Buyer’s Guide - October 2026

10 best hybrid cloud monitoring tools, ranked

Q: Is Netdata suitable for large hybrid fleets?

Yes. Per-node pricing decreases as node count grows, containers are included at no extra cost, and offline nodes are not billed. Netdata Parents aggregate streams and provide high availability with automatic failover, an architecture proven at very large scale. For regulated or air-gapped segments, Enterprise On-Premises adds RBAC, SSO and local sign-in inside your network.

Hybrid monitoring is defined by the seam: one tool that collects identically on a data-center VM and a cloud node, correlates both halves in a single view, and survives the data-residency rules that rule out SaaS-only backends. We ranked 10 tools on unified visibility, deployment flexibility, collection coverage and what the bill does when your chatty on-prem fleet joins the account.

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10 best hybrid cloud monitoring tools, ranked product interface

Why this list exists

Most “best monitoring tools” lists assume your whole estate lives in one place. Hybrid buyers know better. The estate is split between your own racks (bare metal, VMs, network gear, maybe Kubernetes) and one or more public clouds, and the hard part is not features, it is the seam between the two halves.

The mistake that burns teams most often is buying a cloud-native SaaS suite for the whole estate and discovering, mid-rollout, that the regulated half cannot ship telemetry to a vendor cloud at all. The reverse mistake is nearly as common: extending a traditional on-prem poller that never gained real Kubernetes or cloud-service depth. Either way you end up with two consoles, two alert streams and an incident workflow that stops at the firewall.

Three dimensions decide the outcome more than any feature checklist:

Where telemetry is allowed to live. If any workload is air-gapped or data-residency-bound, SaaS-only backends are out for that part of the estate. Check whether the self-hosted mode has feature parity, including the AI features, which vendors often keep in their own cloud.
Whether collection is identical on both halves. One agent or collector that behaves the same on bare metal, VMs, Kubernetes and cloud nodes is what makes a single view possible. Two products sharing a brand name is not the same thing.
How the bill grows. Per-GB ingest pricing punishes chatty on-prem fleets. Model the pricing against your noisiest environment, not your cleanest one.

A note on prices: we do not quote competitor list prices. They change, they are negotiated, and a stale number helps nobody. Instead we describe each vendor’s pricing shape, what unit the bill grows with, and link the official pricing page so you can model your own fleet. If your estate is cloud-only, our best cloud monitoring tools ranking is the tighter list; this page is for teams straddling both worlds.

We assembled the shortlist from vendor documentation and pricing pages, independent comparison write-ups, and practitioner threads in r/sysadmin and r/ITManagers where hybrid deployments are discussed without a sales filter. Every tool here credibly monitors both on-premises infrastructure and at least the three major public clouds.

The heaviest weights go to the two things that define the category: whether both halves of the estate land in one correlated view, and whether deployment and data-sovereignty options cover regulated or air-gapped segments with feature parity. Cost predictability and collection breadth follow, because hybrid fleets are large and noisy. AI-assisted root cause is a real differentiator but weighted as one; operational effort rounds out the scoring.

Tester credit

Compiled by the Netdata team - Updated October 14, 2026

Sources verified

Scoring criteria

Unified view across on-prem and cloud 25%
One dashboard, alert stream and query across both halves, or stitched consoles.
Deployment flexibility and data sovereignty 20%
SaaS, self-hosted and air-gapped options, with feature parity on self-hosted.
Collection model and coverage breadth 15%
One collector across bare metal, VMs, Kubernetes and cloud; auto-discovery; OTel.
Cost predictability at hybrid scale 15%
What unit the bill grows with, and how it behaves on a high-volume on-prem fleet.
Real-time resolution and alerting quality 10%
Default granularity, anomaly detection at the edge, alert quality.
AI and root-cause analysis 10%
Whether AI runs where the data lives or requires the vendor cloud.
Operational effort to run 5%
Setup time and Day-2 burden, especially for self-hosted stacks.

Vendor 01 / 10 · #netdata

Netdata

Per-second, edge-based observability with the same open-source agent on every on-prem and cloud node, ML trained on the node, and a fleet view in Netdata Cloud.

