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HIRAK

About

I'm Hirak.

I’m interested in the infrastructure behind software: how applications are built, deployed, scaled, observed and recovered when something goes wrong. My current focus is Kubernetes, platform engineering, cloud infrastructure and the systems required to operate AI workloads.

Background

My route into engineering has not been completely linear.

I originally studied business and marketing before moving into computer science and software infrastructure. That change pushed me toward a part of computing I found particularly interesting: not only writing an application, but understanding everything required to make that application run reliably.

An isometric illustration of nine stacked platforms, from Linux at the base to platform engineering at the top, with a figure walking a dashed path up the stack.An isometric illustration of nine stacked platforms, from Linux at the base to platform engineering at the top, with a figure walking a dashed path up the stack.
Foundations first, then distribution and scale, then building and operating platforms.
  • Linux: the foundation — understanding the operating system and how things work under the hood.
  • Networking: understanding how systems communicate.
  • Containers: packaging applications and their dependencies.
  • Kubernetes: orchestrating and managing containers at scale.
  • Cloud: running and scaling applications in the cloud.
  • Infrastructure as code: defining and managing infrastructure through code.
  • CI/CD: automating build, test and deployment pipelines.
  • Observability: monitoring, logging and understanding system behaviour.
  • Platform engineering: bringing everything together to build reliable, scalable systems.

I completed an MSc in Computer Science at the University of Sussex, where my dissertation explored LLM-assisted log analysis for Kubernetes incident response.

Focus

What I’m focused on

Kubernetes & Platform Engineering

Building platforms that make application deployment repeatable, observable and reliable.

Cloud Infrastructure

Understanding the systems beneath managed services rather than treating cloud resources as isolated products.

Reliability

Testing how systems behave during resource pressure, dependency failure, bad deployments and infrastructure failures.

AI Infrastructure

Exploring the infrastructure required to serve AI applications efficiently — inference serving, routing, caching, observability and cost.

Technologies

Tools I work with

Infrastructure
Kubernetes · Docker · Terraform · Ansible · Helm · Argo CD
Cloud
AWS · EKS · EC2 · ECR · RDS · S3 · VPC · IAM
Delivery
GitHub Actions · Jenkins · GitOps
Observability
Prometheus · Grafana · Loki · OpenTelemetry
Development
Python · FastAPI · JavaScript · React · PostgreSQL · Redis
AI Infrastructure
LLM APIs · vLLM · RAG · pgvector

Certifications

CNCF Kubestronaut

Kubernetes and cloud-native certification milestone covering the CNCF Kubernetes certification path.

Homelab

Somewhere to break things on purpose

I also maintain a small environment for infrastructure experiments. It gives me somewhere to test infrastructure, intentionally break things and investigate behaviour without treating every experiment as a cloud bill.

Two-node homelab on a 1 Gbit network.

Contact

Let’s talk.

If you want to discuss Kubernetes, platform engineering, cloud infrastructure, AI systems, an interesting engineering problem, or an opportunity to work together, feel free to reach out.

Email

[email protected]

Elsewhere