Cache Invalidation
Stampedes, penetration, staleness windows and versioned keys.
3 to work through
-
intermediate
A product catalogue is cached with a 10-minute TTL. Merchandisers complain that price changes take 10 minutes to appear. What do you propose?
2 min answer -
advanced
A retail platform's cache layer becomes unavailable during a high-traffic sale and all traffic lands on the primary database. What design prevents a cache outage from becoming a database outage?
2 min answer -
advanced
An edge platform can invalidate cached content either by short TTLs or by explicit purge on publish. Compare the two, and explain when a hybrid is required.
2 min answer
2 terms in this topic
Cache Penetration
Repeated lookups for keys that do not exist, which miss the cache every time by definition and pass straight through to the store.
practiceCache-Loss Survivability
Designing so that losing the cache degrades the system rather than destroying it - because a cache absorbing most of the read traffic is a capacity d…
Neighbouring topics
Data Architecture
General material on structuring, storing and governing data.
Relational Modelling
Normalisation, keys, constraints and the invariants a schema enforces.
NoSQL Stores
Key-value, document, wide-column and graph — what each buys and forbids.
Indexing
Designing indexes per query shape, and paying for them on every write.
Query Optimisation
Reading a plan, fixing statistics, and finding the real bottleneck.
Transactions & Isolation
ACID, isolation levels, and the anomalies each level permits.
Replication
Primaries, replicas, lag, and synchronous versus asynchronous durability.
Partitioning & Sharding
Splitting data across machines, and the one-way door of a partition key.
Caching Strategies
Cache-aside, read-through, write-through and where each belongs.
CQRS
Separating the write model from the read models that serve queries.
Event Sourcing
Storing the change log as the system of record, and what that costs forever.
Change Data Capture
Turning a database's replication log into a stream, and its coupling risk.
Data Warehousing
Dimensional modelling, star schemas and analytical workloads.
Data Lakes & Lakehouses
Open formats on object storage with transactional metadata on top.
ETL & ELT
Where transformation happens, and how much raw history you keep.
Streaming Data
Windowing, watermarks, late arrivals and exactly-once semantics.
Data Governance
Ownership, lineage, quality, catalogues and who may see what.
Data Lifecycle & Retention
How long data is kept, where it ages to, and how it is actually deleted.
Polyglot Persistence
Choosing a store per workload, and the operational cost of variety.