Finout Reviews

Our primary use case for Finout is centralized cloud cost governance, granular Kubernetes cost allocation down to the pod and namespace level, and merging our AWS infrastructure cost with third-party SaaS spending into a single pane of glass.

We operate a multi-tenant AWS EKS environment where microservices share underlying EC2 node groups, and before Finout, AWS Cost Explorer would only give us a lump-sum bill for our EC2 instance, making it impossible to know how much individual product teams or specific clients were costing us. With Finout, we integrated our EKS metrics, allowing us to accurately attribute shared container cost by namespace. We even mapped our DataDog logging cost directly to those namespaces inside Finout. This gave us an exact, unified cost per tenant without tedious manual spreadsheet math.

The best features Finout offers, in my experience, would be MegaBill, Virtual Tagging, Kubernetes cost allocation, cost anomaly detection, and custom dashboards.

Out of those features, we rely the majority on MegaBill because it provides combining multiple cloud providers and SaaS tools into one consolidated dashboard. Also, Virtual Tagging, the ability to logically group and tag resources inside the same Finout UI without having to constantly modify and redeploy our Terraform code.

Finout has positively impacted our organization by fostering a true FinOps culture across our engineering teams, as it removed the guesswork from cost attribution, automated our monthly financial reporting, and highlighted exactly where we were overprovisioning third-party tools.

We have achieved a twenty to thirty percent reduction in total cloud and SaaS waste by identifying orphaned resources and optimizing underlying third-party licenses, and we also saved hours of engineering time previously spent manually building cost allocation spreadsheets every month.

While the visibility features are top-notch, I would like to see more actionable, automated cost optimization recommendations, and I would also love to see more advanced cost forecasting models.

Finout is exceptionally strong for observability and reporting, and most desired improvements are centered on adding more active, automated infrastructure optimization features.

More out-of-the-box native integration for mid-tier SaaS tooling would be great.

We have been using Finout for about a year.

Finout is highly stable.

Finout's scalability is excellent, as it easily ingests massive, complex billing data streams and seamlessly handles the scale of our expanding EKS environment.

Finout's customer support team is responsive and highly technical, and they were particularly helpful when we were setting up our initial EKS cost allocation rules.

I would rate the customer support eight out of ten.

We were using AWS Cost Explorer coupled with manual spreadsheets, so we moved to Finout.

The initial onboarding and setup were very quick because it relies primarily on API connection and cloud reports, and pricing is tied to your total monitored cloud spend, so it is reasonable.

Do not let physical infrastructure tags stall your FinOps; use Finout's business mapping layers to organize your cost.

We got the ROI in about two to three months when the anomaly detection and Virtual Tagging flagged several unmapped ideal resources over our over-scaled SaaS commitments.

We evaluated native AWS tools and a few legacy cloud cost platforms, and we selected Finout because it blends container metrics with third-party SaaS cost.

We heavily rely on Finout to democratize cost data, as it allows our finance team and engineering managers to log into the same platform and see identical, clear metrics without requiring finance to understand AWS console architectures.

Finout's governance capabilities are very solid, as Virtual Tagging rules allow us to enforce strict cost boundaries. From a security standpoint, it connects using secure, read-only IAM roles and digests AWS Cost and Usage Reports, meaning it does not pose an operational risk to our live application environments.

The data reconciliation is highly accurate, and once the Virtual Tagging logic is set up correctly, numbers match up perfectly.

Finout is a SaaS platform we have integrated via read-only, cross-account IAM roles for AWS, alongside an open-source agent Prometheus connection to securely scrape our EKS cluster metrics.

We purchased Finout through the AWS Marketplace. I would rate Finout an overall eight out of ten.

Public Cloud

Amazon Web Services (AWS)

Our main use case for Finout is centralized cloud cost governance, granular Kubernetes cost allocation down to pod and namespace level, and merging our AWS infrastructure cost with third-party SaaS spend like DataDog into a single pane of glass.

We operate a multi-tenant AWS EKS environment where microservices share underlying EC2 node groups. Before Finout, AWS Cost Explorer would give us a lump sum bill for our EC2 instance, making it impossible to know how much individual product teams or specific clients were costing. With Finout, we integrated our EKS metrics, allowing us to accurately attribute shared container cost by namespace. Even better, we mapped our DataDog logging cost directly to those same microservices inside Finout. They gave us an exact, unified cost per tenant without tedious manual spreadsheet math.

Finout has positively impacted our organization by fostering a true FinOps culture across our engineering teams. It removed the guesswork from cost attribution, automated our monthly financial reporting, and highlighted exactly where we were over-provisioning third-party tools.

