New Relic solved the problem of billing per host and created two new ones. One is that in Kubernetes ingested GBs grow without anyone deciding to. The other, more expensive, is that the price of a seat decides who is allowed to look during an incident.
New Relic bills for two things at once. The first is data coming in: the first 100 GB per month are free, and beyond that it is USD 0.40 per GB on the standard option or USD 0.60 per GB on Data Plus, which adds longer retention and some capabilities.
The second is users. Basic users cost nothing but can only look. A full platform user — the one who can actually investigate — runs from USD 10 per month on Standard to USD 349 per month on Pro with an annual commitment.
Publishing the prices is a real merit and worth saying: you can do the maths before signing, which is not always the case in this market. The problem is not transparency, it is what those two axes do in Kubernetes.
A hundred free gigabytes sounds like a lot. A Kubernetes cluster with the Prometheus exporters installed as they ship consumes it in days, and not because of logs.
The reason is the number of distinct metrics. Every label combination counts as a separate series, and labels accumulate: service name, namespace, version, node, response code. One metric with four labels of ten possible values each is ten thousand series, and each one reports its value every few seconds.
Adding a pod identifier to a metric that already had three labels multiplies the total by the pod count — a number that in Kubernetes changes on its own, without anyone approving it.
So the axis that drives the bill is not your user traffic or the size of your business. It is a configuration decision someone made to debug something months ago and nobody reverted.
At USD 349 per seat per month on Pro, a ten-person platform team is USD 41,880 a year in access permissions alone. And that figure grows with hiring, not with usage.
The consequence shows up on call. When full seats are expensive they get rationed, and then the person on duty at three in the morning may not have the seat they need to investigate. They have to wake up someone who does.
That cost appears on no invoice, but it is what stretches incidents out: time to resolution stops depending on the tool and starts depending on who got the licence.
It is also the hardest spend to cut, because cutting it means taking access away from someone who was using it.
Moonin does not bill per seat. The price depends on cluster size, so whoever needs to look, looks — including the person on duty at three in the morning. That is what it replaces in the New Relic model, and it is not a pricing detail: it is an operational difference.
On data, Moonin does not compete on volume. It answers two questions: what changed in the cluster and what broke afterwards. For that it keeps a resource inventory, a revision history per service with image and commit, DORA metrics computed from that history, and service-to-service traces with eBPF, without instrumenting code.
What it does not do: it is not an instrumented APM, it has no dashboard engine for arbitrary charts, and it does not ingest or search logs at scale. If the value you get from New Relic is NRQL queries over your own business data, that is not replaced.
If you use New Relic as a telemetry database — sending your own application events and querying them with NRQL to answer business questions — that is a legitimate use case and Moonin does not cover it. It is not a general-purpose data platform.
If your team is small and fits in the free tier, there is nothing to optimise. A hundred gigabytes and one free full seat are enough for a modest cluster, and competing with free makes no sense.
And if the real problem is that nobody cleaned up cardinality, switching tools hides it instead of fixing it. Dropping unnecessary labels reduces a New Relic bill without migrating anything, and it is worth trying first.
Moonin bills for the size of what you are running: one Compute Unit is 1 vCPU or 2 GB of RAM, and the larger dimension is billed, never the sum. A cluster with 120 vCPU and 180 GB of RAM pays for 120 units, because 120 vCPU beats 90 RAM units.
The price drops in tiers, and each tier is billed at its own rate: the first 100 units at USD 20, units 101 to 250 at USD 18, units 251 to 500 at USD 15, and above 500 negotiated. A 300-unit cluster pays 100 × 20 plus 150 × 18 plus 50 × 15, which is USD 5,450 per month.
What that number does not include is a per-person charge. Ten engineers or forty cost the same, because what is billed is the infrastructure observed, not access permissions.
And it does not depend on how much data your metrics generate, so adding a label to debug something has no consequence on the bill.
Install the Moonin chart on one cluster and leave it running in parallel for two or three weeks without turning anything off. Access to the Kubernetes API is read-only and does not interfere with the New Relic agent.
Then look at your New Relic usage summary and separate two things: how many GB come from cluster infrastructure metrics, and how many from your own application data. The first part is what a deployment history usually makes redundant; the second is not.
With that you can decide concretely which integrations to turn off and how many full seats you actually need, instead of negotiating blind at renewal.
Two numbers say almost everything: how many GB you ingest per month and how many full seats you are paying for. If the second number made you ration access, there is something to fix there.
About usPricingSecurity and permissionsPartner programmevs Datadogvs Prometheus & Grafanavs New Relicvs Dynatracevs ELK and ElasticsearchCrashLoopBackOffOOMKilledImagePullBackOffPod stuck in PendingDocumentationDemoSign upContact usArguz, the consultancy
No. It replaces the part that answers what changed in the cluster and what broke afterwards, and it removes the per-seat charge. It does not replace an instrumented APM, NRQL queries over your own application data, or log ingestion at scale.
Almost never because of logs. It is the number of distinct metrics: every label combination counts as a separate series and reports its value every few seconds. Prometheus exporters, installed as they ship, produce tens of thousands of series in a single cluster. Adding a pod-identifier label multiplies the total by the pod count.
Depending on the plan, from USD 10 per month on Standard to USD 349 per month on Pro with an annual commitment, per prices published by New Relic in September 2026. Basic users are free but can only look, not investigate. Check the current figure before deciding, because these prices change.
No. The price depends on cluster size, not on how many people log in. Ten engineers or forty cost the same. That matters more on call than on the invoice: the person on duty at three in the morning does not need to borrow anyone else access.
Yes, and it is worth trying before switching tools. Lowering cardinality — dropping labels nobody queries, especially those with one value per pod — reduces ingested GB directly. If that brings you back under budget, migrating solves nothing you have not already solved.