Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. It is now a CNCF-graduated project, released under the Apache 2.0 license, and widely used for Kubernetes and cloud-native metrics monitoring.
Pricing matters because Prometheus is free only in the software-license sense. Teams still pay for compute, storage, high availability, long-term retention, scaling tools, dashboards, alerting maintenance, and engineering time.
In this guide, we’ll verify Prometheus pricing in 2026, explain self-hosted and managed Prometheus costs, summarize public user-review themes, and compare Prometheus with alternatives such as CubeAPM, Grafana Cloud, Datadog, and Dynatrace.
What Is Prometheus?
Prometheus is a monitoring and alerting toolkit for collecting, storing, querying, and alerting on metrics. It stores data as time series, where each series is identified by a metric name and labels. Teams query that data with PromQL, Prometheus’s own query language.
Prometheus commonly runs with Grafana for dashboards and Alertmanager for alert routing. Alertmanager handles grouping, deduplication, silencing, inhibition, and routing alerts to receivers such as email, PagerDuty, Opsgenie, and webhooks.
Because Prometheus is a toolkit, not a complete managed observability platform, teams usually run it in one of three ways: self-hosted Prometheus, self-hosted Prometheus with a scale-out layer such as Thanos/Cortex/Mimir, or a managed Prometheus-compatible service from AWS, Google Cloud, Azure, Grafana Cloud, or another provider.
Supported Languages, Integrations, and Data Sources
Prometheus supports application and infrastructure monitoring through client libraries, exporters, service discovery, and remote-write integrations.
| Area | Prometheus support |
| Languages | Official client libraries include Go, Java/Scala, Python, and Ruby; community libraries cover additional languages. |
| Infrastructure | Linux, Windows, Kubernetes, containers, VMs, databases, queues, web servers, and network systems through exporters. |
| Kubernetes | Commonly used with Kubernetes service discovery, kube-state-metrics, node-exporter, and Prometheus Operator patterns. |
| Dashboards | Usually paired with Grafana, although Prometheus has its own expression browser. |
| Alerting | Prometheus alert rules plus Alertmanager for routing, grouping, silencing, and deduplication. |
| OpenTelemetry | Prometheus can be used with OpenTelemetry through Prometheus scraping and remote-write paths. |
Key Features of Prometheus
Prometheus stores metrics using labels, which makes it flexible for slicing data by service, pod, namespace, status code, region, or other dimensions. PromQL lets teams aggregate and transform this data for alerts, dashboards, and troubleshooting.
Prometheus usually pulls metrics from HTTP endpoints instead of requiring every application to push metrics to a backend. This model works well for infrastructure and Kubernetes workloads where scrape targets can be discovered dynamically.
Prometheus evaluates alerting rules, while Alertmanager handles alert grouping, deduplication, silencing, inhibition, and routing to notification tools. This separation is one reason Prometheus remains popular in SRE and platform engineering teams.
Prometheus is one of the default choices for Kubernetes metrics because many Kubernetes components, exporters, Helm charts, and operators expose or collect Prometheus-format metrics.
Prometheus has exporters for systems that do not expose Prometheus metrics natively. The official docs describe exporters as a way to export metrics from third-party systems such as HAProxy or Linux system stats.
Prometheus includes local on-disk time-series storage, but it can also integrate with remote storage systems. For long-term retention, global querying, and horizontal scale, teams commonly add tools such as Thanos, Cortex, Mimir, VictoriaMetrics, or a managed Prometheus backend.
Prometheus Pricing in 2026
Prometheus core has no license fee. The official Prometheus site says it is 100% open source and that all components are available under the Apache 2.0 License.
That does not mean Prometheus is cost-free in production. The real cost usually comes from:
| Cost area | What you pay for |
| Infrastructure | Prometheus servers, storage, replicas, load, and backup capacity |
| Long-term retention | Object storage, remote storage, Thanos, Cortex, Mimir, or managed backends |
| Engineering time | Setup, scaling, upgrades, alert rules, dashboards, and incident response |
| High availability | Redundant Prometheus instances, remote-write pipelines, and failover |
| Managed service fees | Per-sample ingestion, query, storage, and active-series billing, depending on provider |
Self-Hosted Prometheus Pricing
Self-hosted Prometheus has no software subscription fee. A small internal deployment can be inexpensive if it runs on existing infrastructure and only needs short retention.
The cost changes when Prometheus becomes a production monitoring system. High availability, long retention, multi-cluster querying, cardinality control, and storage tuning all add cost. Self-hosted Prometheus is usually cheapest when a team already has strong Kubernetes/SRE skills and can maintain the stack without creating a dedicated observability operations burden.