Best for

Teams that want one agent across data-center VMs, bare metal, Kubernetes and AWS/Azure/GCP with zero-config auto-discovery
Environments where telemetry must stay on the node: ML runs locally and raw data never leaves the host
Buyers burned by per-GB or per-host-plus-module bills who want predictable per-node pricing

Pricing

Per-node pricing: Cloud Business from $4.50/node/month on annual plans, with the per-node price decreasing as node count grows
Not billed: metrics volume, Logs Monitoring (querying logs in place), users, data retention, containers
Community plan free for personal, non-commercial use with up to 5 active connected nodes; businesses use the open-source Agent or Cloud Business with a 14-day trial
Logs Management is in Free Preview; Traces are marked Free Preview on the price list

Pros

Per-second metric collection on every node with sub-2-second latency, versus minute-level defaults on most competitors
800+ integrations with auto-discovery across on-premises, AWS, Azure, GCP and Kubernetes; the same agent everywhere, no cloud-specific variants
Unsupervised ML (18 models per metric) trains on the node with a claimed 99% false-positive reduction and zero data egress for anomaly detection
Multi-tier on-node storage retains roughly 2 years of metrics out of the box at about 0.6 bytes per sample
Ingests OpenTelemetry metrics, logs and traces over OTLP; spans are stored and indexed on your own agents and explored in the Netdata Cloud Traces tab
Enterprise On-Premises supports fully air-gapped deployments with local sign-in; SOC 2 Type 2, GDPR/HIPAA/PCI DSS alignment

Where it falls short

Code-level and continuous profiling remain the strength of APM-first suites such as Dynatrace and Datadog; Netdata does OpenTelemetry distributed tracing next to per-second infrastructure metrics
Log search has no Splunk- or Elastic-class full-text index; Logs Monitoring queries the operating systems’ own log stores in place
Cloud-service monitoring leans on native integrations and Prometheus exporters rather than the deep agentless managed-service inventories of Datadog or New Relic

Verdict

Netdata leads this category because it solves the two problems that break hybrid deployments: identical collection on both halves, and telemetry that never has to leave your boundary. The same GPLv3+ agent auto-discovers bare metal, VMs, containers, Kubernetes and the three major clouds at per-second resolution, parents aggregate streams, and Netdata Cloud (or Enterprise On-Prem for air-gapped networks) provides the single pane. Because ML trains on the node and metrics stay on your disk, the regulated half of the estate is not an exception case. Per-node pricing with no metrics-volume charges means the chatty on-prem fleet does not ambush the budget. The honest caveat: teams needing code-level profiling or a full-text log platform will pair it with a specialist for those workloads.

Get started with Netdata -> See hybrid cloud observability ->

Vendor 02 / 10 · #dynatrace

Dynatrace

Enterprise observability with OneAgent auto-discovery, Davis AI root-cause analysis and a self-hosted Managed option for large hybrid estates.

Best for

Large enterprises with complex hybrid estates that want automated discovery and AI-assisted root cause
Organizations needing deep APM and Smartscape topology mapping across on-prem and cloud applications

Pricing

Dynatrace Platform Subscription: one annual platform-level commitment consumed against a rate card, with unit prices decreasing at larger commitments
Rate card bills per host-hour for infrastructure and per memory-GiB-hour for full-stack; no per-seat fees
Bill grows with monitored host count, host memory size and which capabilities are consumed
Self-hosted Dynatrace Managed is a separate, enterprise-negotiated deployment

Pros

OneAgent auto-discovers applications, services, containers and hosts across on-prem, private cloud and public cloud
Davis AI gives deterministic root-cause analysis over the Smartscape topology, a genuinely different approach from per-metric anomaly detection
One of the few premium suites with a credible self-hosted deployment (Dynatrace Managed)
Ingests OpenTelemetry metrics and traces alongside OneAgent telemetry

