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126 questions, 454 terms and 400 topics in 20 areas.
60 results for “Centralised vs Distributed”
Monolith vs Microservices
A trade of deployment independence against distributed-systems complexity, decided by team topology far more often than by technology.
Active-Active vs Active-Passive
Whether all regions serve traffic simultaneously, or one serves while another waits to take over — a choice about which failure mode you would rather have.
Build vs Buy
The choice between developing a capability in-house and acquiring it, decided on differentiation and total cost rather than on feature lists.
Containment vs Eradication
Stopping an attacker's ongoing access versus removing their foothold entirely — sequential phases with different urgency and different risks of doing them wrong.
Cost vs Reliability Trade-off
The non-linear relationship between availability and spend, which makes each additional nine roughly an order of magnitude more expensive.
Delivery vs Maintainability
Choosing where to take deliberate shortcuts, based on which kinds of debt are cheap to repay and which compound.
Distributed Tracing
Following one logical request across every service it touches by propagating a shared trace identifier and recording timed spans.
Durability vs Availability
Two different storage guarantees — whether data survives, and whether it can be reached right now — routinely conflated because both are quoted in nines.
ETL vs ELT
Whether data is transformed before loading into the target or after it, which decides where the compute happens and how much raw history you keep.
Fail-Fast vs Fail-Safe
Whether a component should stop immediately on detecting a problem, or continue in a degraded but safe mode — a choice that depends entirely on which outcome is worse.
Horizontal vs Vertical Scaling
Adding more machines versus making one machine bigger — and the fact that vertical is underrated for stateful tiers.
Layer 4 vs Layer 7 Load Balancing
Balancing on connection metadata (IP and port) versus on the content of the request (path, host, headers).
Managed vs Self-Managed
Trading control, portability and unit cost against the operational burden of running the thing yourself.
OLTP vs OLAP
Two workload shapes with opposite requirements — many small indexed transactions versus few large scans and aggregations — which is why they belong in different stores.
Operational vs Analytical Store
The separation between the store serving the application's transactions and the one serving reporting and analysis, and the mechanism connecting them.
Provisioned vs Serverless Capacity
Paying for a fixed database size continuously, versus paying for capacity consumed with automatic scaling — a crossover decision driven by duty cycle.
Re-architect vs Rebuild
Restructuring an existing system incrementally versus writing a replacement from scratch — and the strong evidence that incremental wins.
SQL vs NoSQL
A choice driven by access patterns, consistency requirements and query flexibility — not by data volume, which is the reason usually given.
Security vs Usability
A trade-off that is usually resolved by varying the control with the value of the action, rather than by choosing a uniform level of friction.
Strong vs Eventual Consistency
A per-operation decision, not a per-system one: whether this specific read must reflect every completed write.
Synchronous vs Asynchronous Communication
Whether the caller waits for the callee's answer — decided by whether the caller's outcome depends on it, not by latency or taste.
Synchronous vs Asynchronous Replication
Whether a write is acknowledged only after a replica has it, trading write latency against the amount of data a failure can lose.
Zonal vs Regional Services
Whether a cloud resource lives in one availability zone or is inherently spread across several — a property that determines what a zone failure takes with it.
At-Least-Once Delivery
The guarantee that a message will be delivered, possibly more than once — the practical default in every distributed messaging system.
Atomic Commit Protocol
Any protocol ensuring that several participants reach the same decision to commit or abort — and a problem provably unsolvable with certainty in an asynchronous system with failures.
A nightly job occasionally runs twice, producing duplicate charges. The team proposes a distributed lock. What do you say?
The first response A lock will reduce the frequency and will not eliminate it , and if the team believes otherwise they will stop looking for the real fix. The
Placing an order must reserve stock, charge the card and create a shipment across three services. Design it, and justify why not a distributed transaction.
First: question the boundary A transaction spanning three services often means one invariant has been split across three owners. Before designing a protocol, ch
Prime Video reported a 90% cost cut by consolidating a serverless distributed service into one process. Does that mean microservices were the wrong choice, and what is the actual decision rule?
What actually happened The Prime Video Video Quality Analysis team's 2023 post describes an audio/video monitoring service built as Step Functions orchestrating
Three designs need distributed locks: a nightly report, a per-customer state machine, and a global config reload. For each, is a lock the right answer?
The nightly report — a lock is acceptable Purpose: efficiency . Two instances generating the same report wastes compute and possibly sends two emails, but nothi
A 43-second network partition caused GitHub over 24 hours of degraded service in 2018. How does a 43-second event become a day-long incident?
The case, as publicly reported On 21 October 2018, routine maintenance replacing failing optical equipment caused a 43 second loss of connectivity between GitHu
A card payment authorisation service runs active-active across two regions. A network partition splits them. Do you keep accepting authorisations, and what breaks either way?
What the interviewer is testing Whether you can apply CAP to a domain where the cost of each choice is concrete, and whether you recognise that "it depends" has
A downstream service slows from 50 ms to 3 s. Within two minutes every service in the request path is down, including ones that do not call it. Explain the mechanism and how you would have prevented it.
What the interviewer is testing Whether you understand that most outages are amplification, not failure — and whether you can name the specific mechanism rather
An order service must notify inventory, billing, shipping and analytics when an order is placed. Synchronous calls or events? Justify your choice per consumer.
What the interviewer is testing Whether you apply the decision per interaction rather than adopting one style globally. The framing that matters Synchronous cal
Centralised vs Distributed
Shared platform leverage against team autonomy.
Build vs Buy
Differentiation versus table stakes, priced over five years.
Build vs Buy
Differentiation, five-year TCO, and the exit cost of each option.
Cost vs Reliability
Each nine costing an order of magnitude, and pricing the failure instead.
Debugging Distributed Systems
Localising a regression when every service reports healthy.
Delivery vs Maintainability
Fast in the cheap places, careful in the expensive ones.
Distributed Locking
Mutual exclusion across machines, and why it is harder than it looks.
Distributed Systems
General material on partial failure, coordination and distributed reasoning.
Distributed Tracing
Reconstructing one request's path across every service it touched.
Distributed Transactions
Two-phase commit, its blocking failure mode, and when it is still reasonable.
Functional vs Non-Functional
Behaviour versus quality of behaviour, and why only the second constrains structure.
Horizontal vs Vertical Scaling
Scale out for stateless, scale up first for stateful.
Layer 4 vs Layer 7
Connection-level versus request-level balancing, and what each unlocks.
Managed vs Self-Managed
Trading control and unit cost against operational attention.
Monolith vs Microservices
A team-topology decision far more often than a technology one.
Orchestration vs Choreography
A coordinator that knows the flow, or services that react to events.
Performance vs Cost
Buying latency, and knowing what the last millisecond is worth.
Rebuild vs Re-architect
Why greenfield replacement fails, and the narrow cases where it does not.
Reliability vs Complexity
Mechanisms that add availability and add failure modes.
SQL vs NoSQL
Decided by access patterns and query flexibility, not by data volume.
Security vs Usability
Varying control by the value of the action rather than uniformly.
Serverless vs Containers
Spiky and event-driven versus sustained throughput.
Single vs Multi-Region
Driven by RTO, RPO and residency rather than by ambition.
Strong vs Eventual Consistency
A per-operation decision, resolved by what a stale read would cost.
Sync vs Async
Whether the caller's outcome depends on the callee's response.
AI Gateways
Centralised routing, keys, quotas, caching, logging and safety policy.