Crystal-clear visibility into cloud spend at the workload and tenant level
- Days
- Time to first cost insights after install
- Days
- From install to powerful cost reporting
- Workload & tenant
- Granularity of cost visibility
Salt Security's event-driven architecture relied heavily on shared resources across machine learning, pipelines, and application layers. While DevOps had implemented customer tracing through observability tools, consolidating those signals into accurate cost metrics was difficult. Monitoring areas separately and inferring costs produced inaccuracies and inconsistencies. The CFO team needed precise cost data to measure margins and refine pricing, but manual methods could not keep up with the dynamic consumption patterns of Salt's infrastructure.
With Attribute™, Salt Security used its existing in-application identifiers, available at the payload level, to allocate customer costs within Kafka messages and other shared resources. Attribute™ integrated with zero changes to the system and zero tagging, consolidating cost insights across the platform. The result is a trusted, automated cost model that maps to Salt's architecture and gives DevOps and finance teams a shared view of customer-level costs, margins, and business performance.
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
Salt Security is a leader in API security. Its platform runs on a complex, event-driven architecture spanning EKS, Kafka, ElasticCache, MongoDB, Redis, SingleStore, and Glue, with shared resources across machine learning, data pipelines, and the core application.
Salt's DevOps team had instrumented customer tracing with observability tools, but turning that telemetry into reliable cost metrics was hard. Monitoring different areas separately and inferring costs produced inaccuracies. The CFO team needed precise, standardized cost data to measure margins and set pricing, and manual methods could not scale with Salt's dynamic, multi-tenant consumption patterns.
Salt Security adopted Attribute™ to automate customer cost allocation across shared resources. Attribute™ used Salt's existing in-application identifiers at the payload level to attribute costs inside Kafka messages and other shared components. Integration required no code changes and no tagging, and consolidated cost insights into one consistent model aligned with Salt's architecture.
With Attribute™, DevOps and finance now work from the same numbers. Customer-level costs are visible across all system components, giving the CFO clear insight into margins and business performance while giving engineering a trusted view of where spend is concentrated.
Standardized COGS measurement gave Salt a single source of truth for monthly business reviews. With full visibility into customer costs, the CFO can continuously refine pricing strategy to optimize margins and boost profitability. Communication between DevOps and finance became more efficient, accelerating decisions on pricing, packaging, and profitability.
By adopting Attribute™, Salt Security established an accurate, standardized COGS measurement system that aligns technical and financial teams. Optimizing customer cost allocation across its multi-tenant architecture improved internal collaboration, profitability, and competitiveness.
Explore how Attribute™ delivers runtime cost attribution without tagging, so teams can understand cost per workload, service, and customer.
Attribute™'s platform is truly unique. We now have crystal-clear visibility into our cloud spend at the workload and tenant level, and that insight has already led to actionable savings and powerful insights as we further scale our service.
Paul White, VP of Engineering, Shasta Cloud
We have worked with DoiT for many years, and there has been an increasing number of capabilities and features in DoiT Cloud Intelligence. We've embedded features such as Cloud Analytics and Reports in our own FinOps processes, it's become core to what we do.
Martin Lee, Director of Operations
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
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
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
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
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
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
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
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
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
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
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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