Cons

Premium pricing above most competitors; the annual commitment model suits large buyers, not mid-market teams
Proprietary OneAgent creates lock-in; OpenTelemetry support is partial rather than native-first
Licensing across modules takes real effort to model before purchase

Verdict

Dynatrace is the strongest premium answer for large hybrid enterprises: deep APM, automated discovery across both halves of the estate, and one of the only SaaS-suite vendors with a real self-hosted mode. Davis AI’s topology-based root cause is a genuine differentiator for sprawling application estates. The trade-offs are price and commitment shape: the platform subscription rewards big annual commitments, and mid-market teams will find it over-budget and over-built. If you need APM depth plus an on-prem option and have enterprise budget, this is the shortlist’s number two.

Read full Netdata vs Dynatrace -> Dynatrace pricing ->

Vendor 03 / 10 · #datadog

Datadog

The broadest SaaS observability platform, with the same agent on-prem and in every major cloud, but no self-hosted backend.

Best for

Cloud-first teams that can keep all telemetry in SaaS and want one platform for infra, APM, logs, RUM and security
Enterprises that value the deepest integration catalog over deployment control

Pricing

Per-host pricing for infrastructure, with separate per-host or per-container charges for APM and other products
Per-GB log ingestion plus separate indexing fees; each product module bills separately
Bill grows with host count, log volume, indexed events and enabled modules
SaaS only; CloudPrem keeps log storage in your infrastructure but the control plane stays in Datadog’s cloud

Pros

Same agent on bare metal, VMs, containers and Kubernetes, on-prem or in any cloud, plus agentless AWS/Azure/GCP integrations
Very broad product surface: infrastructure, APM, logs, RUM, synthetics and security in one platform
700+ integrations with strong auto-discovery and tagging of dynamic infrastructure
Private-cloud integrations for OpenStack, VMware and Hyper-V cover the virtualization layer many hybrid estates still run

Cons

No on-prem backend: all telemetry leaves your premises, ruling out air-gapped or strictly regulated workloads
Per-host plus per-GB pricing compounds quickly on large, chatty on-prem fleets
AI features (Watchdog, Bits AI) are SaaS-only and cannot run inside your boundary

Verdict

On collection coverage alone Datadog would top this list: the same agent works on both halves, the integration catalog is the deepest here, and the product surface is unmatched. But hybrid monitoring is graded on the seam, and Datadog fails the data-sovereignty test: if any segment of your estate cannot ship telemetry to a vendor cloud, Datadog is out for that segment, which breaks the single-view promise exactly where hybrid teams need it. Cost forecasting is the second concern, since per-host and per-GB charges stack on noisy fleets. An excellent pick for SaaS-compatible estates; disqualified for regulated ones.

Read full Netdata vs Datadog -> Datadog pricing ->

Vendor 04 / 10 · #elastic

Elastic Observability

Search-based observability on Elasticsearch with genuinely air-gapped self-managed deployment, best-in-class log search, and AI that can run against your own LLM.

Best for

Log-heavy hybrid teams where search and security analytics are central
Organizations with data-residency or air-gap requirements that still want AI features, via a self-hosted LLM and local ML

Pricing

Resource-based on Elastic Cloud Hosted or usage-based on Serverless; enterprise tiers are sales-quoted
Self-managed distribution is open source (Elastic License/AGPL for recent versions) and you operate it yourself; the real cost is Elasticsearch operations
Bill grows with ingested GB, indexed data and deployment resources

Pros

Runs as Elastic Cloud SaaS or fully self-managed via ECK/ECE, with documented air-gapped deployments at feature parity
Single Elastic Agent for logs, metrics, traces and security data, now bundling an OpenTelemetry collector
Agentless integrations for AWS, Azure and GCP; 450+ out-of-the-box integrations
AI Assistant can run against a self-hosted LLM with no outbound access; ML anomaly detection runs locally
ES|QL gives one query language across logs, metrics and traces

Cons

Operating Elasticsearch at scale is a real commitment in storage, tuning and staffing
Collection leans on agents and OpenTelemetry rather than eBPF auto-discovery; less turnkey than SaaS suites
No native SNMP-style network-device polling depth comparable to SolarWinds or Checkmk

Verdict

Elastic is the best deployment-flexibility story among the commercial platforms: air-gapped self-managed mode with parity, and an AI layer that can stay inside your boundary, which almost nobody else offers. For hybrid estates where log search and security analytics sit at the center, it is a natural fit. The price is operational: you are running a search cluster, and the staffing and tuning burden is real. Buyers who want turnkey infrastructure monitoring rather than a search platform should weigh that honestly.