A realistic self-hosted Prometheus cost model should include:
| Component | Why it matters |
| Prometheus servers | CPU and memory increase with scrape volume and active series |
| Disk or object storage | Retention and cardinality drive storage needs |
| HA replicas | Production teams usually avoid a single monitoring instance |
| Grafana | Dashboards need hosting, access control, upgrades, and maintenance |
| Alertmanager | Alert routing needs configuration and ongoing tuning |
| Thanos/Cortex/Mimir | Often needed for long retention, global queries, and large environments |
| Engineering labor | Usually the largest hidden cost once the stack becomes business-critical |
Managed Prometheus Pricing: AWS, Google Cloud, Azure, and Grafana Cloud
Managed Prometheus services reduce the operational burden, but they charge based on usage. The main billing units are usually metric samples ingested, samples queried, stored data, active series, or data points per minute.
| Provider | Published pricing model | Verified pricing detail |
| Amazon Managed Service for Prometheus | Ingestion, storage, query samples, and optional collector charges | AWS says AMP charges for metrics ingested, queried, stored, and collected. Its pricing example uses $0.90 per 10M samples for ingestion, $0.03/GB-month for storage, and $0.10 per billion query samples processed. |
| Google Cloud Managed Service for Prometheus | Per-sample ingestion tiers, plus Cloud Monitoring read/query usage | Google lists $0.060 per million samples for the first 0–50B samples, then lower tiered rates at higher volumes. |
| Azure Monitor managed service for Prometheus | Metrics ingestion and metrics queries in Azure Monitor Workspace | Azure says metrics sent to an Azure Monitor Workspace, including Managed Prometheus and OpenTelemetry metrics, are charged by samples ingested and samples processed for queries; ingestion includes 18 months of retention. |
| Grafana Cloud Metrics | Active series and data points per minute | Grafana Cloud Pro lists metrics at $6.50 per 1K series, with a $19/month platform fee that includes 10K active series and 13 months retention. |
AWS Managed Prometheus Example
AWS publishes a worked example for one Kubernetes cluster with 10 nodes and 1,000 metrics per node collected every 30 seconds for 744 hours. AWS calculates 892.8 million samples ingested, $80.93 ingestion cost, $0.10 storage cost, $0.72 query cost, and a total monthly charge of $81.75 before Free Tier benefits.
That example is useful, but it is not a universal benchmark. Real bills can rise quickly when the number of nodes, scrape targets, labels, scrape frequency, dashboards, and alert rules increase.
Prometheus Is Free, But Production Operations Still Add Cost
📌 Note on DIY Operational Overhead
Prometheus is free to license, but a DIY monitoring stack still needs to be operated. Teams are responsible for deployment, upgrades, scaling, retention planning, dashboard maintenance, alert tuning, backup strategy, high availability, and troubleshooting the monitoring system itself.
That overhead may be small for simple environments, but it grows as infrastructure becomes more distributed. In larger setups, the real cost is not the Prometheus license. It is the time and effort required to keep the monitoring stack reliable, accurate, and useful during incidents.
Prometheus itself is free to use. The core project is open source under the Apache 2.0 license, so teams do not pay license fees, host fees, user fees, or per-GB ingestion fees when they self-host it.
The cost appears when Prometheus becomes part of a production monitoring stack. Teams still need compute, memory, disk, retention planning, Grafana dashboards, Alertmanager routing, high availability, backups, upgrades, and scaling tools for larger environments.
For small teams, this can remain inexpensive. A basic Prometheus setup with short retention and a few scrape targets may only need modest infrastructure. But larger Kubernetes or multi-cluster environments usually need more storage, replicas, remote write, object storage, and long-term querying layers such as Thanos, Cortex, or Mimir.
Estimated Self-Hosted Prometheus Operating Cost
These are directional editorial estimates, not official Prometheus costs. Prometheus has no license price. The numbers below estimate the infrastructure and supporting services needed to run Prometheus in production. They do not include internal engineering time.
| Team profile | Typical setup | Estimated monthly operating cost |
| Small team | 1 Prometheus server, Grafana, Alertmanager, short retention, limited HA | ~$100–$300/month |
| Growing team | HA Prometheus, multiple Kubernetes clusters, Grafana, Alertmanager, longer retention, more storage | ~$500–$1,500/month |
| Mid-market team | Multi-cluster HA setup, remote write, long-term storage, object storage, Thanos/Cortex/Mimir-style scaling | ~$2,000–$6,000+/month |
These estimates cover the kind of infrastructure Prometheus needs around it: servers, storage, replicas, dashboards, alerting, long-term retention, and scaling components. The exact amount depends on active series, scrape interval, retention period, cloud provider, and how many clusters or environments are monitored.
The key takeaway is simple: Prometheus is free to adopt, but production Prometheus is not always free to run. At small scale, the cost can be very low. At larger scale, the cost usually shifts into infrastructure, storage, high availability, and operational complexity rather than software licensing.
What Drives Prometheus Costs?