We have achieved a twenty to thirty percent reduction in total cloud and SaaS waste by identifying orphan resources and optimizing underutilized third-party licenses. We also saved hours of engineering time previously spent manually building cost allocation spreadsheets every month.

The best features in my experience with Finout are the MegaBill, combining multiple cloud providers and SaaS tools into the consolidated dashboard. Virtual Tagging, Kubernetes cost allocation, cost anomaly detection, and custom dashboards are all valuable features.

Virtual Tagging paired with the MegaBill concept completely resolved our historic tagging gaps. If a legacy resource lacks physical AWS tags, we can virtually tag it in seconds inside Finout to fix our cost attribution immediately.

The governance capabilities of Finout are very solid. Virtual tagging rules allow us to enforce strict cost boundaries. From a security standpoint, it connects using secure, read-only IAM roles and digests AWS cost and usage reports, meaning it does not pose an operational risk to our live application environments.

While its visibility features are top-tier, I would appreciate seeing more actionable, automated remediations and guardrails similar to tools that can actively scale down infrastructure automatically. Rather than just alerting us to do it manually, I would also welcome deeper machine learning forecasting models for long-term budget.

More out-of-the-box native integration for mid-tier SaaS tooling would be a great addition to Finout's existing high-hitter integrations.

The platform is exceptionally strong for observability and reporting. Most desired improvements are centered on adding more active, automated infrastructure optimization features.

I have been using Finout for more than a year.

Finout is highly stable since it processes data asynchronously from our cloud billing reports. It has zero impact on our live production workloads.

Finout's scalability is excellent. It easily ingests massive, complex billing data streams and seamlessly handles the scale of our expanding EKS environments.

The customer support team for Finout is responsive and highly technical. They were particularly helpful when we were setting up our initial EKS cost allocation rules.

Before Finout, we relied entirely on native AWS Cost Explorer, coupled with manual spreadsheet tracking and custom internal Grafana dashboards.

The initial onboarding and setup for Finout were quick because it relies primarily on API connections and cloud reports. The pricing is tied to your total monitoring cloud spend and is reasonable given the deep level of visibility and waste reduction it enables.

We integrated it via read-only, cross-account IAM roles for AWS alongside an open-source agent Prometheus connection to securely scrape our EKS cluster metrics.

The ROI for Finout was clear within the first sixty days when the anomaly detection and virtual tagging flagged several unmapped, ideal resources and overscoped SaaS commitments that we were able to clean up immediately.

We evaluated native AWS tools and a few legacy cloud cost platforms before choosing Finout. We selected Finout because it uniquely blends container metrics with third-party SaaS costs, whereas most alternatives only look at core cloud infrastructure.

I advise others looking into using Finout to take full advantage of the virtual tagging engine early on. Do not let imperfect physical infrastructure tags stall your FinOps journey. Use Finout's business mapping layers to organize your costs logically from day one.

If your team is struggling to piece together a clear financial picture across Kubernetes and external tools like DataDog, Finout is a fantastic choice. It bridges the communication gap between the DevOps team and finance effortlessly.

I give this product an overall rating of eight.

Public Cloud

Amazon Web Services (AWS)

Our use case is integrating cloud costs from a multi-cloud estate to have one pane of glass for cost visibility. We use it for reports, but there's also other functionality that we've liked using, such as anomaly alerts, looking at the asset inventory, and setting budgets for different cloud accounts.

I like the virtual tags feature of Finout, which is like business mappings within Cloudability, which is one of their competitors. Virtual tags work really well because you can specify them without changing the configuration of cloud accounts directly. It's a filtering mechanism that's specifically within Finout and can be fully managed there.

It makes it easier to group cloud accounts into a specific bucket. For example, an engineering team might own five different cloud accounts. Rather than them having to change their code to tag them all to their team, we can instead use the virtual tags feature within Finout to have a layer of abstraction over the top. This makes it easier and allows us to manage it, rather than having to burden engineers to manage the tags of their own accounts.

Finout, being a FinOps tool, leads to cost reductions within cloud spend, which is great. By looking at how much cost is spent over time, you can then figure out different areas to reduce your cost and make it more efficient. We've definitely found that from our FinOps tool usage.

From using the cost anomaly feature, you can very quickly see when costs are getting out of control. We've used cost anomaly alerts in our FinOps tools to look for costs that are too high and then make sure that they can be reduced. There have been situations where costs get out of control, we use that feature, and then we're able to cut them down. By using that, you can definitely cut down anomalous costs by anywhere from twenty to fifty percent if you catch it quickly enough.

