The Real Cost of Building WebRTC Video: A Complete Breakdown

The build vs buy question in real-time video almost always starts as a cost question. A developer spins up a peer-to-peer call in an afternoon, the demo looks polished, and suddenly the engineering estimate reads 'a few weeks'. That estimate isn't wrong; it's just answering the wrong question. It prices the prototype, not the production system that prototype has to become, and that's a different question entirely. By the time the gap between the two becomes visible, the team has already committed to a path that quietly consumes 6 to 18 months of engineering capacity and leaves a trail of operational obligations that never fully close.

This article is a cost-component map for anyone seriously weighing whether to build WebRTC video from scratch. A single number would be meaningless, because so much depends on scale, geography, and feature scope. Instead, it breaks the problem into its real parts: engineering effort, infrastructure burden, and the hidden costs that only surface once you have real users. It also offers a straightforward framework for making the build vs embed decision on the right axis.

Table of contents

1. The deceptive cheap part: a 1:1 WebRTC prototype
   
2. Where the cost actually accumulates: the production stack
   
3. The hidden costs teams forget
   
4. Build vs embed: the break-even
   
5. What do you stop paying for when you embed
   
6. Conclusion
7. Frequently asked questions

The deceptive cheap part: a 1:1 WebRTC prototype

WebRTC is a browser-native standard. Chrome, Firefox, Safari, and Edge all ship with the APIs built in. Establishing a direct video call between two browsers requires no media infrastructure of your own because the browsers negotiate the connection, encrypt the streams with DTLS-SRTP (the encryption protocol WebRTC uses by default), and pass media peer-to-peer. A developer who already understands the API can have something visually convincing running in a day or two.

This is both WebRTC's greatest strength and the source of almost every underestimation of what building video actually costs. The prototype is cheap. The problem is that it solves for one very specific topology: two participants on reasonably open networks, using up-to-date browsers. Remove any of those constraints, add a third participant, put one user behind a corporate firewall, test on Safari iOS, or try to record the session, and the prototype starts to collapse. Each of those changes forces you to add infrastructure or engineering the prototype never needed.

The gap between 'a call that works in a demo' and 'a call that works reliably for 1,000 users across different devices and networks' is where the real cost lives.

Where the cost actually accumulates: the production stack

Signalling server

WebRTC handles the media itself, but it does not handle the coordination step that precedes media: telling two clients how to find each other, exchanging session descriptions (SDP), and relaying ICE candidates. That is the signalling layer, and you have to build and operate it yourself.

A signalling server is not especially complex in its first form: a WebSocket server that relays messages between peers. But it needs to be hosted, secured with TLS, monitored, and scaled. Under load, it needs horizontal scaling with sticky sessions or a shared session store. When you add rooms, authentication, and webhook events, it becomes a meaningful service in its own right. The engineering effort here runs to days at the low end and weeks once you factor in hardening and operational tooling.

STUN and TURN infrastructure

When two browsers try to connect peer-to-peer, they use ICE, which is a process that tries several candidate paths in order of preference. A STUN server helps each client discover its public IP address, which is usually enough for users on home networks. But a substantial proportion of real-world users sit behind symmetric NATs, corporate firewalls, or VPNs where direct peer-to-peer is blocked. For those users, traffic must be relayed through a TURN server.

TURN relay is bandwidth-heavy. Every packet of video and audio passes through your TURN infrastructure, which means egress costs scale directly with usage. Estimating TURN consumption before you have production traffic is difficult, because TURN utilisation rates vary widely depending on your user demographics, but it is not a cost you can ignore in your total cost of ownership (TCO) calculation. Operating TURN at scale also requires geographic distribution: a TURN server on the wrong continent adds hundreds of milliseconds of latency and degrades call quality noticeably.

Media server / SFU

Peer-to-peer only works cleanly at very small participant counts. Beyond two or three participants, the mesh topology, where every participant sends a stream to every other participant, becomes impractical. Each participant uploads a copy of its own stream to every other participant, so per-client upload grows linearly with the participant count, while the total number of streams across the mesh grows with the square of that number. The standard solution is a Selective Forwarding Unit (SFU): a media server that receives streams from each participant and forwards the appropriate streams to each receiver, without decoding or re-encoding.

