Company
Genial Investimentos is one of the leading investment platforms in Brazil that offers comprehensive solutions for customers seeking security, profitability, and innovation in the financial market. With an investor-centric approach, the company stands out for its advanced technology, specialized services, and wide range of financial products.
Challenge
Genial Investimentos experienced rapid growth and a sharp increase in its customer base, which brought new challenges – most notably, rising cloud computing costs. At the same time, the company’s expanding Kubernetes footprint created an urgent need for a robust and reliable container security solution.
Solution
To tackle rising cloud costs, Genial Investimentos adopted a structured FinOps approach, ultimately selecting Cast AI as the ideal partner to meet its optimization goals.
A key differentiator was Cast’s ability to automate Kubernetes management. With features like node scaling, rebalancing, and bin-packing, the platform ensures that Genial’s rapid growth doesn’t compromise financial efficiency.
On the security front, Cast’s integrated automation has significantly strengthened Genial’s container security posture. With continuous visibility, real-time vulnerability detection, and streamlined reporting, the security team can act proactively—eliminating the need for multiple standalone tools.
Results
- ~50% cost savings in the cloud
- Dramatically improved resource allocation efficiency
- Deep cost visibility across all clusters
By implementing Cast, Genial Investimentos strengthened its FinOps strategy, ensuring greater cost visibility and continuous optimization of cloud resources.
Cast’s automation empowers the team to intelligently optimize cloud resources, delivering scalability and stability without waste. This directly translates into a better customer experience, supported by a robust, resilient, and cost-efficient infrastructure.
Scheduled rebalancing
The solution maintains optimal compute cost by running a scheduled rebalancing job every night. During a rebalancing operation, Cast groups workloads onto fewer nodes and moves them to more cost-effective compute resources.
Cost savings achieved through scheduled rebalancing
Example of a rebalancing operation
Spot Instance automation
Cast automates the entire Spot Instance lifecycle, from selection and provisioning to scaling in line with real-time workload demand.
The impact of automated Spot Instance scaling
Tangible cluster cost savings
Cluster 1: ~40% average cost savings on Production cluster
Using Cast’s automation, Genial Investimentos was able to save around 40% on its production cluster, with the average cost per CPU dropping from $5.88 to $5.40.
Cluster 2: ~80% average cost savings
In this scenario, Cast reduced the cluster’s cost per CPU from $13.29 to $5.29.
Cluster 3: ~52% cost savings
Here, the cluster’s cost per CPU was reduced from $7.63 to $4.46.
Kubernetes automation through Cast is a game changer. Stability is also very important: Cast frequently changes machines – one after another, change after change – yet the environment remains completely stable.
The cost reduction has been significant – unlike anything we’ve seen before. The cluster hibernation for non-production environments has worked very well and was a major win for us. We’ve seen cost savings that were never possible before.
Carlos Almeida, Platform and AI Engineering Manager at Genial Investimentos
Reducing cloud costs and increasing team efficiency
Which solutions have you tried before deciding that Cast meets all of your requirements?
We tried just one tool before Cast. Our costs were reduced, but we hit a limit. No further reductions were possible. After trying Cast in a non-production environment, we saw the potential for even more savings. The solution we had previously worked well, but I believe Cast’s intelligence is more advanced.
Cast AI was implemented with the support of your partner, Delfia. Could you share more about your experience?
So, it’s been good support. After our implementation, Delfia checked in with me several times to see if we needed any further improvements or had any other issues. They were ready to assist us at any time. The team listened to us and showed a willingness to do more after implementing Cast AI to improve our tech stack.
Smooth integration
What was onboarding Cast like?
I told my team that Cast is like an iPhone – it’s very easy to start. We just need one command in our environment, and we can immediately see how Cast can reduce our costs. The graph is clear and helpful.
Starting automation isn’t always easy for everyone, but with a technical team, we were able to set it up in five to ten minutes.
So I told everyone: try Cast, because it’s incredibly easy to see how you can cut costs without any compromise. Just run one command and see what you can achieve.
What level of support did you receive from Cast?
I told your team that this is the best support we’ve had at Genial. I called your team several weeks ago about a problem, and within minutes, we received an email and had three or four people on a call with my team to resolve it as quickly as possible.
Your account manager kept messaging me: “Carlos, we’re looking into your issue. We have a lot of engineers on it.” It worked very well.
50%+ cost savings and DevOps efficiency boost
Can you describe the impact of automation on your team?
It’s the automation – the ease of automating things – that really makes a difference. I’m a heavy user of Cast. While my team handles all the technical issues, I always keep Cast open on my second screen. I experiment with new configurations in a non-production environment, adjusting CPU minimums and maximums.
Kubernetes automation through Cast is a game changer. Stability is also very important: Cast frequently changes machines – one after another, change after change – yet the environment remains completely stable.
A few months ago, our workloads were running heavily during off-hours, especially at night, which led to high costs. After implementing Cast AI, by around 11:00 PM our workloads are minimal. It’s now operating with much better resource efficiency.
The cost reduction has been significant, unlike anything we’ve seen before. The cluster hibernation for non-production environments has worked very well and was a major win for us. We’ve seen cost savings that were never possible before
Did Cast have an impact on your team’s efficiency as well?
About 90% of our workload runs on Kubernetes, so yes – Cast AI is one of our most important tools. It’s not just about reducing costs but also about improving efficiency. The automation is truly automated, we don’t need to touch it anymore.
Automating Kubernetes security
Security was another area where Cast made a change, right?
After Kubernetes automation, the biggest benefit is security. We didn’t have strong container security before—we had a couple of tools, but none that went this deep into Kubernetes.
We lacked a global view of our container security.
Now, our security information chain relies heavily on the data from Cast’s container security. It generates reports, sends them to the development team, and triggers upgrade requests when needed. I wanted to reduce these issues, and now we only need two tools.
Security was a key goal, and since Cast’s security model is included in our contract, we didn’t need any additional tools. That’s a big advantage.
Building a FinOps platform together
What are the next steps in your collaboration with Cast?
We’re continuing to improve Cast AI efficiency. Just a few weeks ago, we changed a few configurations and were able to reduce costs even further—just three configuration adjustments made a noticeable difference.
We’re also interested in trying out new Cast features ahead of time, especially as we improve our AI workloads. What we really need is a complete FinOps platform—and Cast is helping us move in that direction.