Read full Netdata vs Elastic -> Elastic pricing ->

Vendor 05 / 10 · #solarwinds

SolarWinds Observability

Long-standing IT-ops monitoring with a genuinely self-hosted Orion platform and strong SNMP/WMI polling, paired with a separate OpenTelemetry-native SaaS product.

Best for

IT-ops teams with a substantial network and on-prem footprint that want the control plane in-house
Windows-heavy enterprises modernizing toward hybrid observability on familiar ITOM workflows

Pricing

Subscription licensing per node or per entity; the self-hosted and SaaS products are licensed separately
Independent write-ups report a multi-year subscription commitment posture on the self-hosted line
Bill grows with node count and licensed modules (network, database, application, logs)
The SaaS product is usage-based

Pros

A genuinely self-hosted product (SolarWinds Observability Self-Hosted) running behind your firewall
Best-in-class traditional network and infrastructure monitoring via SNMP and WMI polling of devices, servers and VMs
Multi-cloud visibility for AWS, Azure and GCP in both deployment models
The SaaS product adds OpenTelemetry-native collection, Kubernetes monitoring and synthetic probes

Cons

Self-hosted and SaaS are two separate products, not one platform in two modes; rich network monitoring and cloud-native depth may mean running both
AI anomaly alerting runs in SolarWinds’ cloud AIOps service and needs outbound connectivity even on the self-hosted product, so it is not an air-gapped fit
Limited OpenTelemetry support on the self-hosted line; reviewers report a dated UI

Verdict

SolarWinds owns the traditional half of hybrid better than anyone here: SNMP/WMI polling of network devices, Windows servers and VMware, with a real on-prem deployment. The problem is the other half. Kubernetes and OpenTelemetry depth live in a separate SaaS product with separate licensing, so the unified view splits into two products, and the AI layer phones home even when the platform does not. A strong choice for network-and-Windows-heavy estates; verify which product covers your cloud-native workloads before signing.

Read full Netdata vs SolarWinds -> SolarWinds pricing ->

Vendor 06 / 10 · #logicmonitor

LogicMonitor

SaaS hybrid-IT monitoring with on-prem collectors, strong auto-discovery and a Hybrid Unit licensing model built to span on-prem, cloud and edge.

Best for

Mid-market and enterprise ops teams that want agentless-style onboarding and auto-discovery with minimal configuration
MSPs needing multi-tenant monitoring across customer environments

Pricing

Platform packages priced per Hybrid Unit, a flexible unit covering on-prem devices, cloud IaaS instances, PaaS services, wireless access points or OpenTelemetry metrics volume
Tiered packages (Essentials, Advanced, Signature with Edwin AI) bundle capabilities at a per-unit price
Bill grows with total monitored resources across on-prem, cloud and edge; sales-quoted

Pros

On-prem collectors feed the SaaS control plane, so internal segments are monitored without internet exposure
Strong auto-discovery with 2,000+ pre-built integrations across servers, network devices, cloud services and applications
Hybrid Unit licensing shifts capacity between on-prem, cloud and edge without changing the model
Topology mapping, anomaly-based alerting and MSP-friendly multi-tenancy; recommended in r/sysadmin threads for large hybrid fleets

Cons

SaaS-first: the control plane cannot be self-hosted, so restricted networks and air-gapped data centers are out
Pricing requires sales engagement; per-unit costs are not published
Limited OpenTelemetry depth relative to OTel-native platforms

Verdict

LogicMonitor is a genuine hybrid specialist: the collector architecture and Hybrid Unit licensing were designed for estates that straddle on-prem and cloud, and practitioners recommend it for large mixed fleets. It ranks mid-list for one structural reason: the control plane is SaaS-only, so the regulated half of a hybrid estate has no option. If your data-residency constraints are satisfied by collectors-in, control-plane-out, it deserves a serious look; the sales-quoted pricing means modelling costs requires a conversation first.

