Elixir engineer behavioral interview questions

As asked

Tell me about a time you had to diagnose and fix a critical issue in a production Elixir system with limited information. What tools did you use, how did you narrow down the cause, and what did you change to prevent recurrence?

Sample answer outline

A strong answer follows the STAR format, uses specific Elixir/BEAM tools (:observer, recon, Telemetry dashboards, logs), describes a systematic narrowing process (not random guessing), and ends with a concrete change: added a metric, fixed a supervision tree, added back-pressure, or added a test that would have caught the issue.

Expect these follow-ups

• How did you communicate the incident status to stakeholders while still debugging?
• What would you have done differently if you had more preparation time before the incident?

As asked

Describe a situation where an Ecto query was causing performance problems in production. How did you identify it, what was the root cause, and how did you fix it?

Sample answer outline

A strong answer identifies the query via slow query logs or EXPLAIN ANALYZE, names the root cause (missing index, N+1, sequential scan, large join result), and describes the fix with the measurable outcome. Bonus points for mentioning they added a test or monitoring to catch regressions.

Expect these follow-ups

• How do you evaluate whether adding a database index is worth the write overhead?
• Did you consider caching as an alternative to query optimization? Why or why not?

As asked

Tell me about the most complex supervision tree you have designed. What processes did it manage, how did you decide on restart strategies, and what went wrong that you had to fix afterward?

Sample answer outline

A strong answer describes specific supervised processes (workers, pools, connection managers), explains the reasoning for strategy choices (not just listing them), and honestly discusses a design flaw discovered in production and how the tree was restructured. Shows understanding that supervision design is iterative.

Expect these follow-ups

• How did you test the supervision tree's failure recovery behavior before deploying?
• Were there any processes you considered not supervising? Why?

As asked

Describe a time you helped a colleague who was new to OTP or Elixir understand a concept they were struggling with. What was the sticking point and how did you explain it?

Sample answer outline

A strong answer gives a specific concept (e.g., why processes are not threads, why 'let it crash' is a deliberate design choice, or how supervision differs from try-catch), describes the analogy or example used, and shows awareness that the concept was genuinely counterintuitive for someone coming from OOP or imperative backgrounds.

Expect these follow-ups

• Did that person later apply the concept on their own? How did that go?
• What resource or exercise would you recommend for someone first learning OTP?

As asked

You joined a project where the production system had almost no monitoring. Describe how you prioritized and introduced observability, what you instrumented first, and how you got buy-in from the team.

Sample answer outline

A strong answer starts with highest-impact metrics first (error rates, latency, queue depths), uses Elixir's telemetry library to instrument incrementally, and shows how early wins (catching a real bug with the new metrics) built team buy-in. Mentions connecting Telemetry to a concrete dashboard (PromEx + Grafana or AppSignal) rather than just emitting events with no consumer.

Expect these follow-ups

• How did you decide which processes or endpoints to instrument first?
• Did introducing monitoring change how the team behaved during incidents?

As asked

Describe a project where you improved deployment reliability for an Elixir application. What was the previous deploy process, what problems did it cause, and what did you implement to fix it?

Sample answer outline

A strong answer identifies the problem (downtime on restart, lost WebSocket connections, in-flight requests dropped), describes the solution (blue-green deploys, rolling restarts via Kubernetes, graceful shutdown with Plug.Cowboy drain, short-circuit breakers for in-flight work), and gives a measurable outcome (deploy time, error rate during deploy).

Expect these follow-ups

• How did you handle database migrations that needed to be backward-compatible during a rolling deploy?
• How did you test the graceful shutdown behavior before deploying it?

As asked

Tell me about a time you inherited or built a GenServer that had grown too large and was doing too many things. How did you approach breaking it apart, and how did you maintain correctness during the refactor?

Sample answer outline

A strong answer identifies the symptoms of a God GenServer (too many callbacks, hard to test, long message queue), describes the decomposition strategy (separate concerns into multiple GenServers, use ETS for shared read state, delegate sub-domains to separate modules), and explains how tests were maintained throughout (characterization tests before refactor, new unit tests after).

Expect these follow-ups

• How did you coordinate the split across a running system without taking downtime?
• What signals would you watch for to know when a GenServer is getting too large again?

As asked

Have you migrated an existing JavaScript-heavy frontend to Phoenix LiveView? Walk me through what you kept in JS, what you moved to LiveView, and what trade-offs the team debated.

Sample answer outline

A strong answer discusses what LiveView cannot replace (complex client-side interactions requiring offline support, third-party widget integrations), and names specific things moved successfully (data tables, form flows, real-time dashboards). Discusses the trade-offs of reduced client complexity versus WebSocket dependency, and how the team evaluated user experience impact.

Expect these follow-ups

• How did you handle LiveView's initial page load performance compared to the SPA?
• Were there any features you had to defer or abandon because LiveView could not support them well?

As asked

Tell me about a technical decision where your team disagreed on whether to use a GenServer or ETS for shared state. How did you evaluate the options and what did you decide?

Sample answer outline

A strong answer frames the GenServer as simpler and safer (serialized access, ownership) versus ETS as higher-throughput for reads but requiring care around concurrency and ownership. Discusses the actual access pattern of the use case (read ratio, write frequency, contention) as the deciding factor, and shows that the decision was data-driven rather than opinion-driven.

Expect these follow-ups

• Looking back, was the decision correct? What would you change?
• How did you test that the chosen approach performed as expected under load?

As asked

Tell me about a time you recommended Elixir for a project where it was not the obvious default choice. How did you build the case, and how did you address concerns from stakeholders who were unfamiliar with the ecosystem?

Sample answer outline

A strong answer frames the technical fit (concurrency model, fault tolerance, real-time requirements) and addresses the practical concerns honestly (smaller hiring pool, fewer libraries, learning curve). Shows ability to separate personal preference from objective fit, and mentions how they planned to mitigate ecosystem risks (training, library evaluation, fallback plan).

Expect these follow-ups

• Were there requirements where Elixir was actually a worse fit than the alternatives?
• How did you manage the onboarding of team members who had never written Elixir?

As asked

Describe a time a BEAM node crashed unexpectedly in production. What was the impact, how did you investigate the crash dump, and what did you do to prevent it from happening again?

Sample answer outline

A strong answer describes using the erl_crash.dump file with crashdump_viewer or the online analyzer, identifying the root cause (atom table exhaustion, memory pressure, long-running NIF, scheduler lockup), and applying a fix targeting the root cause. Also discusses alerting and runbook improvements made to respond faster next time.

Expect these follow-ups

• What monitoring would have caught the symptom before the crash?
• How do you set atom table and process count limits safely for a production node?