Cardinality is the number of unique label combinations across metrics. Labels such as pod, container, endpoint, customer ID, request ID, and status code can multiply active series quickly. This affects memory, storage, query performance, and managed-service bills.
Scraping every 15 seconds creates about four times as many samples as scraping every 60 seconds. In managed services that charge per sample, scrape interval directly affects ingestion cost.
Short local retention is cheap. Long retention usually requires larger disks, object storage, remote storage, or a managed backend.
A single Prometheus server may be acceptable for small internal workloads, but production teams usually need redundancy. HA replicas increase infrastructure usage and operational complexity.
Dashboards, alert rules, recording rules, and ad hoc PromQL queries all consume resources. Managed providers may also charge for query samples processed.
Prometheus requires ongoing work: target discovery, exporter updates, rule tuning, dashboard maintenance, upgrades, scaling, and troubleshooting. For many teams, this is the largest hidden cost.
Prometheus User Reviews
Prometheus has strong visibility on G2. G2 lists Prometheus at 4.5/5 based on 62 reviews, with categories including container monitoring, database management systems, and time series databases. G2’s review summary says users praise integrations, alerting, cloud-native monitoring, custom metrics, and handling complex data, while noting that PromQL and the learning curve can be challenging.
Capterra lists Prometheus at 4.3/5 based on 9 reviews in its Database Monitoring category. However, Capterra also marks “starting price” as “contact vendor,” which is not accurate for the open-source Prometheus project itself and likely reflects limitations of directory-style product listings rather than Prometheus licensing.
| Review source | Rating shown publicly | Notes |
| G2 | 4.5/5 from 62 reviews | Best available review source for Prometheus monitoring |
| Capterra | 4.3/5 from 9 reviews | Useful, but directory pricing fields should be treated carefully |
| Gartner Peer Insights | Not used | Search results surfaced “Prometheus Platform,” which appears to refer to a different product/vendor category, not the open-source monitoring project |
What Users Like
- Users praise Prometheus for easy integrations, especially with Grafana and cloud-native environments. G2’s review summary highlights integrations, alerting, cloud-native monitoring, custom metrics, and the ability to handle complex data.
- Users also value Prometheus because it is open source, widely adopted, and flexible enough for Kubernetes, infrastructure, and application metrics.
- PromQL is another major strength. It gives experienced users a powerful way to query and aggregate time-series data for dashboards and alerts.
What Users Criticize
⚠️ Disclaimer
These points reflect public user-review and community themes. They are not universal limitations for every Prometheus deployment.
- Users commonly point to PromQL’s learning curve. G2 specifically highlights that many users find the learning curve, especially PromQL, challenging for new users.
- Visualization is also a common limitation. Prometheus has a basic UI, but most teams use Grafana for production dashboards.
- Prometheus can become operationally demanding at scale. Long retention, high cardinality, multi-cluster querying, and high availability often require additional systems such as Thanos, Cortex, Mimir, or a managed Prometheus backend.
Prometheus Alternatives: How it Compares to Competitors
Prometheus is strongest as a metrics toolkit. Alternatives usually fall into two categories: Prometheus-compatible managed backends or broader observability platforms that combine metrics, logs, traces, dashboards, and alerting.
Prometheus vs CubeAPM
Prometheus is a metrics-first open-source toolkit. CubeAPM is a self-hosted, vendor-managed observability platform with metrics, logs, traces, APM, RUM, synthetics, error tracking, SLOs, RBAC, SSO, MFA, and audit logs under a published $0.15/GB ingestion model.
| Category | Prometheus | CubeAPM |
| Deployment | Self-hosted or managed by cloud provider | Self-hosted, vendor-managed in customer environment |
| Pricing model | Free core; managed services charge by samples/series/query usage | $0.15/GB ingestion |
| Native telemetry scope | Metrics | Metrics, logs, traces, APM, RUM, synthetics, errors |
| Long retention | Requires planning or add-ons | Available in platform, depending on plan |
| Best for | Teams wanting a vendor-neutral metrics toolkit | Teams wanting unified observability with predictable ingestion pricing |
Prometheus vs Grafana Cloud
Grafana Cloud is often the natural managed path for teams that already like Prometheus and Grafana. It provides managed metrics, logs, traces, dashboards, alerting, and other observability products. Grafana Cloud Metrics Pro lists $6.50 per 1K series, with a $19/month platform fee that includes 10K active series and 13 months metrics retention.
| Category | Prometheus self-hosted | Grafana Cloud |
| Operations | Team manages backend | Grafana Labs manages backend |
| Metrics model | Prometheus-native | Prometheus-compatible |
| Pricing | Infra + labor | Active series/DPM and platform pricing |
| Dashboards | Usually self-hosted Grafana | Hosted Grafana included |
| Best for | Teams wanting control | Teams wanting managed Prometheus-style metrics |
Prometheus vs Datadog
Prometheus is open source and metrics-focused. Datadog is a SaaS observability platform that combines infrastructure monitoring, APM, logs, RUM, synthetics, security, and many integrations. Datadog reduces operational burden but uses commercial SaaS pricing across products and usage dimensions.
