Read-Only vs Write-Access Cloud Cost Tools: What to Grant a Vendor

A read-only cloud cost tool can see your billing and usage data but cannot start, stop, resize, or delete a single resource, while a write-access tool holds permissions to change your infrastructure directly. Read-only is the safer default and covers everything most finance and platform teams need: visibility, allocation, savings recommendations, and anomaly alerts. Write access is only worth granting when you specifically want a vendor to automate changes, such as rightsizing Kubernetes pods, and it carries a much larger blast radius if something goes wrong. The right question is not which is better, it is how much you actually need the tool to do on your behalf.

Cloud cost tooling is one of the few categories where you hand a third party a key to your production account. It is worth being deliberate about which key you hand over.

What is the difference between read-only and write access?

Read-only access grants a tool permission to view resources and billing data without the ability to modify anything. Write access, sometimes called read-write or management access, grants permission to create, change, or delete resources. In AWS terms, a read-only role is built from policies like ViewOnlyAccess and Cost Explorer read permissions, while a write role includes actions like ec2:TerminateInstances or ec2:ModifyInstanceAttribute.

The line matters because a read-only integration cannot cause an outage. The worst case for a read-only tool is a data exposure, which is serious but recoverable. The worst case for a write-access tool is that a bug, a bad heuristic, or a compromised vendor changes or removes a resource your business depends on. Those are different orders of risk, and they deserve different levels of scrutiny.

Does a cloud cost management tool need write access?

No. The core work of cloud cost management, showing where the money goes, attributing it to owners, catching spend spikes, and telling you exactly what to cut in dollars, is entirely a read operation. A tool that only reports and recommends never needs to touch a resource, because the change is executed by your own engineers through your normal deployment process. This is how most cost platforms operate, and it is why cloud waste detection and cost allocation work perfectly well against read-only billing and usage data.

Write access enters the picture only for one category of product: automation tools that change your infrastructure for you. The most common example is Kubernetes optimization, where a platform continuously rightsizes pods, bin-packs nodes, and swaps in cheaper instance types. That automation is genuinely valuable if you want it, and it is impossible without write permissions. But it is a distinct decision from cost visibility, and you should not grant write access just because a tool bundles reporting with automation you may not use.

When is it worth granting write access?

Granting write access is worth it when the value of hands-off automation outweighs the loss of a human in the loop, which is usually true for large, fast-changing Kubernetes fleets where manual rightsizing cannot keep up. If your workloads scale up and down hourly and no engineer can retune requests and limits fast enough, an automation platform that acts in real time will save more than a recommendation you act on next sprint. That is the honest case for tools like CAST AI.

It is not worth it when your infrastructure is relatively stable, when you have change-management or compliance requirements that need approval before anything changes, or when the savings are the kind you can capture in a scheduled maintenance window anyway. In those situations you get most of the benefit from a read-only tool that names the savings, and your team keeps control of the change. We lay out that specific tradeoff in more detail in our Costanalyst vs CAST AI comparison.

What permissions should you actually grant?

Grant the narrowest role that lets the tool do its job, and read the policy document before you approve it rather than accepting a default. For a read-only cost tool on AWS, that means a cross-account IAM role scoped to billing, Cost Explorer, and resource-describe actions, with an external ID to prevent confused-deputy attacks. On Azure it means a Reader or Cost Management Reader role at the subscription or management-group level. On Google Cloud it means the Billing Account Viewer and Viewer roles.

Whatever the vendor asks for, apply the same discipline you would to any integration that reaches into a production system: scope the permission to exactly what the feature needs, and enforce that boundary rather than trusting it. The same principle now applies to the wave of AI tools connecting to internal systems, where controlling exactly which tools and data an automated system can touch is the difference between a useful integration and an open door. Cost tooling was doing this before it was fashionable, and the checklist is the same.

• Prefer a role over a key. A cross-account role you can revoke instantly beats a long-lived access key sitting in a vendor's database.
• Require an external ID on AWS roles so the trust relationship cannot be assumed by another customer of the same vendor.
• Scope to the account or subscription the tool needs, not the whole organization, unless you genuinely want org-wide visibility.
• Log the role's activity through CloudTrail or the equivalent, so you can see exactly what the tool read and when.
• Revisit at renewal. Permissions granted for a trial often outlive the trial. Re-check what each vendor can still access.

Is a read-only tool safe to connect to a production account?

Yes, a properly scoped read-only tool is safe to connect to production, because it cannot change or delete anything, and its access is limited to billing and usage metadata rather than the contents of your databases or storage. The residual risk is that the spend data itself is sensitive, since it can reveal architecture, scale, and vendor relationships. That risk is managed the same way you manage any data-sharing arrangement: scope the access, log it, and confirm the vendor's own security posture.

Costanalyst is read-only by design. It connects to AWS, GCP, and Azure billing and to your SaaS subscriptions, reports savings as dollar figures with the line items behind them, and watches for anomalies, and it never starts, stops, or changes a resource or moves a cent. That posture is a deliberate choice, because for the job most finance and platform teams are actually trying to do, there is nothing to gain from write access and a lot to protect by not having it.

How do you decide between the two?

Start from what you want to happen after the tool finds a saving. If the answer is "an engineer reviews it and makes the change on our schedule," you want a read-only tool, and granting more access buys you nothing. If the answer is "the system should just do it, continuously, faster than a human could," and you are comfortable with a vendor holding the keys to act, then a write-access automation tool is the right pick for that specific workload.

Many teams end up running both: a read-only analyst for the whole cloud and SaaS bill that finance signs off on, plus a narrowly scoped automation tool inside the one system, usually Kubernetes, where continuous automation pays for itself. What you should avoid is granting broad write access by default, to a general-purpose tool, for a job that never required it. When you are ready to see your spend without handing over control, you can connect your cloud and SaaS accounts read-only and have the savings named in dollars.