Read full Netdata vs LogicMonitor -> LogicMonitor pricing ->

Vendor 07 / 10 · #checkmk

Checkmk

Infrastructure-first monitoring for hybrid IT with 2,000+ integrations, self-hosted and SaaS editions, and host/service-based pricing that avoids ingest taxes.

Best for

Hybrid and on-prem environments, MSPs and regulated enterprises wanting predictable per-service pricing
Teams consolidating server, network, cloud and application monitoring under one alerting layer

Pricing

Subscription priced per service (infrastructure), per custom metric (application observability via OpenTelemetry) and per synthetic test
Open-source Community edition; paid editions (Pro, Ultimate self-managed, Cloud SaaS) are subscription-based
Bill grows with monitored services and custom metrics, not raw ingest volume
Self-hosted editions scale to very large host counts via distributed monitoring; the Cloud edition is capped lower

Pros

Centralized visibility across hybrid IT, data centers and multi-cloud with 2,000+ pre-built integrations
Self-managed Ultimate edition runs in your own AWS or Azure tenant via marketplace BYOL
Application Observability ingests OpenTelemetry metrics; synthetic monitoring add-on on self-hosted editions
Auto-discovery and rule-based configuration that sysadmins consistently praise in practitioner threads

Cons

No native distributed tracing or code-level APM; application observability is metrics-only via OpenTelemetry
Migration between self-hosted editions and Checkmk Cloud is not supported in either direction
Cloud edition is scale-capped relative to self-hosted; log management is not a core strength

Verdict

Checkmk covers the infrastructure half of hybrid very well: servers, network, VMs and cloud instances under predictable per-service pricing that does not punish volume, with serious self-hosted scale. Sysadmin communities recommend it regularly for exactly this profile. It ranks here rather than higher because application-level depth stops at metrics: there is no tracing and no code-level APM, so teams with microservices workloads will need a second tool. For infrastructure-centric hybrid estates, one of the best value propositions on the list.

Read full Netdata vs Checkmk -> Checkmk pricing ->

Vendor 08 / 10 · #grafana

Grafana (LGTM stack)

The composable open observability stack - Prometheus, Loki, Tempo, Mimir and Grafana - that self-hosts identically on-prem or runs as Grafana Cloud.

Best for

Prometheus-first SRE teams that want full data control and no vendor lock-in
Organizations with platform-engineering capacity to build and operate their own telemetry stack

Pricing

Open source and self-hosted: you run and operate it, and the real cost is platform-engineering hours
Grafana Cloud is usage-based, billed per active metrics series, per GB of logs and traces, plus per-seat charges on paid tiers
The self-managed Enterprise line is sales-quoted and, per third-party write-ups, in maintenance with end-of-life announced for early 2029
Bill grows with active series, ingested GB and user count on Cloud

Pros

The same open LGTM components self-host on-prem or run as Grafana Cloud, so the deployment model is genuinely flexible
Open standards throughout (Prometheus, OpenTelemetry, Loki, Tempo) minimize lock-in
Grafana Alloy collector with service discovery for AWS, Azure and GCP plus the Cloud Provider Observability app unifies multi-cloud collection
The de facto visualization layer with a huge dashboard and plugin ecosystem

Cons

You operate the stack yourself: assembling, securing and scaling Prometheus, Loki and Tempo is a significant ongoing commitment
The intelligence layer is tethered to Cloud: Grafana Assistant keeps its backend in Grafana Cloud even in self-managed Grafana, and Sift is Cloud-only
No built-in anomaly detection or AI-assisted root cause in the self-hosted stack

Verdict

Grafana is the maximum-flexibility, minimum-lock-in answer, and for teams that define hybrid monitoring as the same open stack everywhere, it is a legitimate choice. It ranks eighth because the category grades on turnkey outcomes: assembling, securing and scaling four backends across two environments is the highest operational burden here, and the AI features that speed up triage exist only in Grafana Cloud. Excellent for platform-engineering-rich organizations; a slow, expensive path for teams that wanted a product.

