Single point of failure

Any component whose failure stops the whole system. Find them by asking, for every box, what happens if it disappears; remove them with redundancy across instances, zones or regions.

Where it shows up in real systems

  • Virtual machine

    Throughput grows with vCPUs and depends on the runtime: Go serves several times more requests per core than Python. If memory is below what the runtime needs, the machine swaps and slows down sharply. Several instances behind a load balancer survive the loss of one.

    In production: Amazon EC2, Azure Virtual Machines, Google Compute Engine, OVHcloud Public Cloud

  • Scheduler

    Use it for nightly reports, cleanups and retries. A single scheduler is a single point of failure; managed schedulers or leader election avoid running the same job twice.

    In production: Amazon EventBridge Scheduler, Kubernetes CronJob, Celery beat, cron

  • Reverse proxy

    NGINX or HAProxy on your own machines: very cheap and flexible, but you operate it, patch it and make it redundant yourself. A single proxy is a single point of failure.

    In production: NGINX, HAProxy, Envoy, Traefik, Caddy

See it break, then fix it

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