Building a production-grade EKS platform for accelerated innovation
Adaptavist engineered a comprehensive AWS EKS platform enabling rapid application deployment across four specialised environments whilst achieving 30-40% cost savings.
Requirements at a glance
- Scalable platform for rapid application deployment
- Abstract Kubernetes complexity from development teams
- Support diverse workloads across multiple domains
- Maintain security and compliance standards automatically
- Optimise costs whilst ensuring performance
Industry: Enterprise IT | Digital Transformation
Solution: Cloud-native platform engineering with AWS EKS
Result: Four specialised platforms supporting accelerated innovation and deployment velocity
Key metric: 30-40% cost savings through intelligent resource optimisation
Summary
A digital transformation company needed a streamlined infrastructure for deploying developer tools and internal applications across multiple business functions. Traditional approaches would create fragmented infrastructure and operational overhead. Adaptavist engineered a production-grade AWS EKS platform with comprehensive observability, intelligent autoscaling, and security-first architecture, enabling teams to focus on innovation rather than infrastructure management whilst achieving significant cost efficiencies.
The challenge
The challenge extended beyond basic infrastructure provisioning. Development teams needed to focus on application delivery rather than wrestling with Kubernetes complexity. Meanwhile, diverse organisational functions—from data science to AI development—each demanded specialised tooling and environments tailored to their unique requirements.
Traditional approaches would have resulted in fragmented infrastructure, inconsistent security policies, and significant operational overhead. The organisation needed a unified platform strategy that could scale across multiple domains whilst maintaining governance and cost efficiency.
The solution
Our team engineered a robust, production-grade platform cluster using AWS Elastic Kubernetes Service, establishing comprehensive infrastructure for scalable and resilient application hosting. High availability and fault tolerance across multiple Availability Zones ensured business continuity, whilst EKS best practices guided every architectural decision.
Comprehensive observability
Comprehensive observability
The platform integrated a comprehensive observability stack, featuring Prometheus for metric collection, Grafana for interactive dashboards and visualisation, and centralised logging through OpenSearch. This comprehensive monitoring provided deep visibility into both application performance and infrastructure health, enabling proactive issue resolution.
Intelligent autoscaling
Intelligent autoscaling
We implemented dual-layer autoscaling mechanisms to balance performance and cost efficiency. Karpenter dynamically adjusted underlying EKS node counts based on cluster-wide demand patterns, whilst Horizontal Pod Autoscalers scaled application workloads based on CPU, memory, or custom metrics. This intelligent scaling absorbed traffic spikes gracefully whilst minimising unnecessary resource consumption.
Security-first architecture
Security-first architecture
Security considerations permeated every layer of the platform. Network Policies controlled pod-to-pod communication, while IAM Roles for Service Accounts (IRSA) provided granular workload permissions, adhering to least-privilege principles. The CI/CD pipeline incorporates vulnerability scanning and image signing, complemented by runtime security policies enforced through Kyverno to maintain compliance standards automatically.
Infrastructure as code
Infrastructure as code
Crossplane integration enabled declarative infrastructure provisioning, maintaining synchronisation between application requirements and underlying resources. This approach embeds infrastructure management within standard development workflows, ensuring consistency and enabling version control of the complete platform stack.
Enhanced developer experience
We abstracted Kubernetes complexity through strategic platform design, enabling GitOps workflows with ArgoCD and providing simplified deployment pipelines alongside comprehensive documentation. This developer experience platform allowed application teams to focus purely on business logic and delivery, eliminating the cognitive burden of complex cluster operations and Kubernetes manifest management.
Comprehensive observability
The platform integrated a comprehensive observability stack, featuring Prometheus for metric collection, Grafana for interactive dashboards and visualisation, and centralised logging through OpenSearch. This comprehensive monitoring provided deep visibility into both application performance and infrastructure health, enabling proactive issue resolution.
Intelligent autoscaling
We implemented dual-layer autoscaling mechanisms to balance performance and cost efficiency. Karpenter dynamically adjusted underlying EKS node counts based on cluster-wide demand patterns, whilst Horizontal Pod Autoscalers scaled application workloads based on CPU, memory, or custom metrics. This intelligent scaling absorbed traffic spikes gracefully whilst minimising unnecessary resource consumption.
Security-first architecture
Security considerations permeated every layer of the platform. Network Policies controlled pod-to-pod communication, while IAM Roles for Service Accounts (IRSA) provided granular workload permissions, adhering to least-privilege principles. The CI/CD pipeline incorporates vulnerability scanning and image signing, complemented by runtime security policies enforced through Kyverno to maintain compliance standards automatically.
