Search the practice set
275 questions, 991 terms and 600 topics in 30 areas.
60 results for “Self-Service Provisioning”
Provisioning Self-Service
Teams obtaining infrastructure without a ticket, within bounds that make the request safe by construction rather than by review.
Governed Self-Service
Letting anyone analyse anything while constraining what may be treated as authoritative, which resolves the apparent conflict between speed and consistency.
Managed Service
A capability the provider operates — provisioning, patching, backup, scaling and failover — leaving you the configuration and the data.
Managed Service Substitution
Replacing a self-managed component with a managed equivalent during migration, without changing the application's architecture.
Developer Portal
The self-service surface where consumers discover APIs, read documentation, obtain credentials and test calls — the main determinant of adoption.
JSON Web Token
A signed, self-contained token carrying claims, which a service can validate locally without calling the issuer.
Operational Burden Assessment
Quantifying the ongoing engineering effort a self-managed component requires, so it can be compared honestly with a managed service's price.
Airbnb's Service-Oriented Migration
Airbnb decomposed a large Rails monolith by first extracting a unified data-access layer, so that services were built on owned data rather than on shared database tables.
Cross-Service Debugging
Investigating a failure that spans multiple services by moving between traces, logs, metrics and profiles along a single correlated request.
Database per Service
Each service owning its own datastore, with no other service reading or writing it directly.
Managed Service Upgrade Window
The period during which a provider may apply patches or version upgrades to a managed service, usually involving a failover or brief unavailability.
Managed vs Self-Managed
Trading control, portability and unit cost against the operational burden of running the thing yourself.
Service Boundary
The line separating what one service owns and is accountable for from what it must ask another service about.
Service Catalogue Entry
The record that makes a service a first-class object in the platform — owner, dependencies, docs, runbooks and health in one place with a single identity.
Service Control Policy
An organisation-level guardrail that limits what any identity in an account may do, regardless of the permissions granted within that account.
Service Discovery
The mechanism by which a caller finds a currently healthy network address for a service whose instances are ephemeral.
Service Level Agreement
A contractual commitment about service level, with a defined remedy — usually a service credit — when it is missed.
Service Level Indicator
The actual measurement of a service's behaviour that an objective is set against — a ratio of good events to valid events.
Service Level Objective
An internal target for a service level indicator, set below the level at which users notice, and used to decide whether to ship or to stabilise.
Service Mesh
An infrastructure layer of sidecar proxies that handles service-to-service networking — mTLS, retries, timeouts, routing, telemetry — outside the application.
Your platform team is now a ticket queue — every environment, every permission, every new service goes through them. How do you get out of it?
Categorise the queue before automating anything Take a month of tickets and group them. The distribution is always uneven, and two or three categories are usual
A team wants to self-manage Kafka on Kubernetes to save money against the managed service. Evaluate.
The comparison they have probably made Instance cost versus managed service list price. That comparison usually favours self managing by a wide margin, and it o
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
A downstream team needs to react to order changes. The order service can publish events, or they can consume CDC from its database. Which, and why?
The recommendation: published events, with CDC as the mechanism if needed The distinction that matters is what the consumer becomes coupled to . CDC consumed di
A global SaaS product has a 200 ms p95 API budget. Users in Sydney see 900 ms against a single US-East deployment. The application team says the service responds in 40 ms. Who is right and what do you do?
Both are right, and that is the point The service does respond in 40 ms. The other 860 ms is network — and no amount of application profiling will show it, whic
A new platform must serve a public partner API, three internal front-ends with different data needs, and high-volume service-to-service traffic. Choose the API styles and defend the choice.
Resist "pick one" These are three different problems with three different consumers. Standardising on one style optimises for architectural tidiness at the expe
A platform team proposes adopting a service mesh for 40 services. Make the case for and against, then decide.
What it genuinely provides mTLS everywhere, with automated certificate rotation. This is usually the deciding factor. Doing mTLS by hand means short lived certi
A service autoscales on CPU. During incidents it never scales out, even as latency triples. Why, and what would you scale on instead?
Why CPU never triggers The service is latency bound, not compute bound. Its threads are waiting — on a database, a downstream API, a lock, or a connection pool
A service becomes unresponsive during an incident in a dependency it barely uses. Investigation finds the client had no read timeout. Explain the full mechanism.
