Search the practice set
275 questions, 991 terms and 600 topics in 30 areas.
60 results for “Change Management vs CD”
Standard Change
A pre-authorised class of change whose risk controls are automated and evidenced, so it does not need per-instance approval.
Focus Management
Deliberately controlling where keyboard focus sits after an interface change, which is what makes a dynamic application usable without a mouse.
Deployment Pipeline
The automated path from commit to production, structured so that each stage increases confidence and the whole is fast enough to be run on every change.
Device Group Rollout
Applying configuration or firmware to a fleet in ordered cohorts with health checks between them, because a bad change applied to everything at once has no remedy.
Evidence Based Approval
Replacing a human judgement about whether a change is safe with a machine-produced record of the checks it passed, assessed once for the class rather than per instance.
Prompt Registry
A versioned store of production prompts with their model bindings, parameters and evaluation results, so a prompt change is a reviewable, traceable, reversible deployment.
Prompt Regression Suite
A set of test cases with expected properties, run against a prompt on every change, to detect quality regressions before deployment.
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.
Application Portfolio Management
Maintaining an inventory of every application with its owner, cost, business value and technical health, and using it to decide what to invest in, replace or retire.
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.
CI/CD
Merging work continuously into a shared trunk with automated verification, and keeping every commit in a state that could be released.
Change Data Capture
Publishing a stream of a database's row-level changes by reading its replication log, without modifying the application that owns it.
Change Failure Rate
The proportion of deployments that cause a production failure requiring remediation, and the DORA metric that keeps the others honest.
Consent Management
Capturing, storing, honouring and evidencing a data subject's permissions for specific processing purposes, including withdrawal.
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.
Event Notification vs Event-Carried State
Whether an event carries only the fact that something happened, or also the data a consumer needs to act on it.
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.
Global Traffic Management
The layer that decides which region a given user reaches, using DNS, anycast or an edge network, and that performs regional failover.
Horizontal vs Vertical Scaling
Adding more machines versus making one machine bigger — and the fact that vertical is underrated for stateful tiers.
Identity and Access Management
The system of record for principals, credentials and permissions, and the policy engine that decides what each principal may do.
A service has widely varying request costs — most complete in 10 ms, some take 5 s. Under round robin some instances are overwhelmed while others idle. What do you change?
Why round robin fails here It distributes by count , not by cost or by whether a backend is coping. With uniform requests that is fine. With a 500× cost spread,
A team's CI suite fails roughly one run in three for reasons unrelated to the change. Everyone reruns until green. How do you recover the situation?
Recognise what has actually been lost The suite is no longer a gate. Once the team's reflex on red is "rerun", that reflex is applied to genuine failures too, a
A CDC pipeline feeding your warehouse falls three hours behind during a source system's batch job, and the source's transaction log retention is 24 hours. What is the risk and what do you change?
The immediate risk Lag consumes the retention window. At three hours behind against a 24 hour retention, you have 21 hours of margin. If the consumer stops enti
A client wants an assistant that answers questions from 50,000 internal documents which change weekly. RAG or fine-tuning? What actually determines the quality?
What the interviewer is testing Whether you understand what each technique actually does, and whether you know that RAG quality is a retrieval problem. Why RAG
A front-end team wants to replace their global state library because "state management is unmanageable". How do you evaluate the request?
Ask what is actually in the store The complaint almost always resolves to one distinction not having been made: server state versus UI state . Server state is d
A quarterly board report shows a category down 40%. Investigation finds an upstream system stopped sending a field three months ago. Nothing alerted. What do you change?
Understand why nothing fired The pipeline completed successfully every night. It read the source, applied its transformation, and wrote rows — all of which is w
A service's p99 latency has tripled over three months with no single obvious change. How do you investigate?
Establish the shape before touching anything Is it everything or something? Break the metric down by endpoint, tenant, region, instance and version. A tripling
A team proposes exposing their service's database change stream via CDC so other teams can consume it, avoiding the work of building an event API. What is your assessment?
Name what is actually being proposed The proposal is to publish the service's internal schema as its integration contract. CDC does not emit domain events; it e
A transformation project has grown to 600 models with chains twelve deep. A change at the base has an unknowable blast radius. What do you do?
Treat it as a software architecture problem, because it is one Six hundred models with twelve deep chains is a codebase with no module boundaries. The remedies
An order service publishes events consumed by six teams. Every consumer immediately calls back for order details. What is wrong and what do you change?
The failure Thin notification events ("order 123 changed") produce a callback stampede : every event triggers six synchronous calls back to the producer, and th
Design the network layout for a three-tier application in one cloud region. What are the decisions you cannot easily change later?
What the interviewer is testing Whether you know which network decisions are cheap and which are effectively permanent. This is a knowledge question with a clea
During an incident an engineer edits a live Kubernetes resource and the change is reverted a minute later by the GitOps controller. The incident continues. What is your position?
The controller behaved correctly Continuous reconciliation is the property that makes drift impossible and makes the repository an accurate description of the e
Change Management vs CD
Reconciling CAB-era controls with continuous delivery without pretending either away.
Change Advisory vs Automated Gates
Replacing a weekly board with evidence a machine produces on every change.
Database Migration Under CD
Expand-contract, backwards-compatible schema change, and migrations that cannot roll back.
AI Cost Management
Token accounting, routing, caching and the context-window budget.
Application Portfolio Management
Inventory, ownership, cost and health for every application.
Artifact Management
Immutable versioned outputs, promotion between repositories, and retention policy.
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.
CI/CD
Continuous integration and delivery, and the architecture that caps them.
Centralised vs Distributed
Shared platform leverage against team autonomy.
Change Data Capture
Turning a database's replication log into a stream, and its coupling risk.
Control Design vs Operation
A control that is well designed and never runs fails exactly like one that is absent.
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.
Erasure vs Immutability
Deletion obligations against event logs, backups and ledgers designed never to forget.
Exception & Waiver Management
Time-boxed, owned deviations with a remediation date, rather than permanent silence.
Flaky Test Management
Quarantine, detection, and the trust a suite loses once red stops meaning broken.
Fleet Management
Inventory, health, configuration and grouping across devices you will never see.
Functional vs Non-Functional
Behaviour versus quality of behaviour, and why only the second constrains structure.
Guardrails vs Gates
Preventing a class of mistake automatically versus stopping to ask a human.
Horizontal vs Vertical Scaling
Scale out for stateless, scale up first for stateful.
Identity & Access Management
Workload identity, roles, permission boundaries and usage-based review.