Most teams start with a managed RTC or IM service because it is fast. The question is not whether a public cloud is good — it usually is — but whether its delivery model still fits as data requirements, usage volume and integration needs grow.
This article offers a comparison method rather than a verdict. It is written from the perspective of a team that has to defend the decision to engineering, finance and security.
Two delivery models, not two products
The meaningful comparison is between delivery models:
- Managed service: the provider runs the infrastructure, you consume APIs and usage-based capacity. You gain speed, elasticity and a mature global footprint.
- Private deployment: you run SDK-based software in your own environment. You gain data control, customisation and a different cost structure, and you take on operations.
Feature lists differ between vendors within each model, so compare models first, then shortlist vendors inside the chosen model.
Cost lines that are easy to miss
Usage-based pricing is visible. The rest is often invisible until year two.
| Cost line | Managed service | Private deployment |
|---|---|---|
| Compute and network | Bundled into usage pricing | Infrastructure, bandwidth, reserved capacity |
| Storage and retention | Metered storage, egress charges | Storage hardware or cloud storage you own |
| Engineering | Integration and configuration | Integration, deployment, upgrades, on-call |
| Operations | Included, with vendor support tiers | Monitoring, capacity planning, patch management |
| Compliance and audit | Provider attestations, shared responsibility | Your controls, your evidence |
| Switching costs | API/data migration, re-integration | Migration to another platform or exit |
Two further lines deserve attention:
- Engineering time is a real cost. A private deployment is not a one-off installation; it is a system that needs an owner.
- Elasticity has value. Over-provisioning for peak load is a cost even when the hardware is idle.
A simple TCO model
For a defined horizon of N months:
- Estimate peak and average concurrency, plus storage growth.
- Price the managed service over N months, including support and egress.
- Price infrastructure for the private option: compute, storage, bandwidth, licences, and a realistic staffing allocation.
- Add integration effort for both.
- Add a migration or exit allowance for both.
The output is rarely a single number that wins by an order of magnitude. More often the models cross: managed services are cheaper at low and volatile volume; private deployment becomes competitive when usage is steady, large and long-lived — and when a compliance requirement already forces a private footprint.
Use explicit assumptions and sensitivity ranges. A comparison with one point estimate invites arguments instead of decisions.
Data sovereignty: requirement or preference?
“Sovereignty” is often used loosely. Make it concrete by answering:
- Which data classes must stay in which jurisdiction or network? Meeting media, message content, metadata, backups, logs — each may have a different answer.
- Who must be able to access the data, under whose authorisation?
- What must be provable to an auditor, and in what format?
- What happens during support: can a vendor engineer access data, and how is that access logged?
A managed service can meet many requirements through regional hosting and contractual commitments. Private deployment is the stronger option when the requirement is absolute: the data cannot be placed on infrastructure the organisation does not control, or cannot traverse the public internet at all.
Shared responsibility in practice
With a managed service, the provider secures the platform and you secure configuration, identity and data usage. With private deployment, almost everything is yours. That shift changes the operating model:
- Who receives security advisories, and who applies patches?
- Who owns incident response for a media or message outage?
- How are backups tested, and who restores them?
- What evidence can you produce during an audit?
If those answers do not exist yet, the private option is not cheaper — it is unfinished.
Decision framework
Consider private deployment when most of the following hold:
- Data placement is a hard requirement, not a preference.
- Usage is stable and large enough that self-hosted unit economics are attractive.
- You need to customise message models, signalling or permission logic.
- You have infrastructure and operations capability, or a partner who does.
- The system is strategic enough to justify owning its lifecycle.
Consider a managed service when most of the following hold:
- You need to validate a product quickly.
- Volume is small or highly volatile.
- You have no appetite for running media or messaging infrastructure.
- Global access and vendor-operated reliability are priorities.
- Data can be hosted under acceptable contractual and regional terms.
Contract and exit considerations
Whichever model you choose, negotiate the exit before you need it:
- Data export formats and timelines.
- Notice periods and support during migration.
- Licence transfer or source escrow arrangements, where offered.
- For managed services: egress pricing and data deletion confirmation.
Conclusion
Public-cloud RTC and IM are often the right first choice. The mistake is treating that choice as permanent without revisiting it when requirements change. A short, explicit TCO and sovereignty assessment — updated annually — is more useful than a one-off debate.
FeiyanCloud builds privately deployable SDKs, so we have a bias. We still recommend running this comparison honestly; if a managed service fits your constraints better, that is the correct answer.
Capabilities marked Coming soon or Roadmap are not available in the current release. Product capabilities and availability are governed by the official release notes.