Scalability·Reliability·Efficiency
Scalability
Reliability
Efficiency
We help ML/AI startups and other ambitious teams build scalable, reliable & cost-efficient cloud infrastructure. Fast.Who We Are
Weʼre the infrastructure team you wish you hired firstCloud Whales is a group of senior engineers whoʼve scaled production ML systems, cut millions in cloud waste, and built the kind of automation most startups only dream about. We donʼt sell dashboards - we deliver working systems and teach you how to own them_
The Truth
Many ML/AI startups face infrastructure challenges that slow down development and increase operational costs_
Here’s some of the challenges:
Lack of In-House DevOps Expertise
Teams struggle with setting up andmanaging cloud environments efficiently
High Infrastructure Costs
Poorly optimized cloud resources lead tounnecessary expenses_
Unexpected Cloud Charges
Misconfigured resources, such as cross-region data transfers or forgotten
instances, can lead to significant
unexpected expenses
Slow Time-to-Production
Complex deployments and scaling delays impactthe ability to launch quickly and reliably
Security & Compliance Concerns
Managing secure deployments andcompliance standards is a major challenge
This leads to...
29%
of startups fail due to inability to secure funding, cash flow issues, noted in 82% of failed cases_23%
fail because of lack of skills, experience, or team cohesion, including co-founder friction20%
fail because of IT infrastructure issues, including cloud challenges10%
fail due to high costs or improper pricing strategiesOptimal IT infrastructure reduces operational costs, accelerates development cycles, and keeps customer prices low_
Ready to talk?
What we deliver
We help startups and scale-ups move fast, run lean, and build with confidence.Whether youʼre just starting or fixing whatʼs already in place, we offer:
Custom Tools For Cost Control
NodeShifter, Capacity Testing Suite, and KubeAudit Kit
You don't just get charts — you get decisions
And better margins
Infrastructure, Done Right
more time to build product instead of patching infra.
We don't just spin up clusters - we build infrastructure we'd run
ourselves. Stable, scalable, production-grade
Expert Guidance, Operational Support
We architect, tune, and maintain like it's our own product, guiding your team through every stage, from Git repos setup to OpsGenie on-call handover
CI/CD & Observability Baked In
Delivery pipelines, monitoring, and alerting shouldn't be afterthoughts
Future-Proof Foundation with Automated Standards
We codify SDLC standards into your own Helm chart so every new service follows best practices — automatically
Predictive Autoscaling That Just Works
We build predictive, history-based autoscaling (inspired by ARIMA models) without needing extra ML engines
Combined with KEDA and your own tuned metrics, you'll scale up before load hits - and scale down to save
Our Cases
Capacity Testing Framework: From Guesswork to Science
The client: guessed which VM types were best for each ML microservice_What we did:
Result: Infrastructure decisions became data-driven — autoscaling was tuned, > built a framework to test each service across instance types,
measuring real throughput and cost
measuring real throughput and cost
performance-per-dollar was maximized
Capacity Testing Framework: From Guesswork to Science
The client: guessed which VM types were best for each ML microservice_What we did:
Result: Infrastructure decisions became data-driven — autoscaling was tuned, > built a framework to test each service across instance types,
measuring real throughput and cost
measuring real throughput and cost
performance-per-dollar was maximized
Capacity Testing Framework: From Guesswork to Science
The client: guessed which VM types were best for each ML microservice_What we did:
Result: Infrastructure decisions became data-driven — autoscaling was tuned, > built a framework to test each service across instance types,
measuring real throughput and cost
measuring real throughput and cost
performance-per-dollar was maximized
Capacity Testing Framework: From Guesswork to Science
The client: guessed which VM types were best for each ML microservice_What we did:
Result: Infrastructure decisions became data-driven — autoscaling was tuned, > built a framework to test each service across instance types,
measuring real throughput and cost
measuring real throughput and cost
performance-per-dollar was maximized
Capacity Testing Framework: From Guesswork to Science
The client: guessed which VM types were best for each ML microservice_What we did:
Result: Infrastructure decisions became data-driven — autoscaling was tuned, > built a framework to test each service across instance types,
measuring real throughput and cost
measuring real throughput and cost
performance-per-dollar was maximized
Why Cloud Whales
Weʼve already done the hard part — togetherWeʼre a team thatʼs built and operated the backend for ML-driven products serving millions of users. Weʼve made the mistakes, fixed them with automation, and came back with tools that work across companies_
Business Outcomes
- Faster time to production
Cut infra delays, deliver features sooner - Stronger infrastructure ROI
Maximize performance per dollar at every scale - Reduced cloud bill surprises
Know whatʼs running, why, and what it costs - Smoother scaling paths
Go from prototype to production without rearchitecting_
How We Do It
- Standardization-first mindset
Unified charts, naming, infra labels, SDLC processes - Cloud-native automation
CI/CD, scaling, observability — wired in by default - Custom tools for real cost-efficiency
NodeShifter, historical autoscaling, and more - Engineers whoʼve done it at ML scale
We bring what weʼve built — and battle-tested — before_