Serverless vs Containers
Spiky and event-driven versus sustained throughput.
5 to work through
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intermediate Multiple choice
A publisher must choose between serverless functions and containers for its asynchronous processing. What decides it?
2 min answer -
intermediate
A team must choose between serverless functions and containers for a new API with unpredictable, spiky traffic. Walk through the decision.
2 min answer -
intermediate
A team must choose between serverless functions and long-running containers for a new workload. Which characteristics decide it?
2 min answer -
advanced
A grocery-delivery marketplace moves its order-status API from long-running containers to per-request functions to stop paying for idle capacity overnight; traffic swings about 20x between trough and the evening peak. What did the team buy, and when does the bill arrive?
2 min answer -
advanced
An image-derivative pipeline runs as functions: about 270 million invocations a month at roughly 1.8 seconds and 2 GB of memory each, costing about 16000 dollars a month at 2026 per-invocation prices. The team wants to move it to a container fleet on one-year reserved capacity. Give the sequence, say where output can diverge, and name the point of no return.
3 min answer
2 terms in this topic
Execution Model Fit
Matching a workload's traffic shape, duration and state requirements to the execution model that suits it, rather than choosing one model for everything.
metricUtilisation Break-Even
The sustained busy fraction at which always-on compute becomes cheaper than per-invocation billing, which turns the serverless-or-containers argument…
Neighbouring topics
Architecture Decision-Making
General material on making and recording architectural decisions.
Architecture Decision Records
One decision, its context, alternatives and consequences, kept immutable.
Reversibility
One-way and two-way doors, and buying optionality deliberately.
Build vs Buy
Differentiation, five-year TCO, and the exit cost of each option.
Monolith vs Microservices
A team-topology decision far more often than a technology one.
SQL vs NoSQL
Decided by access patterns and query flexibility, not by data volume.
Sync vs Async
Whether the caller's outcome depends on the callee's response.
Strong vs Eventual Consistency
A per-operation decision, resolved by what a stale read would cost.
Managed vs Self-Managed
Trading control and unit cost against operational attention.
Single vs Multi-Region
Driven by RTO, RPO and residency rather than by ambition.
Centralised vs Distributed
Shared platform leverage against team autonomy.
Performance vs Cost
Buying latency, and knowing what the last millisecond is worth.
Reliability vs Complexity
Mechanisms that add availability and add failure modes.
Security vs Usability
Varying control by the value of the action rather than uniformly.
Delivery vs Maintainability
Fast in the cheap places, careful in the expensive ones.
Deciding Under Uncertainty
Bounding the downside and buying information cheaply.
Trade-off Analysis Methods
ATAM, scenarios, and naming the points where qualities conflict.
Technology Selection
Evaluating options against drivers rather than against enthusiasm.
Decision Practice
Thresholds, review, supersession and keeping the log alive.