Sold by: Grafana Labs
Deployed on AWS
Grafana Kubernetes Monitoring provides a simplified approach that enables you to monitor your Kubernetes fleet. You can use its rich interface to drill into your data, as well as take advantage of preconfigured dashboards, recording rules, and alert rules. Grafana Kubernetes Monitoring is only available with an active Grafana Cloud License.
4.5
Overview
Grafana Kubernetes Monitoring is an out-of-the-box solution that promptly detects infrastructure issues, optimizes costs & efficiency, predicts resource usage, automates incident management, and adapts to your specific services. It provides:
- Full visibility, from Kubernetes clusters to Kubernetes pods to quickly move throughout your Kubernetes setup in a single UI. Start with a cluster view and drill all the way down to specific Kubernetes pods with just a few clicks.
- Instant Prometheus-correlated logs. Prometheus and Grafana Loki shared metadata keeps the exact same labels for your Kubernetes cluster, so accessing correlated Kubernetes metrics and logs couldnt be easier.
- Better insight into your resource usage. You can dial in on cloud resource usage to optimize efficiency, discover unused and stranded resources, easily determine better pod limits and improved placement, understand your resource management policy imperfections, and decrease your carbon footprint
- Cost monitoring. You can gain better insight into your Kubernetes costs, spending trends, and potential savings with the cost monitoring feature, which is based on the open source project Opencost.
Grafana Kubernetes Monitoring in only available with an active Grafana Cloud License: https://grafana.com/products/cloud/ & https://grafana.com/pricing/
Highlights
- Get cost monitoring out of the box for no extra charge apart from the ingested metrics: https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring/navigate-k8s-monitoring/#analyze-costs
- Understand efficiency and resource use: https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring/navigate-k8s-monitoring/#understand-efficiency-and-resource-use
- Compatible with Otel Collector & deployable via Helm, Terraform, ArgoCD: https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring/configuration/configure-infrastructure-manually/
Details
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Supported services
Delivery option
Grafana Cloud Kubernetes Monitoring Add-on
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Operating system
Linux
Deployed on AWS
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Delivery details
Grafana Cloud Kubernetes Monitoring Add-on
Supported services: Learn more
- Amazon EKS
EKS add-on
An add-on is software that provides supporting operational capabilities to Kubernetes applications but isn't specific to the application. This includes software like observability agents or Kubernetes drivers that allow the cluster to interact with underlying AWS resources for networking, compute, and storage. Add-on software is typically built and maintained by the Kubernetes community, cloud providers like AWS, or third-party vendors. Amazon EKS add-ons provide installation and management of a curated set of add-ons for Amazon EKS clusters. All Amazon EKS add-ons include the latest security patches and bug fixes, and are validated by AWS to work with Amazon EKS. Amazon EKS add-ons allow you to consistently ensure that your Amazon EKS clusters are secure and stable and reduce the amount of work that you need to do to install, configure, and update add-ons.
Version release notes
v1 maintenance release. See the chart directory at this tag for the source.
Note: k8s-monitoring v1 is deprecated as of 2026-06-01. Please migrate to v4 (charts/k8s-monitoring).
Additional details
Usage instructions
Before deploying this Add-on, create a secret with this information:
apiVersion: v1 kind: Namespace metadata: name: monitoring
apiVersion: v1 kind: Secret metadata: name: grafana-cloud namespace: monitoring stringData: prometheus-host: <prometheus host> prometheus-username: <prometheus username> prometheus-password: <prometheus password> loki-host: <loki host> loki-username: <loki username> loki-password: <loki password> tempo-host: <tempo host> tempo-username: <tempo username> tempo-password: <tempo password>
For more information, see https://grafana.com/docs/grafana-cloud/monitor-infrastructure/kubernetes-monitoring/configuration/config-aws-eks/
Resources
Vendor resources
Support
Vendor support
Get support for Grafana Cloud and Grafana Cloud Kubernetes Monitoring:
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Customer reviews
German F.
Proactive, AI-Driven Cloud Monitoring with Grafana Labs
Reviewed on Sep 22, 2026
Review provided by G2
What do you like best about the product?
Grafana Labs enables me to proactively monitor my infrastructure through a cloud-based, AI-driven environment. I appreciate how it has evolved from a visibility system focused on tracking IT KPIs into a more AI-managed environment that supports ongoing monitoring and oversight.
