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Claroty unlocks precise customer cost attribution with Attribute™

Real-time, transaction-level visibility across a complex multi-tenant SaaS architecture, with zero disruption to operations.

Cloud Intelligence™
Claroty

The Challenge

Claroty's SaaS platform runs on a complex, multi-tenant architecture powered by Kubernetes, Apache Kafka, Apache Spark, and many other technologies. Shared resources across services made customer-level cost visibility extremely difficult. Manual tagging and internal tooling were impractical given limited engineering and DevOps bandwidth. After evaluating multiple external and in-house options, Claroty's Center of Cloud Excellence found no solution that delivered the required granularity, scalability, and cost efficiency.

The Solution

Attribute™ deployed seamlessly across Claroty's production regions, spanning multiple Kubernetes clusters, hundreds of nodes, and thousands of vCPUs. Its eBPF-based sensor captured real-time, transaction-level data and identified customer-specific resource usage across Kafka message streams, RDS database queries, and S3 storage operations. Within days, Claroty received granular reports attributing precise costs to each customer interaction across regions.

Results

  • Granular visibility into resource usage per customer across all regions.
  • Clearer insights into customer profiles, profitable verticals, and high-cost users.
  • Improved forecasting accuracy and optimized budgeting for production infrastructure.
  • Refined customer targeting strategy informed by accurate cost and usage data.
  • Fast, seamless deployment with zero disruption to ongoing operations.

Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.

Jonathan Langer, COO, Claroty

Goal

As Claroty's customer base and cloud operations expanded rapidly, the company embarked on a multi-year journey to refine its cloud cost management strategy. After achieving cost allocation, chargeback, and basic forecasting, leadership sought to align cloud cost metrics with business growth. In a fiercely competitive market, Claroty needed deep insights into gross margin, profitability, and cost efficiency for each customer, region, and customer profile.

Implementation

Attribute™'s technology deployed seamlessly across Claroty's production regions, each containing multiple Kubernetes clusters, hundreds of nodes, and thousands of vCPUs. Implementation was fast and required minimal intervention from the DevOps team, ensuring zero disruption to ongoing operations. Attribute™'s eBPF-based sensor captured real-time, transaction-level data and identified customer-specific usage across Kafka, RDS, and S3 components.

Future plans

Claroty plans to deepen its partnership with Attribute™, using the platform to refine cost attribution down to individual customer actions and feature usage. With this level of insight, Claroty aims to forecast profitability more accurately, identify efficiency opportunities, and drive strategic initiatives that improve customer satisfaction and operational efficiency.

See how Attribute™ reveals the hidden profit in your cloud spend

Explore how Attribute™ delivers runtime cost attribution without tagging, so teams can understand cost per workload, service, and customer.

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What they say

Finlex

DoiT gave us the confidence to move from experimentation to production. They helped us understand the right way to build AI for the real world.

Milad Rezazadeh, CTO

Hippo

Attribute™'s cost grouping technology took our cost visibility and allocation to a whole new level. Now, our teams are fully accountable for their budgets, significantly improving our cloud efficiency and helping us minimize unnecessary costs.

Eli Zilbershtein, Head of DevOps, Hippo

Island

You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.

Omri Cohen, Director of Engineering, Platform

Claroty

Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.

Jonathan Langer, COO, Claroty

Salt Security

Attribute™ simplified tracking customer costs in our multi-tenant environments. Customer cost measurement is now clear and standardized, and finance gets the business context they need. Integration was quick and required no changes.

Kfir Lippmann, CFO, Salt Security

PropertyGuru

Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.

Balamurugan Mohandossgandhi, Head of IT and Infrastructure, PropertyGuru

Accrete AI

This has let us get a better idea of what our cost of goods sold really is. It's not every day you come across something that delivers value as quickly as yours did for us. I was seeing useful insights inside the POC, and we had only deployed it to a couple of real clusters.

Jason Moore, Principal DevOps Engineer, Accrete AI

Akamai

Eliminating the need to tag thousands of resources has freed up my team and we've invested our efforts in enhancing our platform significantly.

Ziv Sivan, VP of Engineering

OneFootball

PerfectScale by DoiT has become an important part of how we optimize Kubernetes at scale at OneFootball. It gives our platform team the visibility, automation, resiliency insights, and confidence we need to balance cost efficiency with production readiness, especially as we prepare for major global football moments like the 2026 FIFA World Cup.

Andrea Benfatto, Platform/Cloud Runtime Engineering Manager

Raptive

Cloudflow's new RDS End of Life alerts have allowed us to be more proactive on keeping our database instances up-to-date. The new solution gives us internal visibility ahead of time so that we can prepare for upgrades, instead of having to upgrade under pressure while incurring extended support costs.

Jon Fairbanks, Site Reliability Engineering Manager

Luma Health

PerfectScale cut 40% off our total EKS spend, and the automations handle what used to take our team 20 hours a month. Now we spend that time on reliability and performance instead of chasing cost metrics.

Caio Cristo, Director of Infrastructure/SRE

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What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.

Chiamaka Ibeme, Engineering Manager, Platform

Personio

SELECT has made important cost data readily accessible. I will often pull it up during engineering design reviews so we can quickly evaluate cost impact and projections and factor that into our design decisions.

Douglas Zickuhr, Senior Data Platform Engineer at Personio

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