Rolling vs blue/green vs canary deployments — what are the tradeoffs?

Deep dive

Expanding on the short answer — what usually matters in practice:

• Context (tags): deployment, rolling, blue-green, canary
• Reliability: detect issues (monitoring) and limit blast radius (rollback, feature flags).
• Security: least privilege, secret rotation, supply chain.
• Automation: idempotency, repeatability, drift control.
• Explain the "why", not just the "what" (intuition + consequences).
• Trade-offs: what you gain/lose (time, memory, complexity, risk).
• Edge cases: empty inputs, large inputs, invalid inputs, concurrency.

Examples

A tiny example (an explanation template):

// Example: discuss trade-offs for "rolling-vs-blue/green-vs-canary-deployments-—-wh"
function explain() {
  // Start from the core idea:
  // Rolling updates replace instances gradually with minimal extra capacity but can expose par
}

Common pitfalls

• Too generic: no concrete trade-offs or examples.
• Mixing average-case and worst-case (e.g., complexity).
• Ignoring constraints: memory, concurrency, network/disk costs.

Interview follow-ups

• When would you choose an alternative and why?
• What production issues show up and how do you diagnose them?
• How would you test edge cases?