What do you dislike about the product?
The most difficult part is establishing the necessary connections to monitor my local servers; it also requires creating very clear security policies to determine which traffic is permitted.
What problems is the product solving and how is that benefiting you?
It makes things easier for me to have a cloud-based Grafana environment, whereas I previously used it locally alongside another monitoring tool.
Computer Software
Powerful Custom Dashboards for Real-Time Metrics and Infrastructure Monitoring
Reviewed on Sep 21, 2026
Review provided by G2
What do you like best about the product?
Helps me in making of custom dashboards, helps us make centralized views of our infrastructure we use it to integrate with our product to show real time metrics, also internally we make dashboards to monitor the latency and detect and troubleshoot issues, lately the ai features also giving good boilerplate
What do you dislike about the product?
There are a lot of configuration options, and the learning curve was steep. It needs to be easier to learn and get started with. Troubleshooting can also be difficult, especially when trying to figure out whether the issue is with the tool or with our source query itself.
What problems is the product solving and how is that benefiting you?
It helps us monitor our infrastructure without needing to log in or SSH across different systems. We also use it to build real-time dashboards that help both our team and our customers visualize the metrics and properties we’re collecting, instead of having to check multiple systems.
Koli P.
My review about Grafana labs.
Reviewed on Sep 10, 2026
Review provided by G2
What do you like best about the product?
I like its clean UI, with dashboards, metrics, and logs. It makes it easy for me to track my work data and performance.
What do you dislike about the product?
I don’t like its pricing; they could make it more affordable for the features they’re offering.
What problems is the product solving and how is that benefiting you?
It helps me check my dashboards, metrics, and log files all in one place, instead of having to use multiple software tools.
Jaydeepkumar R.
Real-time visibility that makes root cause analysis so much faster
Reviewed on Sep 10, 2026
Review provided by G2
What do you like best about the product?
What really stands out to me is the level of visibility it provides into what’s actually happening behind the scenes during testing cycles. When I’m running automated test suites, being able to correlate test failures with real-time system metrics makes root-cause analysis much faster. I no longer have to dig through separate logs and monitoring tools—everything I need is visible in one dashboard. The alerting setup has also been a game-changer, helping me catch environment issues early before they derail an entire test run.
What do you dislike about the product?
Getting dashboards set up the way I actually want has taken more time than I expected, especially if you’re not already familiar with querying the underlying data sources. There’s definitely a learning curve if you’re coming from a testing background rather than a DevOps one, and it can take a while to get comfortable with how everything fits together.
What problems is the product solving and how is that benefiting you?
In the past, when a test failed intermittently, it took a lot of manual digging to figure out whether it was a real bug, a flaky test, or an environment issue. Now I can pull up system performance data right alongside the test execution results and spot patterns much faster—for example, noticing that a spike in failures lines up with a memory leak or a slow database query. It’s cut down on a lot of back-and-forth with the dev team, since I can actually show the data instead of just saying, “it failed again.” Overall, it’s made root cause analysis during regression cycles feel far less like guesswork.
Vikash K.
Great Visibility with Powerful Dashboards
Reviewed on Sep 10, 2026
Review provided by G2
What do you like best about the product?
As a backend engineer building an AI-driven insurance claims platform, I really value Grafana Labs' ability to aggregate metrics from our diverse tech stack. The custom dashboards we build are essential for tracking response times and visualising our system's performance. Being able to see container health, message queue depth, and model influence time all on one screen helps us identify bottlenecks in our microservices. Hooking Prometheus up to Grafana gave us clear panels to track latency percentiles and container RAM usage across the board. Grafana provides a unified telemetry layer that significantly reduces our mean time to detection, and the vendor-agnostic plugin ecosystem is a huge advantage for seamlessly connecting our software stack.
What do you dislike about the product?
The learning curve for LogQL is undeniably steep. It required a bit of learning to get the syntax right, so it wasn't just plug-and-play. There were some challenges, especially when it came to setting things up for the first time. But once I got a handle on it, things got better.
What problems is the product solving and how is that benefiting you?
In our claim categorisation system, Grafana Labs solves the issue of diving into isolated logs by providing a unified telemetry layer that drastically reduces our mean time to detection. It helps us pinpoint bottlenecks and track microservice performance, improving issue resolution before impacting our users.