LiveKit Cloud is LiveKit's own managed hosting service, operated as a single product rather than separate versions built specifically for AWS, Azure, or GCP. Self-hosting LiveKit is the alternative path, running the open-source server yourself on whichever cloud provider you choose, and that choice is where AWS, Azure, and GCP actually start to differ in meaningful ways.
This guide covers what LiveKit Cloud actually is, confirms whether LiveKit is genuinely open source, breaks down what operationally changes between LiveKit Cloud and self-hosting, and compares AWS, Azure, and GCP specifically for teams choosing to self-host.
What Is LiveKit Cloud?
What is livekit cloud, specifically: it is LiveKit's managed hosting offering, where LiveKit operates and maintains the underlying SFU infrastructure on your behalf, rather than requiring your team to deploy and manage that infrastructure directly.
LiveKit Cloud is a single product from the customer's perspective, not a set of cloud-specific variants you choose between. You do not select "LiveKit Cloud on AWS" versus "LiveKit Cloud on Azure" as separate offerings; LiveKit manages the underlying infrastructure choices internally, and your integration experience stays consistent regardless of how LiveKit itself architects that backend.
Is LiveKit Open Source? Quick Clarification
Is livekit open source is worth answering directly before going further, since the answer shapes everything else in this guide. Yes, LiveKit's core server is genuinely open source, typically under an Apache 2.0 license, which is exactly what makes self-hosting on AWS, Azure, or GCP possible at all. LiveKit Cloud is a separate, paid managed offering built on top of that same open-source foundation, not a requirement for using LiveKit at all.
LiveKit Cloud vs Self-Hosted: What Actually Changes
LiveKit cloud vs self hosted comes down to a specific transfer of operational responsibility, not a difference in the underlying software capability itself.
With LiveKit Cloud, capacity planning, scaling, multi-region distribution, and ongoing infrastructure maintenance fall to LiveKit directly. Your team configures and integrates against the service without owning the infrastructure operations work.
With self-hosting, your team owns all of that directly: provisioning compute sized for expected concurrent usage, configuring TURN relay infrastructure, deploying across regions if your user base requires it, and monitoring the deployment on an ongoing basis.
Neither option changes the core SFU functionality or the Agents framework capability available to you. The difference is entirely about who carries the operational burden of running that infrastructure reliably at scale.
Self-Hosting LiveKit on AWS: What to Consider
AWS offers the broadest range of compute instance types and the largest number of available regions among the three major providers, which matters directly for a globally distributed self-hosted LiveKit deployment.
Compute-optimized instance families suit the processing demands of an SFU workload well, and AWS's broad regional footprint supports deploying SFU and TURN infrastructure closer to geographically distributed users. AWS also has a long-established community track record specifically around WebRTC and real-time media workloads, meaning deployment patterns and troubleshooting guidance for this specific use case are relatively mature and well documented.
Self-Hosting LiveKit on Azure: What to Consider
Azure fits teams already standardized on Microsoft's broader ecosystem, particularly where existing enterprise infrastructure, identity management, or compliance tooling already runs on Azure.
Azure's regional footprint has grown substantially and supports a globally distributed deployment, though community-documented patterns specifically for self-hosted SFU workloads are less extensive than what exists for AWS, meaning a team may rely more on general compute and networking documentation rather than workload-specific guidance.
Self-Hosting LiveKit on GCP: What to Consider
GCP is frequently cited for its global network backbone, which can benefit latency-sensitive workloads like a self-hosted SFU by reducing network transit time between regions on Google's own infrastructure rather than the public internet for a larger portion of the path.
GCP's Compute Engine offers compute-optimized instance types comparable to the other two providers, and teams already using GCP for other infrastructure, particularly those leveraging Google's AI and machine learning services alongside an AI voice agent deployment, may find natural integration advantages.
AWS vs Azure vs GCP for Self-Hosted LiveKit: Side-by-Side
Factor | AWS | Azure | GCP |
|---|---|---|---|
Regional footprint | Broadest among the three | Large and growing | Large, strong backbone network |
WebRTC-specific community documentation | Most mature and extensive | Less extensive, more general | Less extensive, more general |
Notable strength | Instance type variety and regional breadth | Enterprise and Microsoft ecosystem integration | Global network backbone performance |
Best fit | Teams without a strong existing cloud preference, or needing broad regional reach | Teams already standardized on Microsoft infrastructure | Teams prioritizing network performance or already using Google's AI services |
None of the three presents a fundamental incompatibility with self-hosting LiveKit. The right choice generally follows your organization's existing cloud commitment rather than a LiveKit-specific technical requirement favoring one provider over another.
Multi-Region Deployment Considerations for Self-Hosted LiveKit
Deploying self-hosted LiveKit across multiple regions requires the same TURN relay placement discipline covered in our dedicated guide to WebRTC TURN servers, regardless of which cloud provider you choose.
