Voices of Video

When a major live event is only hours away, “we couldn’t get the GPU instance” is not an acceptable outcome.

Cloud capacity constraints are forcing video teams to reconsider how they approach live transcoding, infrastructure availability, operational complexity, and the true cost of delivering IP video at scale.

In this episode, we sit down with Tim Baldwin, VP of Product Management at Zixi, to explore how a company widely known for reliable video transport evolved into a complete live IP video platform.

We start with Zixi’s roots in transporting broadcast-quality video over unmanaged networks. From there, we examine how Zen Master orchestration, observability, automation, and workflow management help teams operate large fleets of live streams without turning every deployment into a custom engineering project.

Tim explains why protocol-agnostic architecture matters in real customer environments. Depending on who controls each endpoint, a workflow may involve the Zixi Protocol, SRT, RIST, RTP, RTMP, or several of them at once. Supporting that reality allows broadcasters, OTT providers, and technology partners to build around their existing infrastructure and business relationships.

We also get practical about the operational demands of modern streaming workflows, including:

• Normalizing hundreds of incoming streams 
• SCTE-35 conditioning and management 
• Market switching, regionalization, and blackout requirements 
• Dynamic pre-roll, mid-roll, and post-roll insertion 
• HTML overlays and graphics 
• Seamless switching controlled through APIs 
• Rapid deployment for temporary channels and live events 

Tim breaks down the competitive landscape, from internal DIY platforms to traditional broadcast vendors moving legacy products into software and cloud environments.

Then we dig into one of the most urgent infrastructure challenges facing live video teams: transcoding capacity.

What happens when the NVIDIA GPU instance your workflow depends on is unavailable in the required cloud region?

Tim discusses Zixi’s journey from CPU and GPU transcoding to NETINT video processing units (VPUs), including how greater transcoding density can reduce instance counts, infrastructure overhead, and total cost of ownership. We also explore deployments on Akamai Connected Cloud and within Zixi as a Service, where fast onboarding and predictable capacity are critical.

In this episode:

• How Zixi evolved from a media server and transport protocol into a broader live video platform 
• How Zen Master simplifies orchestration, monitoring, and fleet management
• Why protocol-agnostic workflows matter when partners require SRT, RIST, RTP, or RTMP 
• How broadcasters, OTT providers, and virtual MVPDs use the platform 
• Automation for dynamic advertising, graphics, switching, and lightweight production 
• The differences between purpose-built platforms, DIY systems, and legacy broadcast software 
• Why cloud GPU availability is influencing transcoding architecture 
• How NETINT VPUs increase density and reduce the number of required instances 
• Deployment options including licensed software, a SaaS control plane, and Zixi as a Service 
• Pricing models aligned with channels and events rather than protocol usage 
For teams evaluating live streaming architecture, the conversation offers a practical look at reliability, interoperability, cloud availability, automation, and the operational economics behind modern IP video.

Explore Zixi’s live video platform and discover NETINT’s purpose-built video encoding solutions.
Stay tuned for more in-depth insights on video technology, trends, and practical applications. Subscribe to Voices of Video: Inside the Tech for exclusive, hands-on knowledge from the experts. For more resources, visit Voices of Video.

Your cameras might be "AI ready," but your security stack can still grind to a halt for a simple reason: video has to be decoded, resized, and converted before any AI model can use it. That invisible work is where many surveillance systems hit their limits, even when GPUs are already reserved for inference.

In this episode, we sit down with Isaac Connor, longtime open source developer and one of the driving forces behind ZoneMinder, to explore how CCTV and video management systems have evolved over the past 15+ years.

We discuss the architectures powering everything from small business NVRs to enterprise and government deployments, why so many systems still depend on scaling commodity CPUs, and what changes once AI enters the picture.

We also dive into the codec reality of modern surveillance. H.264 remains manageable, HEVC raises the compute requirements, and AV1 can dramatically increase decoding costs, especially when analytics are added on top.

