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AI SAAS · PLATFORM ENGINEERING

Scaling AI Infrastructure Without Scaling Complexity

How we helped ApplyOK build infrastructure foundations to scale AI workloads with confidence.

INDUSTRY
AI SaaS
CHALLENGE
Scalability & Reliability
SERVICES
Platform Engineering · Observability · SRE

Overview

ApplyOK is an AI-powered platform that helps job seekers improve their applications through automated analysis, intelligent recommendations and AI-assisted workflows.

As the platform evolved, infrastructure requirements became increasingly demanding. AI workloads introduced additional complexity around scalability, deployment consistency, observability and operational reliability.

The Good Shell partnered with ApplyOK to establish the infrastructure foundations required to support growth while keeping operational complexity under control.

The Challenge

AI products present unique infrastructure challenges. Unlike traditional web applications, they often combine API services, AI inference workloads, background processing, external AI providers and rapid deployment cycles.

As ApplyOK continued to evolve, several priorities emerged:

Limited operational visibility

Understanding what happens across multiple services becomes increasingly difficult without centralized observability.

Infrastructure scalability

The platform required an architecture capable of supporting future growth without introducing operational bottlenecks.

Deployment consistency

As products mature, manual deployment processes become a source of risk and inefficiency.

Operational reliability

The team needed infrastructure that could remain predictable as complexity increased.

Our Approach

The Good Shell focused on building infrastructure foundations designed for long-term scalability and operational confidence.

Infrastructure as Code with Terraform

Infrastructure was standardized and managed using Terraform, creating a reproducible and auditable environment. Benefits included:

  • Consistent infrastructure provisioning
  • Reduced configuration drift
  • Faster environment creation
  • Improved operational control

Kubernetes Platform

Workloads were deployed and managed on Kubernetes, providing a scalable foundation capable of supporting growth without increasing operational complexity. This enabled:

  • Better workload orchestration
  • Consistent deployments
  • Improved resource management
  • Greater platform resilience

Deployment Automation

Deployment processes were automated to improve reliability and reduce manual intervencion. The objective was to make releases predictable, repeatable and easier to operate. Key improvements included:

  • Faster deployments
  • Reduced deployment risk
  • Improved release confidence
  • More efficient engineering workflows

Observability with OpenTelemetry

Visibility is essential when operating AI workloads. The Good Shell introduced observability practices powered by OpenTelemetry, providing deeper insight into platform behaviour and service interactions. This allowed the team to:

  • Monitor application performance
  • Identify issues earlier
  • Improve operational awareness
  • Build a stronger reliability culture

Outcomes

The project delivered a stronger infrastructure foundation capable of supporting future growth while reducing operational overhead.

TECHNICAL OUTCOMES

  • Infrastructure managed through Terraform
  • Kubernetes-based platform architecture
  • Centralized observability with OpenTelemetry
  • Automated deployment workflows
  • Improved visibility across production systems

BUSINESS OUTCOMES

  • Faster engineering delivery
  • Reduced operational complexity
  • Increased confidence when deploying changes
  • Infrastructure foundations ready for growth
  • Better visibility into production workloads

Technical Stack

INFRASTRUCTURE

  • Kubernetes
  • Terraform
  • Cloud Infrastructure

OBSERVABILITY

  • OpenTelemetry
  • Monitoring & Alerting
  • Centralized Telemetry

PRACTICES

  • Infrastructure as Code
  • Deployment Automation
  • Reliability Engineering
  • Platform Engineering

Why It Matters

Many AI startups reach a point where infrastructure complexity begins to slow product development. The goal is not simply to add more infrastructure. The goal is to create systems that allow engineering teams to focus on building product rather than managing operational complexity.

For ApplyOK, this meant establishing a platform foundation capable of supporting future growth while maintaining reliability, visibility and deployment confidence.

Building an AI product?

Whether you're scaling AI workloads, improving observability or modernizing infrastructure, The Good Shell helps teams build reliable platforms without hiring a full platform engineering team.

Book a free infrastructure review and discover where your platform can improve reliability, scalability and operational efficiency.