here is a professional broadcast workflow built entirely on Vajra Cast:

Stage 1: Multi-Camera Ingest

A broadcast studio typically has multiple camera sources. Each camera feeds an encoder that sends to the central routing gateway:

Camera 1 (Studio) --> Encoder --> SRT --> Vajra Cast (Port 9001)
Camera 2 (Studio) --> Encoder --> SRT --> Vajra Cast (Port 9002)
Camera 3 (Field)  --> Encoder --> SRT --> Vajra Cast (Port 9003)
Camera 4 (Remote) --> Encoder --> RTMP --> Vajra Cast (RTMP ingest)

Each input is configured independently:

• Studio cameras (Cameras 1-2): SRT listener on dedicated ports, low latency (60-120ms), AES-256 encryption over the internal network
• Field camera (Camera 3): SRT listener, higher latency (500-1000ms) to handle internet transport, encryption enabled
• Remote camera (Camera 4): RTMP ingest for a legacy encoder that does not support SRT

Stage 2: Failover Protection

For the primary program feed, you configure a failover chain:

Route: "Program Feed"

Primary Input:   Camera 1 (SRT, Port 9001)
Backup Input 1:  Camera 2 (SRT, Port 9002)
Backup Input 2:  Pre-recorded slate (HTTP/TS pull)

Vajra Cast monitors all inputs simultaneously. If Camera 1 drops (encoder failure, network issue, cable disconnected), the system switches to Camera 2 in under 50ms. If both cameras fail, it falls back to the pre-recorded slate. When Camera 1 recovers, Vajra Cast switches back automatically.

This failover chain runs continuously with no manual intervention. For details on configuring failover, see our video failover best practices article.

Stage 3: Distribution

The program feed is distributed to multiple destinations simultaneously:

Route: "Program Feed" --> Output 1: SRT to Master Control (production server)
                      --> Output 2: RTMP to YouTube Live
                      --> Output 3: RTMP to Facebook Live
                      --> Output 4: HLS for web player
                      --> Output 5: SRT to backup recording server

Thanks to Vajra Cast’s zero-copy internal multicast, adding outputs 2 through 5 costs zero additional CPU. The stream is distributed internally without re-encoding or re-packaging until it reaches the output stage where protocol conversion happens.

Stage 4: Monitoring

Every stream in the workflow is monitored in real-time:

• Per-input metrics: bitrate, packet loss, RTT, jitter (for SRT inputs)
• Per-output metrics: connection state, bitrate, error rate
• Route health: failover status, active input, time since last switch
• System metrics: CPU, RAM, GPU utilization per process

All metrics are available in Vajra Cast’s web dashboard and exported to Prometheus for Grafana integration. You can set up alerts in Grafana for critical conditions (input loss, bitrate drop below threshold, failover activation).

Workflow Patterns

Pattern 1: Simple Studio-to-Web

The most basic broadcast pattern. One studio encoder, one output.

Studio Encoder --> SRT --> Vajra Cast --> HLS --> CDN --> Viewers

Add a backup encoder and you have professional-grade reliability:

Primary Encoder   --> SRT --> Vajra Cast (failover) --> HLS --> CDN
Backup Encoder    --> SRT --> /

Pattern 2: Multi-Destination Simulcast

Broadcast the same feed to multiple platforms:

Encoder --> SRT --> Vajra Cast --> RTMP --> YouTube
                               --> RTMP --> Twitch
                               --> RTMP --> Facebook
                               --> HLS  --> Your website
                               --> SRT  --> Partner CDN

Each output can have independent settings. The YouTube output might target 6 Mbps while the Twitch output targets 4.5 Mbps (though bitrate adaptation requires transcoding).

Pattern 3: Contribution Network

Multiple remote locations sending to a central gateway for aggregation:

Location A --> SRT (encrypted) --> Vajra Cast Hub --> Production Router
Location B --> SRT (encrypted) --> /
Location C --> SRTLA (bonded)  --> /
Location D --> RTMP (legacy)   --> /

The hub receives all contribution feeds, monitors their health, and routes them to production. SRTLA bonding enables mobile locations to aggregate multiple cellular connections for reliable transport.

Pattern 4: Cascaded Gateways

For large-scale or geographically distributed broadcasts:

Venue Vajra Cast --> SRT --> Cloud Vajra Cast (Region A) --> HLS --> CDN
                 --> SRT --> Cloud Vajra Cast (Region B) --> HLS --> CDN

Two Vajra Cast instances in different regions provide geographic redundancy. Each generates its own HLS output for the CDN, and CDN-level origin failover provides the final layer of protection.

Hot Management in Production

During a live broadcast, requirements change. A sponsor requests their stream be added to a new platform. A backup destination needs to be swapped. A test output needs to be removed.

With Vajra Cast’s hot management, all of this happens without interrupting the live stream:

• Add an RTMP output to a new platform. Other outputs keep running.
• Disable a malfunctioning output: one click, zero impact on other destinations
• Change the destination URL of an output. The stream reconnects to the new target.
• Add a new backup input. The failover chain gains another layer of protection.

No restarts. No service interruptions. No hoping that the config reload does not break something.

Quality Assurance

Vajra Cast includes VMAF (Video Multimethod Assessment Fusion) quality scoring. During a live broadcast, you can trigger a quality analysis on any active route:

• Score from 0-100 indicating perceptual video quality
• PSNR measurements for objective quality assessment
• Historical trends to detect gradual degradation
• One-click triggering from the dashboard

This is particularly valuable when transcoding is in the chain. You can verify that your hardware-accelerated encode is maintaining acceptable quality in real-time.

Hardware Requirements

A typical broadcast gateway workload on Vajra Cast:

For passthrough routing (no transcoding), Vajra Cast is extremely lightweight. The CPU cost scales with transcoding complexity, not with the number of outputs (thanks to zero-copy distribution).

Next Steps

• Read the SRT Streaming Gateway Guide for the full architecture overview
• Learn about live event streaming for concert and conference workflows
• Explore remote production with SRTLA bonding
• See how hot management enables zero-disruption changes
• Set up SRT Streaming from scratch with our step-by-step guide