Infrastructure Engineering
High-performance backends and production-ready AI runtimes — Docker, CI/CD, Redis, Nginx.
The Problem: Infrastructure Failures Are Business Failures
When your backend can't handle traffic spikes, your database becomes the bottleneck, or your deployment pipeline breaks at 2 AM — your users don't care about your feature roadmap. They just see downtime.
Infrastructure problems compound silently. A slow query here, a missing cache there, a deployment that should have been automated but isn't. Each one individually seems manageable, but together they create a system that's fragile, expensive to maintain, and painful to scale. By the time most teams address infrastructure, they're already firefighting.
For AI and data-intensive applications, infrastructure challenges multiply. Model serving has different resource profiles than web APIs. TTS pipelines need low-latency GPU access. Vector databases require careful memory management. A one-size-fits-all infrastructure approach doesn't work when you're running fundamentally different workloads on the same cluster.
The Solution: Reliable, Observable, Scalable Infrastructure
NemesisNet builds infrastructure that's invisible when it works — and that's exactly how it should be. We design Docker-based ecosystems with clear service boundaries, implement caching and queue patterns that absorb traffic spikes, and set up monitoring so you see problems before your users do.
Every deployment is reproducible through infrastructure-as-code. Every service has health checks and graceful degradation. Every pipeline is automated from commit to production.
Backend Performance & Caching
Implementing Redis caching and queue patterns to handle massive traffic spikes without breaking a sweat. We architect multi-layer caching strategies — in-memory caches for hot data, distributed caches for shared state, and persistent queues for async processing.
Our approach includes connection pooling, read replicas, query optimisation, and circuit breaker patterns. Whether you're serving 100 requests per second or 10,000, we design systems that maintain consistent response times under load.
Dockerised Ecosystems
Creating immutable infrastructure with Docker and Docker Compose, ensuring your app runs exactly the same on your laptop as it does in production. Every service, every dependency, every configuration file is version-controlled and reproducible.
Containerised deployments eliminate "it works on my machine" problems and enable zero-downtime rolling updates. Multi-stage builds keep production images lean. Docker Compose orchestration simplifies local development while mirroring production topology.
Nginx Edge Control
Professional reverse proxy setups for SSL termination, load balancing, and optimised content delivery. We configure Nginx as an application-level gateway with rate limiting, request buffering, gzip compression, and intelligent routing.
Static assets are served directly from Nginx, bypassing application servers entirely. Combined with CDN configuration, this delivers sub-100ms response times for static content globally.
AI Runtime Deployment
Deploying local AI models and TTS pipelines for privacy and speed, bypassing expensive cloud dependencies. We've built production AI serving infrastructure using vLLM, Ollama, and custom Python servers — with GPU memory management, request batching, and model hot-swapping.
Our infrastructure handles the complexity of running AI workloads alongside traditional web services: GPU scheduling, model versioning, inference caching, and graceful fallback to CPU when GPUs are under heavy load.
Who This Is For
Engineering teams that need production infrastructure without hiring a dedicated DevOps team. AI companies running model serving alongside web applications. Scaling startups that have outgrown their initial infrastructure. Teams migrating to microservices or containerised architectures.
How We Deploy
Architecture Assessment
We review your current infrastructure, identify bottlenecks, and define the target architecture — including service boundaries, data flow, and scaling strategy.
Infrastructure as Code
Every component is defined in Docker Compose files and provisioning scripts. Environments are reproducible — development, staging, and production are structurally identical.
CI/CD Pipeline
Automated build, test, and deployment pipelines. Every commit triggers tests; every merge triggers deployment. Rollback is a single command.
Monitoring & Observability
Prometheus metrics, Grafana dashboards, and alerting rules configured for your specific SLAs. We set up error tracking, uptime monitoring, and performance baselines.
Why NemesisNet
Infrastructure is where we started, and it's what we keep coming back to. We've deployed production systems across bare metal, cloud VMs, and container orchestration platforms. We understand the full stack from hardware to HTTP — and we build infrastructure that your developers actually want to work with. Cape Town-based with remote-first workflows that span multiple time zones.