Simplileap

// Scale

Auto-Scaling & Load Balancing

Traffic is unpredictable. Auto-scaling and load balancing ensure your application handles spikes automatically, eliminates single points of failure, and right-sizes resources for actual load — optimising both reliability and cost.

// Key benefits

What makes this service valuable

Horizontal and vertical scaling

Auto Scaling Groups (AWS), Managed Instance Groups (GCP), and Kubernetes HPA — configured with appropriate scaling policies based on your application's traffic patterns and latency requirements.

Load balancer architecture

ALB, NLB, or Nginx — configured for your application type with health checks, sticky sessions where required, TLS termination, and rate limiting.

Cost-efficiency by design

Scaling policies that scale in aggressively during low-traffic periods and scale out ahead of traffic growth — minimising compute costs without impacting availability.

// Details

Infrastructure that handles whatever traffic throws at it

Auto-scaling eliminates the manual ops work of capacity management and the risk of traffic spikes causing downtime. When configured correctly, it is invisible — your application just keeps working regardless of load.

Load balancing distributes traffic across multiple instances — eliminating single points of failure and enabling zero-downtime deployments through rolling updates.

// What this includes

  • Auto Scaling Group or Kubernetes HPA configuration
  • Scaling policy design (CPU, memory, custom metrics)
  • Load balancer setup and health checks
  • TLS termination and certificate management
  • Target tracking and predictive scaling
  • Multi-AZ deployment for high availability
  • Load testing and scaling verification

// Deliverables

What you receive

Every engagement produces clear, documented deliverables. Here is exactly what is included in our auto-scaling & load balancing service.

  • 01Auto-scaling configuration (as code)
  • 02Load balancer setup and documentation
  • 03Scaling policy documentation
  • 04Load test results and scaling behaviour report
  • 05High availability architecture diagram

// FAQ

Common questions about auto-scaling & load balancing

What triggers auto-scaling?+

CPU utilisation and memory are common triggers, but application-specific metrics are often more accurate — request queue depth, active connections, or custom CloudWatch metrics. We design scaling triggers based on your application's actual behaviour.

Ready to get started with auto-scaling & load balancing?

Share your requirements with our team. We respond within one business day with a clear plan from discovery to delivery.