Search the practice set
126 questions, 454 terms and 400 topics in 20 areas.
59 results for “Serverless vs Containers”
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.
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.
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.
Monolith vs Microservices
A trade of deployment independence against distributed-systems complexity, decided by team topology far more often than by technology.
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.
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.
Serverless
A model where the provider allocates and scales compute per request, and you are billed for execution rather than for provisioned capacity.
Serverless Cold Start
The additional latency when a function invocation must allocate and initialise a new execution environment rather than reusing a warm one.
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.
Container Image
A layered, content-addressed filesystem bundle plus metadata, from which containers are instantiated — immutable by construction and identified by digest.
Dropbox's Move Off S3
Dropbox moved the majority of its file storage off Amazon S3 onto custom infrastructure, reporting savings that its S-1 filing put at roughly $75 million over two years.
Feature Parity Trap
The expectation that a replacement system must match every behaviour of the old one before it can be adopted, which is what makes rewrites never finish.
Image Registry
The store from which container images are pulled, and an under-appreciated availability and security dependency of every deployment and every autoscale event.
Kubernetes
A container orchestrator that continuously reconciles the running state of a cluster towards a declared desired state.
Pod
The smallest deployable unit in Kubernetes — one or more containers that share a network namespace, storage volumes and a lifecycle, scheduled together on one node.
Prime Video's Move Back to a Monolith
Amazon Prime Video consolidated a serverless, distributed audio/video monitoring service into a single process and reported a 90% cost reduction — the most-cited example of micros…
Total Cost of Ownership
The full lifetime cost of a capability, including the people, operations, upgrades and exit that a licence comparison leaves out.
A team wants to build a new internal API on serverless functions. It will serve steady traffic of about 200 requests per second during business hours. What do you advise?
What the interviewer is testing Whether you can apply the serverless trade off to a specific workload rather than treating it as a default good or a default bad
A serverless API works in testing and fails under load with connection errors. The database is at 5% CPU. Explain and fix.
The mechanism Serverless functions scale by creating independent execution environments , each with its own process and its own connection pool. Two hundred con
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
Netflix built its own CDN; Dropbox moved storage off S3. Both are usually wrong. What conditions made them right, and how do you test for those conditions?
What the interviewer is testing Whether you can extract the conditions from a famous decision rather than the decision itself. These two cases are the most comm
Serverless vs Containers
Spiky and event-driven versus sustained throughput.
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.
Centralised vs Distributed
Shared platform leverage against team autonomy.
Containers
Images, registries, immutability and the deployment model they enable.
Cost vs Reliability
Each nine costing an order of magnitude, and pricing the failure instead.
Delivery vs Maintainability
Fast in the cheap places, careful in the expensive ones.
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
Scale to zero, per-request billing, cold starts and connection limits.
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.
Compute Models
Instances, containers and functions, and what each is priced and shaped for.