Because much of the surveillance industry is built around FFmpeg, Isaac explains why adding VPU acceleration can feel like an engine transplant rather than a complete rebuild. We cover high-density video decoding, power and PCIe slot constraints, ONVIF interoperability, and how dedicated video processing can dramatically improve scalability while reducing infrastructure costs.

If you're building or modernizing a VMS, NVR, or AI video analytics platform, this conversation offers practical insight into where today's bottlenecks really are and how to design systems that scale.

Topics covered

- ZoneMinder's origin story and the evolution of open source VMS
- The three tiers of surveillance deployments, from home users to government-scale systems
- Why cloud VMS costs often reflect inefficient video architectures
- The hidden workload between video decode and AI inference
- High-density decoding and why CPUs quickly become the bottleneck
- H.264, HEVC, and AV1 in real-world surveillance deployments
- Power, PCIe slots, and why compact VPUs change server design
- How ONVIF simplifies camera discovery, capability negotiation, and PTZ control
- Modernizing FFmpeg-based video pipelines without rewriting applications
- Where dedicated video processing fits into the future of security analytics

Learn more about NETINT: https://netint.com
Learn more about ZoneMinder: https://zoneminder.com

Interested in joining Voices of Video?

If you're building innovative technology in video, streaming, AI, broadcasting, surveillance, or media infrastructure, we'd love to hear your story. Reach out and let's explore whether your work would make a great episode.
Stay tuned for more in-depth insights on video technology, trends, and practical applications. Subscribe to Voices of Video: Inside the Tech for exclusive, hands-on knowledge from the experts. For more resources, visit Voices of Video.

Spinning up high-performance video encoding should not require a weeks-long infrastructure project or a hyperscaler feature request.
Mark Mahle, co-founder and CEO of NetActuate, joins Voices of Video to discuss a network-first approach to global infrastructure as a service, and why the “plumbing” of the internet still determines whether video workflows feel fast, flexible, and resilient.
In this episode, we look at where NetActuate fits between public cloud, co-location, and private data centers, and why infrastructure choice is becoming a key driver for video teams. Cost matters, but so does the ability to run the right workload in the right location with the right hardware. That includes predictable capacity, low-latency connectivity, and specialized compute like NETINT VPUs.
Mark explains how NetActuate’s global footprint and highly peered network support real-world services at scale, then we move into what this means for streaming, transcoding, and live event workflows.
The episode also includes a hands-on demo: deploying a virtual machine with a NETINT VPU attached, selecting firmware, viewing accelerator details, and using observability signals across the deployment. We also look at managed Kubernetes nodes with VPUs for cloud-native video workflows.
Then comes the “wait, what?” moment: controlling NETINT’s BitStreams media processing framework through an AI assistant using plain language. The demo shows Claude creating an adaptive bitrate ladder, applying overlays, and starting a DASH output that can be played immediately.
If you are building video streaming infrastructure, evaluating VPUs for hardware-accelerated encoding, or trying to lower cloud spend without giving up speed, this episode is worth watching.
In this episode:
• Why network-first infrastructure matters for latency-sensitive video
• How NetActuate fits between hyperscalers, co-location, and private data centers
• Why teams want more flexibility, custom hardware access, and cost control
• How NETINT VPUs can be deployed through NetActuate’s global platform
• VM provisioning with an attached VPU
• Firmware selection and accelerator visibility
• Observability for VPU-powered deployments
• Managed Kubernetes nodes with VPU access
• Using an AI assistant to control BitStreams workflows in plain language
• Creating ladders, overlays, and DASH output through natural language commands
For cutting-edge video encoding solutions, visit NETINT at https://netint.com.
Subscribe to Voices of Video for more hands-on conversations with the people building the next generation of video infrastructure.
Stay tuned for more in-depth insights on video technology, trends, and practical applications. Subscribe to Voices of Video: Inside the Tech for exclusive, hands-on knowledge from the experts. For more resources, visit Voices of Video.

