Cloud Era Technology helps startups and mid-size companies get control of their infrastructure — reducing waste, automating operations, and deploying AI that actually works in production.
Cloud Era Technology is a cloud & AI consulting firm helping startups and mid-size businesses cut infrastructure costs and ship faster — without adding headcount.
We work across leading cloud platforms and tools
Over-provisioned instances, forgotten resources, and inefficient storage quietly drain your budget every month.
Engineering time spent on repetitive releases is time not spent building product or serving customers.
Misconfigured IAM roles, unencrypted data, and missed compliance requirements create real business risk.
ML models that never reach production generate zero business value — no matter how good the accuracy is.
We find and eliminate infrastructure waste, guaranteed 20–40% cost reduction within 90 days.
Replace manual processes with CI/CD pipelines and infrastructure-as-code that your team can own.
Close security gaps before they become incidents. We make compliance a side effect of good engineering.
We take your models from notebooks to production — with monitoring, versioning, and automated retraining.
We analyze your infrastructure, costs, and security posture at no cost — and deliver a findings report.
We identify the highest-impact changes first — so you see ROI within weeks, not months.
Our engineers execute the roadmap alongside your team — writing production-grade code and automation.
We document everything and train your team so you're never dependent on us to keep things running.
"We were spending huge amount per month on AWS with no visibility. Cloud Era cut our cloud bill 35% within 60 days and we didn't lose a single feature."
"Our deployment cycle went from 3 days to 4 hours. The CI/CD pipeline they built just works — our team loves it."
"We had an ML model sitting in a notebook for 6 months. Cloud Era had it in production in 3 weeks. It's now processing 10K predictions daily."
Cloud Era Technology was founded by cloud architects and DevOps engineers who spent years inside fast-growing companies watching the same problems repeat: ballooning infrastructure bills, broken deployment pipelines, and AI projects that never made it to production.
We started Cloud Era because we knew these problems were solvable — not with more tooling, but with the right expertise applied in the right order.
Today we work with startups, SaaS companies, and mid-size businesses across AWS, Azure, and GCP — helping them build the infrastructure they need to grow without waste.
To make cloud infrastructure a growth asset, not a cost center — for every company we work with.
A world where every engineering team has access to the infrastructure expertise that only the largest companies currently enjoy.
We prioritize impact. We fix the most expensive problems first and always leave your team more capable than we found them.
Most companies are overspending on cloud by 30–50%. We find exactly where your money is going, fix it, and put controls in place so it doesn't happen again. Our work comes with a guaranteed 20–40% cost reduction commitment.
Full analysis of your AWS/Azure/GCP bill. We identify unused resources, oversized instances, and inefficient storage patterns.
We match your compute and database sizing to actual workload demands and build a reserved instance strategy that fits your growth plan.
Cost tagging, budget alerts, and dashboards so your team has real-time visibility and accountability over every dollar spent.
Manual deployments slow your team down and introduce risk. We automate your entire delivery pipeline — from code commit to production — so your engineers can focus on product, not process.
End-to-end pipeline setup using GitHub Actions, GitLab CI, or Jenkins with automated testing, security scanning, and rollback capabilities.
We write and maintain your infrastructure in Terraform — versioned, repeatable, and team-owned. No more clicking through consoles.
Kubernetes cluster design and management, ECS task definitions, and service mesh configuration for scalable microservices architectures.
Security should be built into your infrastructure, not bolted on after a breach. We embed security controls into every layer — identity, data, networking, and deployment pipelines.
Least-privilege access policies, MFA enforcement, service account hygiene, and cross-account role management.
SOC2, GDPR, HIPAA, and ISO 27001 compliance controls built into your infrastructure with automated evidence collection.
Vulnerability scanning, intrusion detection, and SIEM integration so threats are caught before they cause damage.
Building an ML model is the easy part. Getting it to run reliably in production at scale — that's where most teams get stuck. We close that gap with production-grade MLOps infrastructure.
Deploy models via REST APIs, batch pipelines, or real-time streaming using SageMaker, Vertex AI, or custom Kubernetes deployments.
Automated training, evaluation, and deployment pipelines using MLflow, Kubeflow, or Airflow — integrated with your CI/CD workflow.
Production model monitoring for accuracy degradation, data drift, and latency — with automated alerts and retraining triggers.
Challenge: A 60-person SaaS company was spending $48,000/month on AWS. Engineers had no visibility into what was driving costs, and the bill had grown 80% in 12 months.
What We Did: Conducted a full cost audit revealing $18K/month in idle EC2 instances, unattached EBS volumes, and over-provisioned RDS. Implemented right-sizing, reserved instances, and automated shutdown schedules for non-prod environments.
Challenge: A fast-growing e-commerce company had manual deployment processes requiring 3 days of engineering coordination. Releases happened twice a month, blocking product iteration.
What We Did: Designed and implemented a full CI/CD pipeline on GitHub Actions with automated testing, staging environment promotion, and one-click production deployments. Migrated infrastructure to Terraform for repeatable provisioning.
Challenge: A fintech startup needed SOC2 Type II certification to close enterprise deals. Their AWS environment had 140+ IAM policy violations and no audit logging in place.
What We Did: Completed a full IAM audit and remediation, enabled CloudTrail and GuardDuty across all accounts, implemented encryption at rest and in transit, and set up automated compliance evidence collection for the auditor.
Challenge: A data team at a logistics company had a churn prediction model with 87% accuracy sitting in a Jupyter notebook for 6 months. No production path had been identified.
What We Did: Containerized the model, built a FastAPI serving layer on AWS ECS, set up an MLflow registry for version control, and implemented automated retraining triggered by data drift detection in production.
Challenge: A healthcare SaaS company needed to split workloads across AWS and Azure to meet data residency requirements from enterprise clients in three geographies.
What We Did: Designed a multi-cloud architecture using Terraform for both platforms, implemented VPN-based inter-cloud connectivity, unified logging across both environments, and executed a phased migration with zero-downtime cutovers.
Challenge: A recently funded startup needed to extend their runway by reducing burn without slowing down engineering. Cloud and infrastructure were their second-largest expense.
What We Did: Combined FinOps optimization (right-sizing, spot instances, S3 lifecycle policies) with full CI/CD automation to both cut costs and increase engineering throughput simultaneously over a 90-day engagement.
Tell us where you're feeling the most pain — cloud costs, slow deployments, security gaps, or AI stuck in notebooks. We'll respond within one business day with a clear next step.
No spam. No sales pitch. Just a straightforward conversation about your infrastructure.