TOPIC
Operations
These are the same questions found in the library, grouped here by the capability each one mainly examines.
99 questions
Questions 1–50 of 99 on this page.
A · Professional problem solving and implementation13
- A document assistant can submit most cases automatically, but mistakes have very different consequences. Human review has reduced errors, but the queue keeps growing. How would you decide which cases to automate or review, and keep the queue within the team’s capacity?
- A long-running process keeps using more memory, while object counts in heap snapshots fluctuate. How would you use evidence to distinguish a true leak, intentional cache retention, fragmentation, or growth in native memory?
- A new field must be backfilled across hundreds of millions of rows. The first run increases lock waits and replication lag. How would you decide whether to pause, batch, throttle, or use an online migration?
- Producer logs show an event published and the broker acknowledged it. The consumer has no visible error, but the business object did not change. How would you distinguish acknowledgment semantics, dead letters, filters, deserialization, and duplicate handling?
- On-call engineers receive many alerts each day, yet user complaints and service objective violations still go unnoticed. How would you redesign alerting?
- The application can be rolled back, but a database migration removed an old field and the previous version can no longer start. How would you redesign release order and rollback?
- How would you design a platform where operations staff build campaigns and game mechanics themselves? How do you abstract campaigns, mechanics, rules, and features into configurable parts, and how do you keep a configuration correct once it goes live?
- How would you design an invitation-based viral marketing campaign? How do you design invitation relationships, reward payout, abuse prevention, and effect evaluation?
- After AI output causes actual user harm, product, model, operations, and review teams all take part in the response. How would you divide incident handling and follow-up improvement?
- A critical end-to-end test fails intermittently: it passes alone but fails in a parallel suite, and the team has started rerunning it until it passes. How would you determine whether it exposes product risk, isolate shared state, resource contention, clock or ordering dependencies, and improve the test workflow?
- During a cross-time-zone handoff, a critical alert was sent. The outgoing on-call engineer assumed the incoming engineer would handle it, while the incoming engineer never acknowledged it; escalation was delayed. How would you reconstruct the ownership chain, fix acknowledgment and handoff, and verify the change?
- Average latency is stable while p99 worsens, with large differences across tenants. How would you narrow the cause to queuing, lock contention, downstream fan-out, or resource isolation?
- At peak load, the entry service records a request but downstream events are missing, while retries amplify traffic. How would you trace the request through each service to locate loss and duplication?
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B · Business understanding and domain modeling6
- A critical dataset is reused by several products and reports, but no one can explain its sources, owners, or sensitive fields. How would you improve governance without blocking current use?
- An account moves from sales to customer success mid-month. Monthly metrics must show the outcome and who owned it at each point. How would you define ownership events and reporting rules?
- A quality check occasionally produces false alarms and blocks downstream jobs; removing it once let bad data reach settlement. How would you design tiered handling?
- Duplicate registration created two customer entities later confirmed to be the same company. Reports should unify them, while contracts, approvals, permissions, and personal actions must retain original responsibility. How would you model the merge?
- A producer adds an order status, and an old consumer rejects the whole message because enum validation is strict. Teams disagree over who must update, and consumers have different owners. How would you design compatibility and rollout order?
- After a promotion ends, operations considers the campaign complete, product sees orders still being fulfilled, and finance says settlement is not yet possible. How would you define each party’s objects, states, and state transitions?
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C · Value judgment and direction setting9
- Brand advertising, search, and affiliate channels reach overlapping prospects, while the attribution platform assigns most conversions to the last click. How would you estimate each channel’s incremental contribution and state the limits of the conclusion?
- One section of a community has stayed quiet for a long time. How do you judge whether it deserves continued investment or should be shrunk or merged?
- As the industry enters a stock era, the company demands a complete shift from thinking in transaction volume to thinking in net profit. How do you raise net profit by adjusting the take rate and optimizing supply-chain operating costs without triggering large-scale exits or protests from merchants or creators?
- The algorithm team expects an upgraded recommendation model to lift conversion by 3%, but operations would lose the ability to adjust key placements manually. How would you design an experiment and decision rules while accounting for value the experiment cannot measure?
- After the bot upgrade, sessions with no handoff to a human are counted as resolved, and the rate went from 72% to 91%. In the same week the handoff button moved into a submenu and the denominator changed. How do you respond today to the proposal to cancel weekend human coverage?