Building and operating an SFU is by far the largest single cost driver in scaling WebRTC. Open-source options exist, such as Janus, Mediasoup, and Pion, but open source means the code is free, not that the implementation effort is free. Deploying an SFU correctly, tuning it for simulcast (where senders transmit multiple resolution layers simultaneously so the SFU can adapt to each receiver's conditions), and scaling it horizontally under variable load add up to a serious infrastructure engineering project. Teams routinely underestimate this as a matter of weeks when it is really a matter of months, particularly once it is coupled with observability, failover, and geographic distribution.

Recording and storage

Server-side recording, meaning capturing a composed view of a multi-party call, requires the SFU or a separate recording node to mix audio and video streams and write them to a file. This is computationally expensive: compositing video in real time, even without re-encoding, consumes meaningful CPU resources. The recorded files then need to be stored, typically in object storage, and eventually streamed to users or exported, both of which carry egress costs. For products where recording is a core feature rather than an edge case, the infrastructure costs here warrant their own line item.

Cross-browser and device QA

WebRTC behaviour varies across browsers in ways that are not always documented and that change with each browser release. Safari has historically lagged on WebRTC feature support and continues to diverge from Chrome on certain codec and API behaviours. Mobile Safari on iOS imposes additional constraints (for example, getUserMedia behaviour, screen-sharing limitations, and background-tab handling) that require separate test paths. Firefox has different codec defaults. Older Android WebViews on mid-range devices present their own failure modes.

The result is that cross-browser and device QA is not a one-time investment. It is ongoing. Every time Chrome ships a new version, regression testing is warranted, and that cadence is speeding up: Chrome moves from a four-week to a two-week major release cycle on 8 September 2026, which roughly doubles the number of release checkpoints you have to keep pace with. This is engineering time that does not go towards building new features. Over a 12-month period, this adds up to a substantial number of hours.

Security and encryption

WebRTC encrypts media with DTLS-SRTP by default, which covers transport security. But production systems require more than the baseline. Key management for session establishment needs to be handled correctly. If your use case involves sensitive content, such as healthcare consultations, legal discussions, or financial advice, you may need to evaluate end-to-end encryption (E2EE), which rules out certain server-side capabilities like recording and requires careful protocol design. Signalling must be secured separately. Authentication tokens must be scoped and validated. None of this is prohibitively difficult, but each element represents engineering time and ongoing responsibility.

Compliance

If you serve users in the EU or process data about EU residents, GDPR applies. That means data processing agreements with every sub-processor (your cloud provider, your CDN, your monitoring tool, your TURN infrastructure provider), data residency decisions, and the ability to honour deletion and portability requests. Telehealth products in the US must contend with HIPAA. EdTech products serving children under 13 in the US encounter COPPA. Compliance work is typically invisible in early engineering estimates and very visible in legal bills and delayed launches.

Reliability and observability

You cannot run a production video system without observability. You need call-quality metrics, such as packet loss, jitter, round-trip time, and bitrate, surfaced in a way that lets you diagnose user-reported issues. You need alerting when SFU nodes become unhealthy. You need on-call coverage, because video calls fail at inconvenient hours. Building a quality of experience (QoE) monitoring layer from scratch is a multi-week engineering project, and the on-call burden it creates is ongoing.

Ongoing maintenance

The cost that most build estimates omit entirely is maintenance. The WebRTC specification keeps evolving, browser implementations change, and the IETF continues to refine related standards. Security patches appear, and your SFU library releases its own breaking changes from time to time. Each of these requires engineering attention: sometimes a few hours, sometimes a few days, occasionally a crisis that needs an urgent response. Over a horizon of two to three years, maintenance easily consumes the equivalent of another full implementation cycle.

The hidden costs teams forget

Beyond the direct infrastructure and engineering components above, four hidden costs consistently surprise teams that choose to build.

