Load Shedding
Rejecting some work deliberately so the rest can be served correctly.
6 to work through
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intermediate
Define the degradation ladder for an e-commerce site under extreme load. What is shed, in what order, and who decides?
2 min answer -
advanced
A fantasy-sports platform faces a synchronised traffic spike in the minutes before a major match starts. Workers are saturated. What should be shed, in what order, and what must never be shed?
2 min answer -
advanced Multiple choice
An AI inference service receives computationally expensive requests with unpredictable bursts, where a single request can occupy a GPU for many seconds. Which combination of controls should it use, and in what order do they apply?
2 min answer -
advanced
One customer's batch job saturates a shared service and degrades everyone. Rate limiting them fixes it, until the next customer does the same. What is the structural answer?
2 min answer -
advanced
Your service is at capacity and must reject some traffic. What do you shed, and how do you decide?
2 min answer -
advanced
Your service will exceed capacity by 30% during a known peak. Do you shed load or brown out, and how do you decide what goes first?
2 min answer
6 terms in this topic
Admission Control
Deciding at the entrance whether to accept a request at all, based on whether the system can complete it within its deadline.
patternBrownout
Deliberately reducing the quality or completeness of every response under load, rather than serving some requests fully and rejecting others.
case-studyCloudflare 2019: One Regex, Global Outage
A firewall rule containing a regular expression with catastrophic backtracking consumed CPU across Cloudflare's entire global network within seconds …
patternLoad Shedding
Deliberately rejecting a portion of incoming work so the system continues serving the remainder at acceptable latency, rather than degrading for everyone.
patternPriority Load Shedding
Dropping traffic by declared business criticality under stress rather than uniformly or randomly, exploiting the fact that the highest-volume request…
patternPriority Queueing
Classifying requests by business importance so that overload sheds the least valuable work first rather than an arbitrary slice.
Neighbouring topics
Distributed Systems
General material on partial failure, coordination and distributed reasoning.
CAP & PACELC
What you must give up during a partition, and the latency choice the rest of the time.
Consistency Models
Linearizable, sequential, causal, eventual, and the session guarantees between them.
Idempotency
Making an operation safe to repeat, because a client that times out cannot know.
Retries & Backoff
Exponential backoff, jitter, retry budgets, and how retries become the outage.
Timeouts & Deadlines
Per-hop timeouts that do not compose, and the deadline budget that replaces them.
Circuit Breakers
Failing fast on a broken dependency, and what you fail fast to.
Backpressure & Flow Control
Telling callers to slow down instead of buffering into congestion collapse.
Bulkheads & Isolation
Partitioning resources so one dependency cannot starve the others.
Leader Election
Agreeing who is in charge, and fencing the one who no longer is.
Consensus Protocols
Raft, Paxos and quorums — what they guarantee and what they cost.
Distributed Locking
Mutual exclusion across machines, and why it is harder than it looks.
Distributed Transactions
Two-phase commit, its blocking failure mode, and when it is still reasonable.
Sagas & Compensation
Replacing atomicity with semantic undo, and ordering the irreversible steps last.
Service Discovery
Finding a healthy address for something whose instances are ephemeral.
Messaging & Queues
Decoupling producer from consumer, and the semantics that come with it.
Event Streaming
Retained ordered logs, consumer offsets, partitions and replay.
Clocks & Ordering
Why wall clocks lie, and how logical clocks and versions restore order.
Failure Modes
Slow rather than down, partial, grey, and failing while reporting success.