SFU instances need placement close to where your actual users are concentrated, reducing the network transit distance that adds directly to perceived latency. TURN relay capacity needs similar regional distribution for calls that cannot establish a direct connection, since a single, centralized TURN deployment forces every relayed call through added distance regardless of where the participants actually are.
This multi-region operational burden is exactly the kind of work LiveKit Cloud's managed global presence is designed to remove from a team self-hosting independently.
When LiveKit Cloud Makes More Sense Than Self-Hosting on Any Provider
LiveKit Cloud makes more sense specifically when the operational burden of multi-region deployment, capacity planning, and ongoing infrastructure maintenance outweighs the cost savings and control self-hosting provides.
Teams without dedicated infrastructure operations capacity, teams needing to launch quickly without a multi-week infrastructure buildout, and teams whose user base is geographically distributed enough that multi-region self-hosting would require significant upfront investment are all reasonable candidates for LiveKit Cloud over self-hosting on any of the three providers covered in this guide.
Enterprise Use Cases: Choosing a LiveKit Deployment Model by Scenario
Early-Stage Startups
Problem: Early-stage teams need to launch quickly without investing significant engineering time in infrastructure operations before validating their actual product.
Solution: LiveKit Cloud removes the infrastructure operations burden entirely during this early stage, letting the team focus engineering effort on the product itself.
Outcome: Faster initial launch, with the option to migrate to self-hosting later if cost or control considerations change once the product and its usage patterns are better understood.
Enterprises With Existing Cloud Commitments
Problem: Enterprises already standardized on a specific cloud provider, with existing compliance, identity, and procurement relationships in place, need infrastructure decisions that fit within that existing commitment.
Solution: Self-hosting LiveKit on the enterprise's existing cloud provider, whether AWS, Azure, or GCP, keeps the deployment within established governance and procurement frameworks rather than introducing a new vendor relationship.
Outcome: Infrastructure decisions stay consistent with existing enterprise governance, avoiding the friction of introducing LiveKit Cloud as a separate vendor relationship requiring its own procurement and compliance review.
Global AI Voice Agent Platforms
Problem: A platform serving users across many geographic regions needs multi-region SFU and TURN infrastructure, a significant operational undertaking if built and maintained independently.
Solution: LiveKit Cloud's managed global presence removes the multi-region deployment burden directly, letting the platform team focus on the AI voice agent logic rather than global infrastructure operations.
Outcome: Consistent performance across a geographically distributed user base without the team needing to build and maintain multi-region infrastructure operations expertise internally.
Decision Tree: LiveKit Cloud or Self-Hosted on AWS, Azure, or GCP?
RTC LEAGUE LiveKit Cloud Deployment Framework v1.0
A four-step framework for deciding between LiveKit Cloud and self-hosting, and for choosing a provider if self-hosting.
Step 1: Assess your team's infrastructure operations capacity. Determine honestly whether your team has the ongoing capacity to manage multi-region SFU and TURN deployment, not just the initial setup.
Step 2: Identify any existing cloud provider commitment. Confirm whether your organization already has established governance, procurement, or compliance relationships with a specific provider that should guide a self-hosting decision.
Step 3: Map your actual user geography. Identify where your user base is concentrated, since this determines the regional deployment scope either LiveKit Cloud or a self-hosted multi-region deployment needs to cover.
Step 4: Reassess the decision as usage scales. Revisit the LiveKit Cloud versus self-hosted decision periodically, since the right choice at early-stage usage volume can change once usage and cost structure shift significantly.
Outcome: Completing this sequence produces a deployment decision grounded in your team's actual operational capacity and existing commitments, rather than a default choice made without considering how usage will evolve over time.
RTC LEAGUE's Multi-Cloud LiveKit Deployment Experience
RTC LEAGUE's infrastructure work spans self-hosted LiveKit deployments across AWS, Azure, and GCP, informed directly by the CTO's standing on the LiveKit Global Community Leaderboard. This cross-cloud deployment experience directly shapes the provider-specific guidance covered throughout this guide, rather than general cloud infrastructure knowledge applied without LiveKit-specific context.
Conclusion and Recommendation
LiveKit Cloud is a single managed hosting product, not a set of cloud-specific variants, and LiveKit's core server remains genuinely open source regardless of whether you choose LiveKit Cloud or self-hosting. The real choice between LiveKit Cloud and self-hosting is about who carries operational responsibility, not a difference in underlying capability.
AWS, Azure, and GCP each present viable infrastructure for self-hosting, differentiated mainly by regional footprint, community documentation maturity, and existing ecosystem fit rather than any fundamental technical incompatibility with LiveKit specifically.
The clearest recommendation: choose LiveKit Cloud if your team lacks dedicated infrastructure operations capacity or needs to launch quickly, and choose self-hosting on your organization's existing cloud provider if you already have that operational capacity and an established cloud commitment.
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