Finlex cuts cloud costs 50% and ships production AI with DoiT
- Over 65%
- reduction in cloud infrastructure costs from 2024 - present
- 40%
- cost savings achieved through improved visibility and efficient AI architecture
Cloudify provides customers with cloud orchestration and end-to-end network automation, extending their network and application services from their core location and making them accessible across branches and multi-access edge devices. The product works across public, private, hybrid and multi-cloud environments, automating DevOps operations and supporting cloud migration efforts.
Cloudify's SaaS product requires significant compute resources for complex engineering development. As an early-stage startup, they needed to guard limited resources carefully while avoiding over- or under-provisioning. Commitment-based discounts required accurate forecasting over 1-3 year terms, which was difficult for their varied usage patterns. Manual management of compute discounts meant they didn't always get maximum value from their efforts.
Cloudify implemented Flexsave for Compute to automatically cover on-demand workloads in their AWS environment with rates equivalent to 1-year commitment discounts. This eliminated the need for manual forecasting and commitment management while providing flexibility for their development team to spin up instances as needed.
Flexsave for Compute really does the magic that we need by analyzing and covering our on-demand workloads. That helps us a lot because we can get those savings without all the manual effort we were doing before. We get a great cost reduction without any time consumption.
Yuval Rapaport, DevOps Engineer, Cloudify
Cloudify's team structure is especially suited to this kind of flexibility of compute resources. At Cloudify, each developer and customer success manager has the autonomy to spin up new instances as needed, because they are able to operate quickly and independently without needing to worry about the expense of on-demand workloads.
As Cloudify grows their product portfolio and therefore their underlying cloud needs, Flexsave for Compute will continue to help keep their cloud costs optimized and automated.
Explore how DoiT Cloud Intelligence helps teams improve visibility, governance, and unit economics across cloud environments.
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.
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Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.
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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
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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.
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