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Case Studies

From Manual Deployments to Scalable Kubernetes Infrastructure

•

Implemented Kubernetes for a SaaS startup, boosting scalability, deployment speed, and system reliability while supporting rapid user growth.
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Client:

Early-stage B2B SaaS company (NDA)

Team:

8 engineers

Cloud:

AWS

Stack:

Node.js, React, PostgreSQL, Redis

An early-stage SaaS company with a team of 8 engineers approached CDOps Tech as their platform started growing and deployments were becoming harder to manage.

Their stack included Node.js, React, PostgreSQL, and Redis, running on AWS.

While the product was evolving quickly, the infrastructure was still being deployed manually, creating reliability risks and slowing down releases. The team needed a scalable solution that could support rapid development without hiring a full-time DevOps engineer.

The Challenge

The engineering team was deploying services manually to EC2 instances.

As the product grew, the process became risky and time-consuming. Every release carried the possibility of downtime.

Key issues included:

  • Frequent downtime during deployments
  • Inconsistent environments between staging and production
  • Manual scaling with no automatic recovery
  • Limited visibility and monitoring of workloads

This slowed down development and made it harder for the team to ship updates confidently.

The Solution

The CDOps Tech team redesigned the infrastructure and deployment workflow using Kubernetes and GitOps principles.

The platform was migrated to Amazon EKS, introducing automation across the deployment pipeline and making the system more resilient and scalable.

Key Implementations
Infrastructure as Code

Provisioned the Kubernetes environment using Terraform with reusable infrastructure modules.

Containerized Application Services

All services were Dockerized and deployed using Kubernetes resources such as Deployments, Services, and Ingress.

Standardized Deployments with Helm

Created Helm charts to make deployments consistent, repeatable, and easier to manage.

GitOps Deployment Workflow

Integrated ArgoCD to automate deployments using Git as the single source of truth.

Automatic Scaling and Self-Healing

Implemented Horizontal Pod Autoscaling so workloads scale automatically with traffic demand.

Observability and Monitoring

Added Prometheus and Grafana for monitoring and centralized logs using AWS CloudWatch.

case study 1
Robut & Dynamic Pipeline

The Results

Once the new infrastructure was deployed, the impact was immediate.

  • 99.95% uptime in the first 90 days after migration
  • Faster releases — developers now deploy multiple times per day
  • Automatic scaling to handle traffic spikes
  • Lower operational overhead — no need to hire a full-time DevOps engineer

Most importantly, the engineering team can now focus on building product features instead of managing infrastructure.

Key Takeaway

For growing SaaS teams, infrastructure needs to evolve alongside product development.

By implementing Kubernetes, GitOps, and Infrastructure as Code, this client gained a reliable and scalable platform that supports continuous delivery and growth.

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