can i use gromitor alongside Prometheus without conflict?

yes. gromitor and Prometheus both read metrics from the Docker API / kubelet — they don't interfere with each other. some teams use gromitor for quick operational visibility and Prometheus for long-term retention and custom instrumentation.

does gromitor support custom metrics from my application?

not currently. gromitor focuses on host-level container resource metrics (cpu, memory, network i/o, disk i/o). for application-level custom metrics (business KPIs, request rates, error rates) you'd still want Prometheus with a client library or a product like Datadog.

how does gromitor handle security? i'm worried about forwarding metrics to a third party.

the agent collects only resource utilization metrics — container names, cpu percentages, memory bytes, i/o counters. it does not collect application data, environment variables, or logs. data in transit uses TLS. for teams with strict data residency requirements, the open-source stack is a better fit.

what's the migration path if i want to move back to self-hosted tools?

removing gromitor is a one-line docker command (or kubectl delete for kubernetes). your historical data in gromitor's backend is exportable. there's no lock-in at the infrastructure level — the agent is stateless and disposable.

agent-based container monitoring vs. manual open-source tools

comparison9 june 2026· 7 min read

agent-based SaaS monitoring and self-hosted open-source tools both give you container metrics, but the trade-offs are fundamentally different. open-source tools like Prometheus, Grafana, and cadvisor are flexible and free in license cost, but you own the deployment, operation, storage, and upgrades. an agent-based SaaS like gromitor adds under 2% host cpu, works in minutes, and shifts the operational burden to the vendor — at the cost of some configurability and a subscription.

what open-source container monitoring actually involves

the canonical open-source stack for container monitoring is cadvisor (scraping docker and kubernetes metrics) → Prometheus (scraping cadvisor and storing time-series data) → Grafana (visualizing Prometheus data) → alertmanager (routing alerts). each component has its own deployment, configuration, upgrade path, and failure mode.

an engineer on hacker news captured it well: "there are open source tools like heapster which have to be manually deployed." heapster is deprecated now, but the observation holds for its successors. cadvisor, Prometheus, and Grafana all have to be manually deployed, configured, and operated. when Prometheus runs out of disk space at 2am, that's your problem. when a Grafana upgrade changes the dashboard json schema, that's your problem too.

this isn't a criticism of those tools — they're excellent and widely used for good reason. the point is that using them has a real operational cost that teams often underestimate at adoption time.

the agent-based SaaS model

gromitor's approach is to run a single lightweight agent on each host (or as a DaemonSet in kubernetes). the agent reads container metrics from the Docker stats API or kubelet summary API and forwards them to gromitor's managed backend. you don't deploy Prometheus. you don't configure scrape intervals. you don't size persistent volumes. you don't design Grafana dashboards.

the gromitor dashboard is pre-built for container monitoring — per-container cpu, memory, network i/o, and disk i/o are immediately available after the agent starts. alerting is configured through the UI: pick a container, set a threshold, choose a delivery channel.

direct comparison: key dimensions

the choice comes down to a few concrete trade-offs:

setup time: open-source takes days to get production-ready; gromitor takes under 10 minutes
ongoing ops: open-source requires storage management, upgrades, and debugging; gromitor pushes that to the vendor
cost: open-source is free to license but not free to operate (engineering time, cloud storage, compute); gromitor has a subscription cost
flexibility: open-source is highly customizable — you can instrument anything, store anything, graph anything; gromitor covers the core container metrics use case but isn't a general-purpose observability platform
data ownership: with open-source your metrics never leave your infrastructure; with gromitor metrics are forwarded to gromitor's backend (important for compliance-sensitive environments)
multi-platform: gromitor shows docker and kubernetes in one view; open-source requires you to federate multiple prometheus instances yourself

when open-source is the right call

if you have a dedicated platform team, strong prometheus expertise, and compliance requirements that mandate data stays within your own infrastructure, the open-source stack is probably the right choice. you get maximum flexibility, deep integration with your existing observability tooling (jaeger, tempo, loki), and no vendor dependency.

if you're building a multi-tenant product and want to expose per-customer observability, or if you need to retain metrics for years for compliance audits, you'll want to operate your own store.

when agent-based SaaS wins

for teams that want visibility without operational overhead — developers who own their own infrastructure, small devops teams, startups scaling fast — gromitor delivers the core value (live per-container metrics plus alerting) without the setup tax. you can be monitoring in production in the time it takes to read this article.

the agent's read-only, sub-2% cpu footprint means you're not trading one operational concern for another. and because gromitor is built in public by a focused indie studio (ogbuilds), the product is squarely aimed at the container monitoring use case rather than being a feature in a larger observability platform.

see this on your own containers

gromitor gives you real-time docker + kubernetes monitoring from one lightweight agent — no open-source tools to deploy.

get started, it's free how gromitor works

faq

can i use gromitor alongside Prometheus without conflict?: yes. gromitor and Prometheus both read metrics from the Docker API / kubelet — they don't interfere with each other. some teams use gromitor for quick operational visibility and Prometheus for long-term retention and custom instrumentation.
does gromitor support custom metrics from my application?: not currently. gromitor focuses on host-level container resource metrics (cpu, memory, network i/o, disk i/o). for application-level custom metrics (business KPIs, request rates, error rates) you'd still want Prometheus with a client library or a product like Datadog.
how does gromitor handle security? i'm worried about forwarding metrics to a third party.: the agent collects only resource utilization metrics — container names, cpu percentages, memory bytes, i/o counters. it does not collect application data, environment variables, or logs. data in transit uses TLS. for teams with strict data residency requirements, the open-source stack is a better fit.
what's the migration path if i want to move back to self-hosted tools?: removing gromitor is a one-line docker command (or kubectl delete for kubernetes). your historical data in gromitor's backend is exportable. there's no lock-in at the infrastructure level — the agent is stateless and disposable.

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