The mechanism, step by step 1. The dependency slows. It has not failed — it accepts connections and eventually responds, just very slowly. This is the important
A service calls four dependencies. How do you size its thread pools, and why is the total often smaller than people expect?
The sizing rule Little's Law, per dependency: concurrency = throughput to that dependency × its latency. Dependency Calls/s Latency Concurrency Pool Auth 500 10
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 service intermittently times out connecting to a managed database. The database is healthy, nothing changed, and failures correlate with traffic volume. Where do you look?
The likely cause NAT gateway port exhaustion. Source NAT maps each outbound connection to a source port on the gateway's address. The number of simultaneous con
A service writes to its database and then publishes an event to Kafka. Sometimes consumers see an event for a record that does not exist, and sometimes a record exists with no event. Why, and how do you fix it?
What the interviewer is testing Recognition of the dual write problem — one of the most common defects in event driven systems and one that testing rarely catch
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 is launching a new service and asks what its SLO should be. How do you help them decide, and why is "99.99%" usually the wrong first answer?
What the interviewer is testing Whether you treat reliability as a cost benefit decision with a budget, or as a virtue to maximise. Why not four nines It costs
A team proposes CQRS with event sourcing for a new service. How do you evaluate the proposal?
Separate the two, because they are independent decisions CQRS is separating the write model from the read model. Event sourcing is storing state as a sequence o
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 wants event sourcing for a new order service, citing audit requirements. What do you recommend?
The recommendation: probably an audit log, not event sourcing If the requirement is audit , event sourcing is a very expensive way to obtain it. An append only
After a five-minute network outage at your ingest tier, 200,000 devices reconnect simultaneously and the authentication service collapses. How do you fix this?
The mechanism Every device detected the disconnection at roughly the same moment and retried immediately. Reconnection is the most expensive operation in the fl
After moving a service behind a VPN to an on-premises system, small API calls succeed and large responses hang indefinitely. Walk through the diagnosis.
What the symptom tells you Size dependent failure with a working handshake is a very specific signature. The connection establishes, so routing, firewall rules,
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
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
An order spans payment, inventory and shipping, each in its own service with its own database. How do you keep them consistent?
Rule out the distributed transaction Two phase commit gives atomicity and isolation across services, and its costs make it unusable at scale: locks held across
Design rate limiting for a multi-tenant API where a single customer's traffic spike currently degrades service for everyone.
Name the problem precisely This is the noisy neighbour problem. Rate limiting is one control for it, and on its own it is incomplete — a customer within their l
In an order saga, the shipment service permanently rejects an order after the card has been captured. What now?
What this actually is A step after the pivot has failed permanently , which is the case saga design is supposed to make rare and cannot make impossible. Everyth
One customer's batch job saturates a shared service and degrades everyone. Rate limiting them fixes it, until the next customer does the same. What is the structural answer?
Why per customer rate limits keep failing A static limit is set from what that customer was doing, not from what the service can serve. It is reactive — you dis
One service restarts unpredictably; another is slow with low CPU. Both run on Kubernetes. What are you looking at?
The two symptoms map to the two resource behaviours Unpredictable restarts → OOM kill. Memory is incompressible: a container exceeding its memory limit is kille
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
Run a threat model on a new payment integration: our service calls a third-party payment provider and receives webhooks. Where are the interesting threats?
Draw the boundaries first Three trust boundaries, and nearly every interesting threat lives on one of them: 1. User → our service (untrusted input, authenticate
Self-Service Provisioning
Teams getting infrastructure without a ticket, and the guardrails that make that safe.
Self-Service vs Governed
Letting analysts move fast without four teams reporting four different revenues.
Device Provisioning
Getting identity and configuration onto hardware at manufacture or first boot.
Managed vs Self-Managed
Trading control and unit cost against operational attention.
Service Boundaries
Drawing lines along change patterns rather than technical layers.
Service Discovery
Finding a healthy address for something whose instances are ephemeral.
Service Mesh
Sidecars applied estate-wide, and the scale at which that pays.
Service Mesh Networking
Sidecar proxies supplying mTLS, retries and traffic policy.