• Engineer opportunity cost is the most significant. Every engineering week spent on TURN infrastructure, SFU tuning, or cross-browser regression is a week not spent on the features that differentiate your product. For a SaaS startup or an EdTech company, the real cost of building WebRTC isn't the WebRTC work itself. It's everything else that didn't get built instead.
• Time-to-market delay compounds the opportunity cost. If your competitive window is six months, a video feature that takes nine months to reach production quality is not a cost saving, but a strategic risk. The total cost of ownership (TCO) of a build decision includes the revenue implications of a delayed launch.
• Key-person risk is underappreciated in smaller teams. WebRTC expertise is genuinely specialist knowledge. If the engineer who designed and understands your media infrastructure leaves, the institutional knowledge is difficult to replace quickly.
• Scaling surprises are costs that only appear under load. TURN egress that seemed modest at 100 concurrent users becomes a significant line item at 10,000. SFU nodes that handled 50 rooms start to show stress at 500. These costs are hard to predict in advance, but they can be planned for and factored into the build decision.

Build vs embed: the break-even

The correct axis for this decision is not 'build' versus 'buy a SaaS product'. It is build vs embed video: run the entire stack yourself versus embed a programmable service that handles the infrastructure while exposing the interfaces you need to customise the product.

A simple decision model

Building the stack yourself is the rational choice when real-time communication is core intellectual property, that is, when the media pipeline itself is the product, when you need capabilities that no existing service exposes, or when your scale and team size mean that operating infrastructure is genuinely cost-efficient relative to service fees. It also makes sense when you have in-house RTC expertise and the ongoing maintenance burden is already accounted for in headcount.

Embedding wins in the much more common case: when video is a feature of your product rather than the product itself, when time-to-market matters, when your team's expertise is in your domain rather than in media infrastructure, and when you would rather see your costs up front than discover them in arrears. One clarification on 'predictable' cost: usage-based fees on the embed side still scale with growth, much like infrastructure costs do when you build it yourself. The real advantage of embedding isn't that the bill is fixed. It's that the cost is visible up front and the operational burden sits with the vendor rather than your team.

A useful TCO framing: estimate the engineering weeks required to reach production quality (signalling, TURN, SFU, recording, QA, security, compliance, and observability), then express that as a percentage of your total engineering roadmap for the next 12 months. For most product teams, that number is uncomfortably high. The scale at which self-hosting starts to pay off tends to arrive earlier than you might expect, at a moderate level of usage rather than only at the size of the largest platforms, though it still takes real volume before the economics tip in favour of building.

What do you stop paying for when you embed

The cost components mapped out above line up closely with what a well-designed embedded SDK takes off your plate.

SFU scaling, TURN relay, and the geographic distribution of media infrastructure become the vendor's problem. Cross-browser and device QA, the ongoing regression work that every browser release requires, is absorbed into the service. Even the compliance groundwork, EU data residency and sub-processor management, moves largely to the infrastructure layer, though you remain the data controller for the personal data in your calls.

That division of labour is what we've built Digital Samba around. The infrastructure is EU-hosted, and our data processing agreement is deliberately lean: for most teams it can be signed as-is to cover data residency and sub-processor management, so meeting strict data-sovereignty, privacy, and security requirements does not turn into a drawn-out DPA negotiation.

On the engineering side, the Digital Samba embedded SDK is distributed under the BSD-2-Clause licence, so you can inspect and extend the SDK code freely, and it stays fully programmable rather than boxing you into a fixed UI. The SFU layer is built on Janus, an established, well-documented open-source media server, and end-to-end encryption is available as an option for use cases where no server, including ours, can read the media.

In practice, the components that create the highest ongoing burden in a self-hosted stack, SFU operations, TURN egress, browser compatibility, compliance infrastructure, and perpetual maintenance, are handled for you, and you keep full control over the integrations and customisations your product needs.

Embedding isn't free of trade-offs either, and it's fair to weigh them alongside the hidden costs of building described above. You take on a dependency on the vendor's roadmap and pricing decisions. Most contracts involve a commitment period rather than pure pay-as-you-go flexibility. And if you ever need to switch providers, migrating a live product to a new video stack carries a real cost of its own.

Conclusion

There is no single number for how much it costs to build a WebRTC app, but the components that drive the real cost are well-defined, and none of them are optional once you are building for production. The prototype is cheap. The signalling, TURN, SFU, recording, QA, security, compliance, observability, and maintenance layers are not cheap, and they do not stop costing once they are built.