In terms of money saved, organizations could very easily save anywhere from ten to thirty percent of their cloud costs. That's through anomaly alerts, detecting costs that are getting too high and making sure that they're controlled, building out reports and dashboards to track costs and make them more efficient, and then potentially using the reservations and right sizing features to directly reduce cost.

The right sizing feature is okay. It could be used, but I feel its functionality isn't as strong as the cloud-native solutions, so GCP, AWS, and Azure. They all have better right sizing capabilities, so you probably wouldn't carry out right sizing from Finout. You'd want to do it directly in the cloud platforms.

The right sizing feature needs more development. Also, the reservations analysis feature isn't quite detailed enough as it should be. If you're making purchasing decisions based off of a cloud tool, it's probably better right now to do it directly through the cloud-native tooling rather than through Finout.

Those are the two features where I feel they could be improved. It's a great tool, but it does have those two areas of improvement in the right sizing and the reservation sections. If those sections were functioning very well and were very deep, then I would give it a ten out of ten.

I've used Finout over the last two years.

Finout is very stable. I've not noticed any issues with it.

Finout is very scalable. If an organization had hundreds of cloud accounts or thousands, it would easily scale to that, so there would be no scalability issues.

The people I've interacted with from Finout have been very helpful.

Positive

I've used other cloud FinOps solutions before, for example, using GCP, AWS, and Azure's integrated FinOps tooling. Those have been good tools. The reason for using Finout is having all costs from different cloud providers into one platform is highly beneficial.

Finout was being compared directly against the cloud provider integrated tooling, so that's GCP, AWS, and Azure.

Interactions have been directly with the vendor rather than through the marketplace.

I would recommend them to use it. It's a good tool. The company is still quite new and young, but they're rapidly developing, and their support is great.

The Finout team seemed like they could be flexible on the pricing, which is good. No complaints there. They were quite interested in securing new business while not overwhelming the customer with cost. Because they're a newer and smaller FinOps company, they're more interested in getting customers on board rather than charging high costs, which is good for customers. I would give this product a rating of nine out of ten.

Public Cloud

Google

Finout serves as our primary solution for centralized log and cloud cost governance, providing granular Kubernetes cost allocation down to the pod namespace level and merging our AWS infrastructure cost with third-party spend into a single pane of glass.

We operate a multi-tenant AWS EKS environment where microservices share underlying EC2 node groups. Before Finout, AWS Cost Explorer would only provide us with a lump sum bill for our EC2 instance, making it impossible to know how much individual product teams or specific clients were costing us. Finout allows us to integrate our EKS metrics so we can accurately attribute shared container cost by namespace. Furthermore, we have mapped our Datadog logging cost directly to those same microservices inside Finout, giving us an exact unified cost per tenant without tedious manual spreadsheet math.

We rely heavily on Finout to democratize cost data. It allows our finance team and engineering managers to log into the same platform and see identical clear metrics without requiring finance to understand all AWS console architecture.

Finout's best features are megabill, virtual tagging, Kubernetes cost allocation, cost anomaly detection, and custom dashboard.

Azure tagging paired with the megabill concept completely resolved our historic tracking issues with our apps. If a legacy resource like a physical AWS is tagged, we can virtually tag it in seconds inside Finout to fix our cost attribution immediately.

Finout has positively impacted our organization by fostering a true FinOps culture across our engineering teams. It removed the guesswork from cost attribution, automated our monthly financial reporting, and highlighted exactly where we were over provisioning third-party resources.

We achieved approximately thirty to forty percent reduction in total cloud and SaaS waste by identifying orphan resources and optimizing underutilized third-party licenses. We also saved hours of engineering time previously spent manually building cost allocation spreadsheets every month.

Visibility features are top tier, but I would like to see some more actionable automated remediation guardrails similar to tools that can actively scale down infrastructure rather than just alerting us to do it manually. I would also welcome deeper machine learning forecasting models for long-term budget planning.

Finout's platform is exceptionally strong for observability and reporting, and the most desired improvements are centered on adding more active automated infrastructure optimization features.

We have been using Finout for more than a year to manage our cloud costs effectively.

Governance capabilities are very solid, and virtual tagging rules allow us to enforce strict cost boundaries. From a security standpoint, Finout connects using a secure read-only IAM role and then digests AWS cost and research reports, meaning it does not pose an operational risk to our live application environments.

Data reconciliation is highly accurate, and once the virtual tagging logic is set up correctly, the numbers match up perfectly with our AWS invoices.

Out of the box native integrations for mid-tier SaaS tooling would be a great addition to Finout's existing AVIATOR integrations.

If your team is struggling to piece together a clear financial picture across Kubernetes and external tools, Finout is a fantastic choice. I would rate this product a nine out of ten.

Public Cloud

Amazon Web Services (AWS)