Read full Netdata vs Grafana -> Grafana pricing ->

Vendor 09 / 10 · #newrelic

New Relic

Turnkey SaaS observability with a single consumption model across on-prem agents and AWS/Azure/GCP integrations, but no self-hosted backend.

Best for

Engineering-led teams that want one turnkey SaaS platform across on-prem hosts and the three major clouds
Small teams that can live inside the free ingest allotment while evaluating

Pricing

Usage-based: billed per GB of ingest beyond a monthly free allotment, plus per-user seat charges for full-platform access
Bill grows with ingested telemetry volume and full-platform user count
SaaS only, in US or EU regions

Pros

Infrastructure agent covers on-prem and virtual hosts; agentless integrations connect AWS, Azure and GCP accounts into one platform
Strong OpenTelemetry and Prometheus ingest; unified APM, logs, metrics, traces and RUM with NRQL querying
A single consumption model reduces tool sprawl across the platform
New Relic AI provides an LLM-based assistant that queries telemetry and explains issues

Cons

No self-hosted backend: all on-prem telemetry must leave your premises
Per-user seat costs compound as the team grows; NRQL creates query-language lock-in
Cost forecasting is hard at high ingest; practitioner consensus is that bills climb with fleet chattiness

Verdict

New Relic is the cleanest consumption story among the SaaS suites: one ingest meter, one platform, friendly onboarding. As a hybrid tool it hits the same wall as Datadog: with no self-hosted backend, any regulated or air-gapped segment is simply out, and the single-view promise breaks at the firewall. Per-seat pricing adds a second growth lever that punishes large teams. If SaaS is acceptable across your entire estate it is a strong, engineer-friendly option; if not, it cannot be your hybrid answer.

Read full Netdata vs New Relic -> New Relic pricing ->

Vendor 10 / 10 · #zabbix

Zabbix

The open-source monitoring workhorse: self-hosted anywhere, covering networks, servers, VMs, containers and the major clouds, at the cost of real setup and maintenance effort.

Best for

Cost-conscious teams with in-house Zabbix expertise monitoring large mixed estates
Organizations that need full control and accept a higher maintenance burden

Pricing

Open source and self-hosted: you run and operate it, and the real cost is staff time and expertise
Optional paid support subscriptions and vendor-hosted Zabbix Cloud instances
Bill grows with infrastructure scale and the expertise you hire or contract

Pros

Monitors networks, servers, cloud (AWS, Azure, GCP templates), containers, VMware, databases and applications from one self-hosted platform
Zabbix proxies monitor segmented or hard-to-reach network zones, a natural fit for data-center estates
Massive template library and over a decade of community practice; the most-recommended open-source option in r/sysadmin hybrid threads
Zabbix Cloud Proxy extends the self-hosted model toward hybrid cloud collection

Cons

Setup and Day-2 maintenance are significant; practitioners warn against adopting it without an expert or vendor support
UI and workflow feel dated next to modern observability platforms; weak native APM and tracing
Cloud-native depth (Kubernetes, OpenTelemetry) is thinner than in OTel-native platforms

Verdict

Zabbix covers the breadth of hybrid infrastructure, and practitioner threads name it more than any other open-source tool for exactly this job. It ranks last not because it is weak but because it is a platform you operate, not a product you buy: without in-house expertise the maintenance burden dominates, and there is no modern APM or AI layer. For budget-constrained teams with Zabbix skills, it remains the default open-source answer. Everyone else should price the staffing honestly before choosing it.

Read full Netdata vs Zabbix -> Zabbix pricing ->

Frequently asked questions

What is hybrid cloud monitoring?

