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Managing Permissions in Video Conferencing Apps: 3 Access Models

Three access models for video conferencing permissions

Everyone benchmarks video conferencing on the things you can see: resolution, latency, how many people fit in a grid. But the failures that actually hurt in production are rarely about a dropped frame — they're about the wrong person joining a room they shouldn't be in, or a private recording ending up somewhere public. Permissions are the invisible half of a video app, and they're the half most teams underestimate until something goes wrong.

  • in Release
  • 7 min read

OpenVidu 3.8.0 is now available

OpenVidu 3.8.0 brings a major step forward for both OpenVidu Platform and OpenVidu Meet.

On the OpenVidu Platform side, the standout change is a complete mediasoup overhaul: RTX, DTX, AV1/VP9/H264 codecs and SVC are now fully supported, bringing mediasoup on par with Pion in terms of features while delivering a 2x performance boost. This release also tightens TURN security and improves the robustness of deployments across all supported clouds.

On the OpenVidu Meet side, this release introduces real user accounts with role-based access and fine-grained, per-person room permissions, turning the previous "share a link" model into a complete access control system. It also comes with a redesigned application, now fully translated into 10 languages, and a range of improvements to the in-meeting experience.

Continue reading for the complete release notes of both products.

We deployed the same video platform on five clouds and timed it: 5 minutes to 20, and the slow ones are slow for a reason

Mean time to a working deployment, by cloud and topology Mean time to a working deployment, by cloud and topology

"How long does it take to deploy?" sounds like a trivia question until you're the one watching a progress bar, wondering whether it's stuck. So we stopped guessing and measured it.

We built a tool, ov-cloud-tester, that deploys the same self-hosted WebRTC video stack on all five major clouds — AWS, Azure, Google Cloud, Oracle Cloud and DigitalOcean — in three topologies (single node, elastic, and high-availability), tears it down cleanly, and times the whole thing. We ran it many times per cloud and looked at both the averages and every individual run. The headline: standing up a working deployment ranges from about 5 minutes to 20, DigitalOcean is consistently the fastest and Oracle the heaviest — and the why, plus which clouds are actually predictable, turns out to be more interesting than the ranking.

Host Your Own Secure Video Calls at Home: A Private Server for Family and Friends

A secure family video call running on your own home server

We're all used to reaching for a third-party app to call friends and family: Google Meet, Zoom, Microsoft Teams, etc. Almost nobody wants to complicate their life by running their own server, and if you mention "spinning up a WebRTC media server" to an experienced sysadmin, they'll probably put their head in their hands thinking about how complicated it must be.

In reality, it's much easier than you might think. At OpenVidu we've worked hard to make a self-hosted video conferencing service as easy to install and run as possible, and hosting it yourself comes with some genuine advantages. It's completely free, there are no 40-minute timers or participant limits, your guests join straight from a browser with no account and no app, and every call stays on hardware that lives in your own home.

With a tiny computer like a Raspberry Pi, an old laptop or a mini-PC, you can have your own private video conferencing server running in a matter of minutes. This guide walks you through it in three simple steps using OpenVidu Meet.

5 conversational AI app ideas you can build this weekend

Conversational AI app ideas for 2026 — real-time voice and vision agents you can build this weekend Conversational AI app ideas for 2026 — real-time voice and vision agents you can build this weekend

AI is moving faster than any of us can comfortably keep up with. Every week brings a new model, a new demo, or a viral thread claiming that everything has changed again. Keeping up feels almost impossible.

As AI becomes mainstream, the noise grows even louder. Social feeds are packed with promises of overnight success: build a startup with vibe coding, replace entire teams with a handful of prompts, make money while you sleep.

This post isn't another one of those promises.

Instead, you'll find five conversational AI app ideas you can realistically build over a weekend. Some are practical, some are a little unconventional, but all of them will teach you something valuable about how modern AI systems actually work.

More importantly, these aren't just toy projects. They can help you develop real AI skills, build a portfolio, test business ideas, and maybe even create something people are willing to pay for.

Choosing the right level of abstraction in self-hosted WebRTC solutions in 2026: OpenVidu Meet vs OpenVidu Platform

OpenVidu Meet vs OpenVidu Platform

In this blog post we explore how different levels of abstraction are needed in the WebRTC arena, and which choices do you have when using the OpenVidu WebRTC ecosystem.

Why Abstraction Matters

People are diverse, and that’s what makes life interesting. In the world of real-time communications (RTC), diversity means that different users require entirely different levels of abstraction to get the job done, from a "batteries included" scalable meeting application, to an extremely customizable media processing pipeline with access to low-level media SDKs and APIs.

The Architecture of Scale: How to Scale Video Conferencing from a Single Server to a High-Availability System

WebRTC connectivity paths

Introduction: The Success Trap

Launch week often feels perfect. You ship an MVP, users join calls quickly, and early feedback is strong. Then growth arrives faster than expected.

One customer schedules a company-wide meeting. Hundreds of people join. Your best demo becomes your first major incident: CPU climbs, bandwidth saturates, audio breaks, video freezes. The product didn't fail because the team lacked talent. It failed because real-time media scales very differently from traditional web applications.

Stateless APIs can usually absorb demand with more replicas and a load balancer. Video conferencing can't. Each participant holds a long-lived, stateful connection, and every audio and video packet has to be encrypted and routed with very low latency. A database query can afford to wait 200 ms. A conversation can't — your users notice jitter, gaps, and packet loss the instant they happen.

That's what makes scaling video a genuinely hard problem. It's not a hardware question you solve by adding RAM. You need an architecture that grows with you. This guide walks through a three-phase roadmap:

  1. Single Node — where almost every successful product starts.
  2. Horizontal Elastic Media Plane — how to scale the part of the system that actually processes calls.
  3. High-Availability Control Plane — how to stop a single failure from taking down the entire platform.

Along the way, you'll also learn how to build an autoscaling loop that reacts before saturation hits, and how admission rules can protect call quality even when traffic bursts unexpectedly.

Scaling Up is easy, the challenge is Scaling Down: The Scale-In problem in videoconferences.

Autoscaling is one of the killer features of cloud infrastructure. It promises zero-waste elasticity: when demand rises, you spin up more nodes; when demand drops, you shut them down and stop paying for them. For most cloud workloads, this works beautifully. But for real-time media platforms — videoconferencing systems built on top of media servers — the "shut them down" part is far more dangerous than it first appears.

Scale In

Scale in situation

This post dives into the scale-in problem: why you can't simply terminate a media server node that has active meetings running inside it, how the broader cloud industry has addressed it, and how OpenVidu implements a robust solution across AWS, Azure, GCP and Digital Ocean.

5 React video call platforms in 2026: Is SaaS still the right choice?

React video call platforms in 2026 — SaaS vs Self-hosted

1. Introduction

When React developers need to add video calls to their applications, the first question is usually simple:

"What is the fastest way to get it working?"

Most teams start by looking for a video API with a React SDK they can integrate quickly, without dealing directly with WebRTC complexity.

In practice, that usually means exploring well-known SaaS platforms that promise quick setup and minimal infrastructure work. That choice makes sense at the beginning:

  • Fast to integrate
  • No infrastructure headaches
  • Familiar turnkey experience

But there are questions teams often ask too late:

  • What happens when video becomes core to your product?
  • What happens when usage grows faster than expected?
  • Is paying per minute still the smartest choice in 2026?