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Spotify Logo
Spotify2026, ongoing

Spotify

Backend, platform and SRE work on Spotify's core infrastructure, at global scale

Cloud / DevOps

Traffic
11–12M req/s
Reach
777M users, 184 markets
Cloud
GCP / GKE
Spotify Logo

Spotify's Core Infrastructure group builds and operates the platform Spotify's backend services run on. It serves 11–12 million backend requests per second, globally, for 777 million monthly users in 184 markets, on a Kubernetes fleet spanning regions from Europe and the US to Asia. I joined in September 2026 for backend, platform and SRE work at that scale.

01

A capacity tracker built solo, and used to plan the peak season

Seeing the compute the fleet can actually get used to mean jumping between many monitoring systems and panels in GCP. I built a single pane of glass for it, alone. It shows what compute is available, reserved and running out, per region, live, for anyone in the company who needs it. Everyone and everything is visible in one place, quickly, which was basically impossible before. It was picked up the moment it existed and now drives compute planning for the rest of the year, critically for Black Friday and Cyber Monday.

Built by
Solo
Stack
Java, React, Grafana

02

A service that can take any machine out of the fleet, and never a whole cluster

At this scale the risky part of removing an unhealthy machine is doing it without causing an outage. Every node in the fleet runs a health agent I built, and nodes are never allowed to retire themselves. They report to one central service, where I built the part that decides and acts. It takes a faulty node out of rotation, keeps it for debugging and alerts the team, and it is rate-limited so it can never take down a whole cluster. A service that can reach every machine in a global fleet is only as safe as its limits, so the limits were the work.

Reach
Every node, globally
Stack
Python, Bash, Java, gRPC

03

The agent decides, the scripts act

Creating or updating a custom tenant cluster touches GitHub Enterprise, Backstage and Jira. I automated it with AI agents under one rule. The agent makes the decisions, and every action it takes in those systems goes through strict scripts it is required to use. Whatever gets created or posted is deterministic and consistent, however the agent got there. That rule is what makes an agent safe to put in a real workflow.

Stack
Python, AI agent skills

04

Upgrades and handovers across the whole platform, from the first days

Alongside the build work I upgraded critical platform services across Spotify's global server fleet, policy enforcement among them, and that work has continued with image verification. I also took part in the global GKE version upgrades and took over several projects in handover, among them a new multi-tenant auth and IAM system and the next generation of service auth. None of it waited on a ramp-up. I was working across the entire platform, globally, within the first days.

Regions
EU, US, Asia and more
Since
September 2026

What I owned

Principal Engineer

  • Global capacity tracker, built solo, one place for the fleet's compute per region, live
  • Health agent on every node in the global fleet
  • Safe node retirement, rate-limited so no cluster can be taken down
  • Tenant-cluster automation, AI agents bound to deterministic scripts
  • Fleet-wide platform and GKE upgrades, policy enforcement included
  • Handovers, including multi-tenant auth and IAM and next-gen service auth

GCP / GKE / Kubernetes / Java / React / Python / Bash / gRPC / Grafana / Terraform / Terraform Cloud / Backstage / AI agents

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Next step

Tell me what you're building

Send me a short description of the problem and I'll tell you whether I'm the right fit, what it would cost, and how long it would take. No pitch deck.

Email meCall +46 70 753 73 78
Email
elinor@wigertztech.se
Phone
+46 70 753 73 78
LinkedIn
elinorwigertz