| Category | Prometheus | Datadog |
| Deployment | Self-hosted or managed backend | SaaS |
| Pricing | Free core; infrastructure/labor or managed sample billing | Commercial SaaS pricing by product and usage |
| Telemetry scope | Metrics-first | Metrics, logs, traces, RUM, synthetics, security |
| Data control | Can stay in your environment | Data is sent to Datadog |
| Best for | Teams with SRE capacity and open-source preference | Teams wanting a fully managed commercial platform |
Prometheus vs Dynatrace
Prometheus is a flexible metrics toolkit. Dynatrace is an enterprise observability platform with APM, infrastructure monitoring, logs, traces, Kubernetes monitoring, automation, and AI-assisted analysis. Dynatrace is usually a better fit for large enterprises that want managed observability depth, while Prometheus is stronger for teams that want open-source control and PromQL-based metrics.
| Category | Prometheus | Dynatrace |
| Deployment | Self-hosted or managed Prometheus-compatible service | SaaS or enterprise deployment options |
| Pricing | Free core; operational cost or managed-service billing | Commercial enterprise pricing |
| Query model | PromQL | Dynatrace platform query/analytics model |
| Operations | Team-owned unless managed service is used | Vendor-managed platform experience |
| Best for | Open-source metrics monitoring | Enterprise full-stack observability |
Is Prometheus the Right Choice?
Prometheus Works Best For
- Prometheus is a strong fit for Kubernetes-native teams that want open-source metrics monitoring and already have SRE or platform engineering capacity.
- It also works well for teams that value vendor neutrality, PromQL, open instrumentation patterns, and a large exporter ecosystem.
- Prometheus can be cost-effective for small to moderate metric volumes, especially when the team already has the skills to operate it.
Prometheus May Not Be the Right Fit For
- Prometheus may not be ideal for teams without DevOps or SRE capacity. The software is free, but production ownership is real.
- It may also be limited for teams that need logs, traces, RUM, synthetics, and APM in the same platform. Prometheus focuses on metrics, so unified observability requires additional tools.
- High-cardinality, long-retention, multi-cluster environments should not rely on a basic single-node Prometheus setup. Those teams should plan for Thanos, Cortex, Mimir, VictoriaMetrics, Grafana Cloud, cloud-provider managed Prometheus, or another scalable backend.
Conclusion
Prometheus remains one of the strongest open-source choices for metrics monitoring. It is free, Apache 2.0 licensed, Kubernetes-friendly, PromQL-powered, and supported by a large ecosystem of exporters and integrations.
The pricing story is more nuanced. Self-hosted Prometheus has no license fee, but teams still pay for infrastructure, storage, high availability, long-term retention, dashboards, alerting, and engineering time. Managed Prometheus services reduce that operational load but introduce usage-based pricing around samples, queries, active series, or DPM.
For teams that only need metrics and have strong internal SRE capacity, Prometheus is still a great choice. For teams that want metrics, logs, traces, APM, RUM, synthetics, and predictable pricing in one platform, alternatives such as CubeAPM, Grafana Cloud, Datadog, and Dynatrace are worth comparing.
FAQs
1. Is Prometheus completely free?
Prometheus core is free and open source under the Apache 2.0 license. You still pay for the infrastructure and engineering time required to run it in production.
2. Does Prometheus charge per host?
No. Open-source Prometheus does not charge per host. If you use a managed Prometheus service, pricing is usually based on samples ingested, samples queried, storage, active series, or DPM.
3. How much does Amazon Managed Service for Prometheus cost?
AWS charges based on metric samples ingested, stored data, query samples processed, and optional collector usage. In AWS’s own example, 892.8 million samples ingested plus storage and query usage totals $81.75/month before Free Tier benefits.
4. How much does Google Cloud Managed Service for Prometheus cost?
Google lists Managed Service for Prometheus ingestion pricing at $0.060 per million samples for the first 0–50 billion samples, with lower tiered rates for higher volumes.
5. How much does Azure managed Prometheus cost?
Azure says Managed Prometheus metrics in an Azure Monitor Workspace are charged by samples ingested and samples processed for queries. The metrics ingestion cost includes 18 months of retention.
6. What are the best Prometheus alternatives?
The best alternatives depend on the goal. CubeAPM is a good fit for self-hosted, OpenTelemetry-native unified observability with predictable per-GB pricing. Grafana Cloud is strong for managed Prometheus-compatible metrics and hosted Grafana. Datadog and Dynatrace are stronger for fully managed enterprise observability.