Case study 05 / DevOps · Platform Engineering

Built for the next traffic spike.

Load balancing, horizontal scaling and Redis caching for a growing real estate platform.

Project

Kubernetes Platform Scaling

My role

Infrastructure architecture, deployment design and production troubleshooting

Production architecture showing load balancer, Kubernetes ingress, application pods, Redis and data sources
Production architecture from the platform engineering case study.

01 / The challenge

Start with the problem.

One application instance handled listings, dashboards, CRM integrations and repeated database and API requests. Traffic spikes and instance failures created operational risk.

02 / The approach

Connect the moving parts.

  1. 01

    Designed containerized workloads behind a cloud load balancer and Kubernetes ingress.

  2. 02

    Distributed traffic across application pods with horizontal scaling and health checks.

  3. 03

    Introduced Redis caching for frequently requested data, with freshness rules and fallback to authoritative sources.

Load balancer
Kubernetes pods
Redis + data sources

03 / Engineering decisions

The thinking behind the work.

Scale the application

Distribute requests across healthy application instances instead of relying on one larger server.

Cache with rules

Account for cache keys, TTL, invalidation, misses and fallback when designing data access.

Design for failure

Combine instance recovery, healthy routing and visibility into application and infrastructure behaviour.

04 / The outcome

What changed.

Moved the architecture toward multiple application instances, Redis-backed caching and better fault tolerance, preparing the platform for growing workloads.

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