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275 questions, 991 terms and 600 topics in 30 areas.
60 results for “Change Advisory vs Automated Gates”
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.
Standard Change
A pre-authorised class of change whose risk controls are automated and evidenced, so it does not need per-instance approval.
Automated Release Verification
A gate that compares the new version's live signals against the old one's and decides, on stated criteria, whether to continue or revert.
Definition of Done
The agreed, explicit conditions under which work is finished, which functions as a quality gate only when it is automated and non-negotiable.
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.
Preventive Control Placement
Choosing where in the lifecycle a control acts — at authoring, at admission or after the fact — which determines both its strength and its cost.
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.
Advisory Review Model
Running architecture review as a consulting service that improves designs rather than as an approval gate that permits them.
Automated Accessibility Coverage
The proportion of accessibility criteria a tool can decide mechanically — around a third — and the explicit acknowledgement that the rest needs people.
Automated Governance
Encoding architectural rules as executable checks in the build pipeline, so conformance is verified continuously rather than reviewed periodically.
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.
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.
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.
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.
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 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 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 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 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
A vendor SaaS product embeds a model that scores customers, and its output drives an automated decision in your process. Your model governance framework covers models you build. What do you do?
The obligation does not transfer with the outsourcing You are accountable for the decision. That the scoring is performed by a vendor changes who operates the m
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
Integration failures between 30 services are found in a shared staging environment, days after merge. Propose a change.
Why the current model fails A shared staging environment is a serialised, high latency feedback channel . Failures are found late, attribution is ambiguous (who
Change Advisory vs Automated Gates
Replacing a weekly board with evidence a machine produces on every change.
Change Management vs CD
Reconciling CAB-era controls with continuous delivery without pretending either away.
Guardrails vs Gates
Preventing a class of mistake automatically versus stopping to ask a human.
Deployment Gates
Automated verification between stages, and the difference between a gate and a delay.
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.
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.
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.
Kappa vs Lambda
One pipeline replayed versus two pipelines reconciled, and the maintenance each carries.
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.