Summary
The Observability SRE at Apple Services in London operates at a massive scale, tackling unique challenges across geographies and serving millions of users. This role involves owning the full infrastructure stack for observability platforms, ensuring reliability, performance, and automation. Responsibilities are broad and deep, utilizing a mix of open-source, vendor, and internal tools for provisioning, deployment, monitoring, and end-to-end operation of systems. Collaboration with development teams and a software-engineering approach to automate operational problems are key.
Description
Apple Services' scale is BIG. Operating across multiple geographies and serving hundreds of millions of users presents unique challenges, and as an Observability SRE at Apple you'll solve them using data, teamwork, and your own expertise. SREs here own the full infrastructure stack and our responsibilities are both broad and deep.
Our team is responsible for the reliability, performance, and automation of the observability platforms that power the rest of Apple Services. We run a mix of open source, vendor-licensed, and internally developed tooling to provision, deploy, monitor, and operate these systems end to end from bare-metal and Kubernetes fleets through to the telemetry pipelines that detect a host going down within seconds. You'll learn these tools and have real opportunities to improve them.
We're a collaborative team. We work closely with the development teams we support and often engage as a single team on shared projects to deliver the best result for Apple. We think critically, balance the best solution against the need to get things done, and reward good ideas and results. We approach operational problems with a software-engineering mindset: if something is manual and repetitive, we automate it away.
Experience with the Prometheus observability platform and associated technologies.
Experience with Infrastructure-as-Code and config-as-code tooling such as Terraform, Pulumi, or Pkl.
Experience managing and scaling distributed systems in a public, private, or hybrid cloud environment.
Ability to design, author, and release code in a high-level language such as Python or Go with hands-on experience operating Kubernetes.
Experience deploying, supporting, and monitoring services, platforms, and application stacks.
Solid understanding of the Linux operating system, standard networking protocols, and their components.
Hands-on experience with configuration-management and software-delivery platforms such as Puppet, Chef, Ansible, or Spinnaker.
Experience with Grafana, Thanos, and distributed tracing / OpenTelemetry standards.
Experience with scale testing, disaster recovery, and capacity planning.
Experience with fleet/cluster lifecycle management, node provisioning, and hardware-adjacent reliability (e.g. capacity management) at scale.
Experience building and operating CI/CD pipelines for cloud infrastructure.
Deeper Linux knowledge - kernel, memory, processes/threads, static/shared libraries, IPC, signals and networking fundamentals such as HTTP, DNS, ECMP, TCP/IP, ICMP, the OSI model, subnetting, and load-balancing strategies.