Hybrid cloud monitoring means watching workloads split between your own data center (VMs, bare metal, network devices, Kubernetes) and one or more public clouds from a single place. The hard parts are data-residency rules on one half, different collection models on each side, and correlating both halves in one view. It differs from pure cloud monitoring because deployment flexibility and data sovereignty become first-order requirements, not afterthoughts.

What is the best hybrid cloud monitoring tool in 2027?

Netdata leads for per-second collection on every node, edge-based ML that never requires data egress, roughly two years of on-node retention, and predictable per-node pricing. Dynatrace fits large enterprises needing deep APM plus a self-hosted option, and Datadog fits SaaS-first estates. The right answer depends on whether any part of your estate cannot ship telemetry to a vendor cloud; if it cannot, SaaS-only tools are out for that part.

Which monitoring tools can run fully on-premises or air-gapped?

Netdata (self-hosted agents and parents, with Enterprise On-Premises for air-gapped Cloud features), Elastic (documented air-gapped deployments with feature parity, and AI that can run on a self-hosted LLM), Checkmk self-hosted editions, Zabbix, the self-hosted Grafana LGTM stack, Splunk Enterprise, and SolarWinds self-hosted, though SolarWinds’ AI anomaly service still needs outbound connectivity. Datadog and New Relic have no self-hosted backend.

How much does hybrid cloud monitoring cost?

Pricing shapes differ more than prices across hybrid cloud monitoring software: per-node (Netdata, from $4.50/node/month on annual plans), per-host plus per-GB (Datadog, Splunk), per-GB plus per-seat (New Relic), an annual platform commitment (Dynatrace), per-service (Checkmk), per-Hybrid-Unit (LogicMonitor) and usage-based Cloud (Grafana). Open source is a distribution model, not a price: Zabbix, Grafana OSS and Checkmk Community cost staff time to run. Per-GB models punish chatty on-prem fleets, so model pricing against your noisiest environment.

Can one tool really monitor both on-premises and cloud with the same agent?

Some can. Netdata runs the same agent everywhere, with auto-discovery across on-prem, AWS, Azure, GCP and Kubernetes. Datadog and New Relic also use one agent on both halves, but all data goes to their SaaS. SolarWinds is two separate products (self-hosted and SaaS), not one platform in two modes, and LogicMonitor uses on-prem collectors feeding a SaaS control plane. Ask vendors specifically whether the on-prem and cloud deployment are the same product.

Do I need OpenTelemetry support for hybrid monitoring?

OpenTelemetry is the safest way to avoid a different proprietary agent per environment, so strong OTel support should be near the top of your checklist. Netdata ingests OTLP metrics, logs and traces; Elastic bundles an OTel collector in its agent; Grafana Alloy is an OTel collector; Checkmk ingests OTel metrics; Dynatrace and Datadog accept OTel alongside their proprietary agents. Partial OTel support, as on SolarWinds’ self-hosted line and LogicMonitor, limits portability.

What about monitoring network devices and legacy infrastructure in a hybrid estate?

SolarWinds is strongest for SNMP/WMI polling of network devices, servers and VMs, and Checkmk and Zabbix have deep traditional infrastructure coverage with huge template libraries. Netdata monitors network devices via SNMP collection and maps every TCP/UDP connection into process-to-process links for application dependency mapping. Cloud-native SaaS suites are generally weakest here, so if legacy gear matters, weight this criterion heavily.

Is Netdata suitable for large hybrid fleets?

Can I start free and scale later?

Yes, several ways. The Netdata Community plan is free for personal, non-commercial use with up to 5 active connected nodes; businesses start on the open-source Agent or Netdata Cloud Business with a 14-day trial. Grafana OSS and Zabbix are open source and self-hosted, so you operate them yourself, and Checkmk has an open-source Community edition for small estates. Datadog and New Relic offer trials and free ingest allotments but are commercial SaaS.

10 best hybrid cloud monitoring tools, ranked

How we evaluated hybrid cloud monitoring tools

Netdata

Dynatrace

Datadog

Elastic Observability

SolarWinds Observability

LogicMonitor

Checkmk

Grafana (LGTM stack)

New Relic

Zabbix

Frequently asked questions

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