Infrastructure as code
Crossplane integration enabled declarative infrastructure provisioning, maintaining synchronisation between application requirements and underlying resources. This approach embeds infrastructure management within standard development workflows, ensuring consistency and enabling version control of the complete platform stack.
The result and business impact
Our EKS platform implementation delivered measurable improvements across operational efficiency, developer velocity, and cost management, establishing a foundation for sustained innovation.
Accelerated innovation cycle
The engineering team leveraged the playground platform for rapid prototyping and continuous deployment, supporting the deployment and evaluation of four to five new applications monthly. This high deployment velocity demonstrated the platform's effectiveness as a testbed for emerging solutions and experimental features.
Strategic platform ecosystem
Recognising diverse organisational needs, we strategically extended the core platform into four specialised environments, each optimised for distinct functions:
- Data Platform - Dedicated infrastructure supporting data scientists and engineers with scalable data pipelines, processing, and warehousing capabilities. Key technologies included Apache Airflow for workflow orchestration, Apache Kafka for event streaming, and Apache Flink for real-time stream processing.
- Developer Tools Platform - Central hub for development tooling and infrastructure provisioning, streamlining CI/CD processes. Core components included Internal Developer Platforms for self-service capabilities, GitLab Runners for pipeline execution, and ENV0 for infrastructure automation.
- AI Platform - Secure, high-performance environment for AI model hosting and management. The platform supported local model deployment through Ollama integration, internal AI chat applications for team collaboration, AI gateway routing for model optimisation, and the Vibe Coder Platform for AI-assisted development.
- Application Platform - Internal application hosting environment enabling business functions, including Finance, HR, and Operations, with necessary digital tools and services, consolidating disparate applications onto a unified infrastructure.
Operational excellence through containerisation
Adopting managed container orchestration through AWS EKS substantially enhanced operational efficiency and accelerated product development cycles. The managed service eliminated undifferentiated infrastructure management, allowing teams to concentrate on application innovation rather than cluster maintenance.
Cost optimisation and efficiency
Platform cost efficiency became a continuous achievement through intelligent resource management. Karpenter's dynamic scaling replaced traditional provisioning guesswork with demand-driven capacity adjustment. Strategic use of AWS Spot Instances for fault-tolerant workloads—including GitLab Runner and Airflow executors—delivered substantial cost savings of 30% to 40% compared to On-Demand pricing.
Transformational cloud economics
The combined strategy of managed EKS for operational simplicity, Karpenter for financial efficiency, and comprehensive developer experience platforms for cultural velocity established a modern, resilient, and cost-effective cloud foundation. Usage-based consumption replaced capacity planning, whilst self-service capabilities empowered teams to deploy applications independently.
Full adoption of GitOps workflows ensured deployment consistency, complete traceability, and rapid, reliable rollbacks when needed. The declarative approach to infrastructure and application management reduced configuration drift whilst improving auditability across all platform operations.
Key learnings and best practices
EKS facilitated rapid platform development
The abstraction of Kubernetes complexity provided by AWS EKS proved instrumental in accelerating platform development. Managed control planes eliminated operational burden, while maintaining upgrades ensured that security patches and feature enhancements arrived without manual intervention.
Developer adoption requires trust-building
Initial platform adoption encountered resistance, necessitating deliberate efforts to build developer trust. Comprehensive documentation, responsive support, and visible success stories gradually overcame initial scepticism, demonstrating the platform's value proposition through practical results.
Cloud-native tool integration demands expertise
Deploying third-party tools designed for cloud-native environments presented specific challenges around configuration, networking, and state management. Success required a deep understanding of both the tools and the platform's operational characteristics.
Declarative infrastructure management proves effective
Crossplane's declarative approach to infrastructure provisioning maintained tight synchronisation between application requirements and underlying resources. The GitOps model for infrastructure management reduced configuration drift whilst improving change auditability and rollback capabilities.
Looking forward
The platform's modular architecture positions the organisation for continued expansion. Future enhancements include advanced AI/ML workload optimisation, multi-region deployment capabilities, and enhanced developer self-service features. The established foundation enables rapid adoption of emerging AWS services whilst maintaining security, compliance, and cost efficiency as business demands evolve and scale globally.
Have questions about our approach to intelligent autoscaling or cost optimisation?
Contact Adaptavist today to discuss how we can help.