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Single point of failure

As explained in Think Like a CTO

A single point of failure is a component whose failure can disrupt or halt a system because no adequate redundant alternative is available.

A single point of failure is a component or dependency whose failure can seriously disrupt a service because no adequate alternative is ready. In a cloud environment, lost data or a hardware failure that takes down part of the architecture can expose missing redundancy or an overly tightly coupled setup. Moving to the cloud does not make failures disappear. section 8.3.1

Look for weak points in both the system and the work that keeps it running:

  • Ask what happens when a piece of the architecture fails, and whether another can take over without major disruption. section 8.3.1 section 14.5.1
  • Check backups, recovery plans, and instructions that someone else could follow to restore the environment. section 14.5.1
  • Identify who pays for and renews essential services. An account billed to an original developer's personal card may be an operational dependency that needs resolving. section 14.5.1

A dependency outside the architecture

A production service can go dark because a domain or SSL certificate is not renewed. Google temporarily lost control of the blogger.in domain after a missed payment. A resilience review therefore needs to ask not only what fails over, but also who owns and renews the services on which production depends. section 14.5.1

During due diligence, ask how the team knows production is healthy right now: which daily checks are made, which logs are reviewed, and what early warning signs people watch. Then discuss known weak points and how they are being addressed. The aim is a defensible picture of what it takes to keep the service running, not an assumption that cloud hosting alone provides resilience. section 14.5.1 section 8.3.1

How Think Like a CTO covers it

How deep it goes
Explains warning signs and review questions, but stops short of technical failover designs.
Examples
Uses disruptive hardware failure, lost data, personally billed service accounts, and a missed domain renewal.
What it assumes
Assumes familiarity with cloud infrastructure and production operations rather than teaching their mechanics from zero.
What you can do after
Evaluate/understand it by checking failure behavior, recovery instructions, production monitoring, and renewal ownership.
How it connects
Connects redundancy and cloud elasticity with fault tolerance, backups, recovery, and service-account ownership.

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This explainer was generated by Manning's knowledge graph from the text of Think Like a CTO. The section links point to the parts of the book it draws on.