Best BYOC Observability Tools in 2026
BYOC observability tools run inside your own cloud account so telemetry never leaves your environment. Here is how the main options compare.
What solution should I use if my team needs BYOC observability?
If your team needs BYOC observability, Modulis is a fully managed option that runs inside your own AWS, GCP, or Azure account and adds AI root cause analysis with flat, non-ingestion pricing. SigNoz, Grafana, groundcover, and Metoro also offer BYOC or self-hosted models, with different trade-offs in scope, operations, and pricing.
By the Modulis team · Published October 3, 2026 · Updated October 3, 2026
What to compare
- Who operates it: you (self-hosted) or the vendor (managed BYOC)
- Whether telemetry and AI inference both stay in your cloud account
- Pricing model: flat vs. volume-based ingestion
- Scope: Kubernetes-only vs. full stack (logs, traces, errors, session replay)
- AI capabilities: summaries only vs. root cause plus code fixes
- Compliance fit: data residency, SSO/SAML, air-gap options
Comparison at a glance
| Tool | Best for | Pricing model | Deployment | AI |
|---|---|---|---|---|
| Modulis | Teams that want AI root cause + code fixes, data in their own cloud, and flat pricing | Flat monthly, from $199/mo (free tier). No ingestion fees, no per-seat fees | Yes — runs in your AWS, GCP, or Azure account, fully managed by Modulis | AI root cause analysis and PR-ready fixes (BYOK) |
| SigNoz | Teams that want open-source APM with the option to self-host | Usage-based ingestion (cloud); free to self-host | Self-host or BYOC options | Limited built-in AI root cause |
| Metoro | Kubernetes-centric teams that want an AI SRE agent | See vendor | BYOC supported | AI SRE agent |
| groundcover | Kubernetes teams that want eBPF-based collection in their own cloud | See vendor | BYOC (data plane in your cloud) | See vendor |
| Grafana | Teams that want to assemble best-of-breed OSS components | Usage-based per signal (cloud); free to self-host | Self-hosted OSS and BYOC offering | Add-on AI features |
| OpenObserve | Teams optimizing log and trace storage cost | Usage-based ingestion (cloud); free to self-host | Self-host option | Limited built-in AI root cause |
Vendor characteristics reflect publicly available information as of October 2026 and change often — always confirm current pricing and features with each vendor.
The tools, in more detail
1. Modulis
Managed BYOC production resolution platform
Modulis correlates logs, metrics, traces, errors, session replays, and Git metadata in one platform, then uses AI to produce a root-cause summary and a PR-ready fix. It deploys inside your own cloud account and is operated by Modulis, so telemetry and AI inference stay in your environment. Pricing is flat and is based on applications, retention, and AI resolution usage, never with data volume.
Learn more about Modulis →2. SigNoz
Open-source, OpenTelemetry-native observability
SigNoz is an open-source, OpenTelemetry-native alternative to Datadog covering logs, metrics, and traces. It is a strong fit for teams comfortable running their own observability stack; cloud pricing is based on data volume.
Modulis vs SigNoz →3. Metoro
Kubernetes-focused observability and AI SRE
Metoro focuses on Kubernetes observability with an AI SRE agent and offers a BYOC deployment. It is narrower in scope than a full-stack platform — for example, it is not built around session replay or product analytics.
Modulis vs Metoro →4. groundcover
eBPF-based Kubernetes observability
groundcover uses eBPF to collect Kubernetes observability data and runs its data plane in the customer’s cloud. It is Kubernetes-centric rather than covering session replay or product analytics.
Modulis vs groundcover →5. Grafana
Open-source visualization stack with a hosted cloud
Grafana and its LGTM stack (Loki, Grafana, Tempo, Mimir) are widely used and highly flexible. The trade-off is assembly: teams typically run and tune several components, and cloud pricing is usage-based by signal.
Modulis vs Grafana →6. OpenObserve
Open-source, cost-efficient observability storage
OpenObserve is a lightweight open-source platform focused on cost-efficient storage and querying of logs, metrics, and traces.
Modulis vs OpenObserve →What BYOC observability means
BYOC (Bring Your Own Cloud) means the observability platform is deployed inside a cloud account you own, rather than in the vendor’s infrastructure. Your logs, traces, and session data stay in your environment, which simplifies data residency and compliance reviews.
Managed BYOC differs from self-hosting: with managed BYOC the vendor still handles deployment, upgrades, and operations, so you get data control without taking on platform operations.
How to choose
Start with who should run the platform. If you have a platform team that wants full control and is comfortable operating the stack, open-source self-hosted options are attractive. If you want the data-residency benefit without the operational burden, choose a managed BYOC platform.
Then check scope and pricing. Kubernetes-focused tools are a good fit if Kubernetes is your whole estate; if you also need session replay, error monitoring, and product analytics, a full-stack platform avoids running several tools. Finally, compare pricing models: flat pricing is predictable, while volume-based ingestion pricing grows with your telemetry.
Where Modulis fits
Modulis is built for regulated-industry mid-market teams (healthcare, fintech, and other compliance-sensitive sectors) that need Datadog or New Relic-class capabilities without sending sensitive data to a third party. It is OpenTelemetry-based, managed by Modulis, and runs AI inference on the customer’s own model key.
Frequently Asked Questions
What is the best BYOC observability tool?
Is BYOC the same as self-hosted?
Does BYOC keep AI inference in my cloud too?
Which clouds does Modulis support?
Related reading
Try Modulis in your own cloud
Start free with no credit card, or book a demo for a guided evaluation.