The right way to frame the decision isn't the prototype estimate. It's the full total cost of ownership: ongoing maintenance, engineer opportunity cost, and everything else covered above. For most product teams, that analysis points clearly towards the embed path, particularly when the embedded option is EU-hosted and built on an established open-source foundation, with the trade-offs named honestly rather than glossed over.

If you're ready to look at the embed option in concrete terms, Digital Samba's pricing page is a good place to start. And if you're still working through the build vs embed decision in detail, our build vs embed guide covers the trade-offs in more depth.

The cost of building is not the demo. It is everything that comes after.

Frequently asked questions

How much does it cost to build a WebRTC video conferencing app?

There is no single number, because the cost depends on the scale you need to support, the features you require, the team's existing expertise, and the geographic distribution of your infrastructure. A prototype can be built in days for near zero infrastructure cost. A production system, with an SFU, TURN relay, recording, cross-browser QA, observability, and compliance, typically requires three to nine months of specialist engineering effort and ongoing operational expenditure. The more useful question is: what percentage of your engineering roadmap are you prepared to dedicate to media infrastructure over the next two years?

Why is a WebRTC prototype cheap but a production app expensive?

A prototype typically demonstrates a two-party call over a favourable network using the browser's built-in WebRTC APIs. No media infrastructure is required for that use case. Production adds multi-party support (which requires an SFU), reliable connectivity for users on restricted networks (which requires TURN), cross-browser compatibility (which requires ongoing QA), recording, security hardening, compliance, and observability. Each of those adds engineering effort and infrastructure cost that the prototype never touched.

What are the ongoing maintenance costs of running WebRTC yourself?

Ongoing maintenance includes browser compatibility regression testing (Chrome moves to a two-week major release cycle on 8 September 2026, up from four weeks), SFU and dependency updates, security patches, monitoring and on-call coverage, and periodic re-architecture as your scale changes. Engineering teams that build their own stacks consistently report that maintenance consumes a meaningful fraction of the original build effort each year, often in the range of 20 to 40 per cent annually when amortised over time.

Do I need a TURN server and an SFU, and what do they cost to run?

Yes, in most production cases you need both. TURN is required for users on restricted networks, typically 15 to 40 per cent of real-world traffic depending on your user demographics, and its cost scales with egress bandwidth, which in turn depends on usage. An SFU is required for multi-party calls beyond two or three participants. SFU costs include compute, egress, and the engineering overhead of operating the service. Both need geographic distribution for acceptable latency, which multiplies infrastructure costs. Exact figures depend on your traffic patterns. The Digital Samba pricing page gives a sense of what the embed alternative looks like by comparison.

When does it make sense to build vs embed video?

It comes down to what real-time video means for your business. If it's genuinely core to your product, if you need capabilities no existing service offers, or if you already have in-house RTC expertise and the team to support it long-term, building can make sense. For most teams, though, video supports a different product rather than being the product itself, and time-to-market and predictable, visible costs matter more than owning every layer of the stack. In that case, embedding usually wins.

What costs go away if I use an embedded video SDK?

With a well-designed embedded SDK, you eliminate or substantially reduce: SFU build and operations, TURN infrastructure and egress, cross-browser and device QA, compliance infrastructure (GDPR data residency, sub-processor management), WebRTC maintenance as the specification and browsers evolve, and observability build. You keep full control over the product experience and the application logic: you are embedding infrastructure, not surrendering programmability.

References

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3. Internet Engineering Task Force. (2018). Interactive Connectivity Establishment (ICE): A protocol for network address translator (NAT) traversal, RFC 8445. IETF.
4. Janus WebRTC Server. (2024). Janus: A general purpose WebRTC server. Meetecho.
5. Loreto, S., & Romano, S. P. (2012). Real-time communications in the web: Issues, achievements, and ongoing standardization efforts. IEEE Internet Computing, 16(5), 68-73.
6. Mozilla Developer Network. (2024). WebRTC API. MDN Web Docs.
7. Rescorla, E. (2018). The Transport Layer Security (TLS) protocol version 1.3, RFC 8446. IETF.
8. Uberti, J., & Jennings, C. (2021). JavaScript session establishment protocol (JSEP), RFC 8829. IETF.
9. W3C & IETF. (2021). WebRTC: Real-time communication between browsers. World Wide Web Consortium.