Cloud video infrastructure is getting squeezed from both sides: audiences expect better quality and more formats like AV1, while finance teams are staring down cloud bills that don’t scale with reality.
We sit down with Sarah Walter from Akamai for a one-year check-in on VPU-accelerated instances powered by NETINT, and what stands out is how quickly the conversation has moved from pilots to production. Sarah shares what she’s seeing across customers, from hyperscalers expanding internationally to broadcasters and streaming platforms looking for a practical step between fully managed services and running everything on-prem.
We dig into what’s driving adoption of VPUs for video transcoding and encoding on Akamai Cloud, including new locations in Europe like Frankfurt and London for higher availability designs. We also talk through the “bring your own software” challenge and how making Bitstreams available helps teams operate VPUs with a GUI instead of living in command lines all day.
For larger deployments, we break down new eight-card plan options and why density matters when you’re measuring cost per stream across live streaming, VOD, premium content, and user-generated workloads.
Operationally, we get specific about the parts nobody advertises: firmware updates, SDK dependencies, and how to balance rapid quality improvements with customer stability in an infrastructure-as-a-service environment.
Finally, we connect the dots to NAB season themes like global hardware supply chain pressure and why “getting off the cloud” often really means finding a more sustainable cloud pricing model.
Key topics
• One-year progress on Akamai Cloud VPU adoption and new VPU-backed VM SKUs
• Customer profiles including hyperscalers expanding beyond on-prem points of presence
• Live streaming and VOD workloads across premium and user-generated content
• Why Bitstreams matters as a GUI bridge for teams coming from managed services
• Partner ecosystem support for advanced requirements such as DRM
• The reality of firmware upgrade cycles in IaaS and how SDK dependencies affect rollouts
• New European footprint with London and Frankfurt for higher availability designs
• How to estimate VPU density using a 32× 1080p30 benchmark
• What NAB conversations reveal about supply chain pressure and cloud pricing sustainability
Stay tuned for more in-depth insights on video technology, trends, and practical applications. Subscribe to Voices of Video: Inside the Tech for exclusive, hands-on knowledge from the experts. For more resources, visit Voices of Video.

Swapping the engine while it runs sounds risky - and in production video systems, it is.
Hardware acceleration often gets positioned as “faster encoding,” but that’s not what makes engineering teams hesitate. The real challenge is introducing a new compute model without breaking workflows that already carry years of integrations, monitoring, and operational assumptions. As NAB approaches and the industry talks density and efficiency, the more important question is this: how do you evolve a platform without increasing fragility?
Leo Nieto from NETINT sits down with Dominique Vosters from Scalstrm to unpack what actually triggers the shift away from CPU-only scaling. The answer is less about technology hype and more about cost per stream across the full workflow, from transcoding through packaging and delivery. We explore why teams hesitate, what they are most concerned about breaking, and why live streaming raises the stakes compared to VOD.
We also get practical about architecture. Dominique explains how hardware acceleration fits into a broader system, where VPUs handle encoding while software layers manage resilience, synchronization, and recovery. From the outside, workflows often remain consistent. The real changes happen inside the system, where compute is relocated rather than the architecture being rebuilt.
Finally, we walk through a low-risk rollout approach: parallel environments, staging validation, and gradual channel-by-channel migration instead of big bang transitions.
If you are planning hardware-accelerated transcoding, VPU-based encoding, or broader video workflow optimization, this conversation will help you improve efficiency while protecting production stability.
Key topics covered
• why CPU-based video workflows become unsustainable primarily due to cost pressure across transcoding, packaging, and delivery
• why hesitation around hardware acceleration comes from fear of disrupting production systems, not skepticism about the technology
• differences between VOD and live streaming workflows, and why live environments require more cautious rollout strategies
• how hardware acceleration fits into existing architectures, with software layers handling resilience, synchronization, and recovery
• what actually changes when acceleration is introduced versus what remains stable for operators and workflows
• the concept of “swapping the engine while it runs” by keeping input and output behavior consistent while moving compute inside the system
• when orchestration layers add value and how that depends on platform maturity and scale
• practical deployment strategies including parallel environments, staging validation, and gradual channel-by-channel migration
Stay tuned for more in-depth insights on video technology, trends, and practical applications. Subscribe to Voices of Video: Inside the Tech for exclusive, hands-on knowledge from the experts. For more resources, visit Voices of Video.