- Retention rose during a marketing campaign, and the team credits the channel, but a new product flow also launched and participants may already have been more active. How would you establish a credible comparison, estimate the campaign’s net lift, and state the limits of the conclusion?
- The completion rate of a key task fell this week. Before explaining why, in what order do you confirm that the change is real, where it is concentrated, and what cost users bear?
- A dashboard holds dozens of metrics and the team's attention keeps getting pulled to the most visible numbers. Pick one user task and explain how you would tier the metrics and decide which enter the core list.
- The initial effect of a feature is strong but fades over several months. How would you distinguish novelty from lasting behavior change?
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D · Delivery and ongoing operations22
- A data-write incident has stopped and service metrics look normal, but users still report missing records. How would you organize recovery validation and follow-up communication?
- An onboarding experiment does not change overall signup-to-activation conversion, but activated users complete their first key task sooner. How would you decide whether to roll it out and revise the definition of success?
- During a major promotion, landing-page traffic meets expectations but add-to-cart and order rates are far below target. How would you quickly distinguish traffic quality, page information, pricing rules, inventory, and fulfillment issues?
- A limited-time promotion launches, but popular products run short. Some channels have already promised availability while others continue sending traffic. How would you adjust promotion, page promises, replenishment, and customer communication?
- A brand campaign has delivered its planned total impressions, but actual reach among the core target audience is below expectation, and one-third of the budget remains. How would you decide whether to continue, change the media mix, or revise the objective?
- A community event has strong registration and interaction numbers, but participants rarely continue using the product or contributing content afterward. How would you locate where the connection to product value breaks and design the next operating cycle?
- To meet a quarterly goal, a partner asks to expand promotion delivery at short notice. An initial check suggests the new audience may exceed agreed authorization and brand boundaries. How would you move the decision forward within the deadline?
- A campaign creative gets high engagement on social channels but almost no conversion in search or stores. Another version has ordinary engagement but stronger sales. How would you decide on creative iteration and channel allocation?
- A broad discount meets the overall sales target, but valuable existing customers view it as unfair, and some users delay purchases they would have made anyway. How would you adjust future audiences and offers?
- A discount briefly increases volume, competitors follow, and category prices and margins decline. How would you decide whether to keep matching, change the value proposition, or exit the promotion?
- A new product misses its first-week sales target, yet trial users show strong usage depth and referral intent. How would you determine whether the issue is reach, a longer purchase cycle, price threshold, or positioning, and decide what to invest in next?
- A new-customer offer generates many registrations, but most users do not complete the first key action and the discount cost has already been incurred. How would you plan follow-up and decide which users merit further investment?
- A channel has a low acquisition cost in a small test, but lead quality and conversion fall as spend increases. How would you validate the cost definition and true incrementality, distinguish channel saturation from audience or sales-capacity changes, and set a limit for additional spend?
- A campaign brings in many new users, but support, moderation, and plans for following up with users and helping them complete a key action are not ready. How would you design ownership and capacity before and after the campaign?
- Operations staff directly change customer states, and later no one can explain who changed what or why. How would you design for efficiency, permission, and auditability?
- When a payment-risk dependency slows, checkout times out. The business wants to preserve conversion without bypassing critical safety checks. How would you decide which checkout functions can be temporarily disabled and which checks must remain?
- For several quarters, production support, customer escalations, and cross-team requests have displaced roadmap work. Someone proposes a universal 20% reserve, though interruption rates vary. How would you set the reserve?
- A customer asks for “a real-time dashboard,” but their examples suggest they only discover inventory errors later in the day. How would you guide the discussion?
- A campaign goes live overnight, but heavy traffic stalls the system. Users cannot claim coupons and start complaining. As an engineer involved in the campaign, how would you coordinate with operations and support on temporary business measures while restoring the system?
- Describe a re-engagement or referral campaign you contributed to as an engineer. Which systems, data, or delivery work did you own, how did you clarify budget and key user behavior with operations, and how did you verify incremental impact and your actual contribution?
- The promotion strategy is set and you are responsible for execution. What goals, rules, resources, risks, and acceptance criteria would you confirm before launch?
- Sales, support, and engineering can all label customer issues top priority, so the queue cannot distinguish business outages from general dissatisfaction. How would you design severity and escalation?
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