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Turning cloud costs into team action at Hippo

How Hippo built business unit accountability and empowered engineers to own their cloud spend with Attribute™.

The Challenge

Hippo's cloud teams needed to efficiently own and manage cloud spend across a complex AWS footprint spanning ECS, EKS, RDS, and S3. They lacked cost attribution by business unit, leaving engineering teams without the insights needed to allocate spend or understand microservice cost drivers. Manual tagging stretched engineering thin and still left blind spots, making it difficult to promote cost consciousness, drive accountability, or give management a clear view of cloud efficiency.

The Solution

After evaluating multiple approaches, Hippo selected Attribute™ for its granular cost attribution capabilities. Attribute™ integrated seamlessly with Hippo's AWS infrastructure in minutes, eliminating the need for extensive tagging. The platform surfaced cost insights by business unit, service, and shared resource, with an accountability index identifying primary contributors to each resource cost. Hippo's engineering leaders and service owners gained the contextual consumption data needed to align cloud spend with team usage and profit margins.

Results

Increased team accountability with clear insight into each team's cost contributions, fostering a culture of cost efficiency.
Enhanced engineering engagement by giving service owners detailed, contextual consumption data to proactively track and manage resources.
Improved cost attribution with simple breakdowns of service costs, including shared resource allocation and an accountability index for primary contributors.

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

About Hippo

Hippo is a property insurance company specializing in homeowner's insurance, providing comprehensive coverage for homes, possessions, and liability. Leveraging AI and big data, Hippo aggregates and analyzes property information to offer tailored insurance solutions. The company distributes policies directly to consumers and through independent insurance brokers. Its cloud architecture relies on ECS and EKS for container orchestration, Apache Airflow for workflow automation, RDS for databases, and cross-account S3 for storage.

The challenge: cost transparency and team accountability

Hippo's cloud teams needed to efficiently own and manage cloud spend while driving high team accountability. They wanted to promote cost consciousness among engineers, motivate proactive optimization, and simplify management oversight. Two specific gaps stood out: cost attribution by business unit, which was missing for spend allocation, and microservice cost structure, which service owners needed to understand cost drivers and make informed decisions. Achieving this without compromising operational agility required a more granular approach than tagging alone could deliver.

Solution discovery

Hippo explored several strategies but lacked the data and insights to drive impactful change. Deep, granular visibility into cloud costs was missing, and manual tagging stretched engineering teams thin while still leaving blind spots. Engineering leadership refused to compromise on cost-attribution requirements. After being introduced to Attribute™, Hippo recognized the right fit and implemented the platform. Attribute™ integrated seamlessly with Hippo's AWS infrastructure and delivered the missing granular insights to align cloud spend with team usage and profit margins.

Phase I results

With Attribute™ in place, Hippo realized three key outcomes. Teams gained clear insights into their cost contributions, building a culture of accountability and efficiency. Service owners gained detailed, contextual consumption information to proactively manage their resources. And Hippo achieved clear breakdowns of service costs, including shared resource attribution and an accountability index that highlights primary contributors to each resource cost.

Phase II plans

Hippo plans to deepen its cost management practices by embedding Attribute™ into engineering workflows and proactively eliminating inefficiencies. As Eli Zilbershtein, Head of DevOps, summarized: "Attribute™ helped us clear the cloud spend blind spots we had in our complex cloud architecture."

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What they say

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

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

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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