What Is BYOC Observability?

The three deployment models

Observability and monitoring tools are generally deployed one of three ways:

Why data residency matters here

Observability and debugging tools see a lot of sensitive information by nature — logs can contain user data, traces reveal internal system architecture, and session replay can capture exactly what a user did on screen. For regulated industries (healthcare, fintech, and other compliance-sensitive sectors), routing that data through a third-party SaaS vendor's infrastructure is often a genuine compliance obstacle, not just a preference.

BYOC vs. SaaS: what actually changes

With BYOC, telemetry data never leaves your cloud account, so you retain data sovereignty without taking on the operational burden of running the platform yourself — deployment, upgrades, and monitoring remain the vendor's responsibility. The trade-off versus SaaS is usually setup time (deploying into your own account takes longer than signing up for a hosted tool) in exchange for that data control.

BYOC vs. self-hosted: what actually changes

Compared to self-hosting, BYOC keeps the same data-residency benefit while removing the operational burden — you're not the one patching, scaling, or being paged when the platform itself has a problem. The trade-off is less direct control over the software's internals than a fully self-hosted, open-source deployment would give you.

How Modulis implements BYOC

Modulis is a production resolution platform — correlating logs, traces, errors, session data, and Git metadata with AI-assisted root cause analysis — deployed inside your own AWS, GCP, or Azure account and fully managed by the Modulis team. Where AI-assisted resolution is used, it can also run on your own model key (BYOK), so inference stays inside the same cloud boundary as the rest of your data.

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