HashiCorp Infrastructure as Code & Configuration interview questions

Four commands, and the interesting one is plan, because it is the only point where you see the three-way comparison Terraform is actually making before anything changes.

The Terraform question that actually filters. Everyone knows both meta-arguments exist; the answer is about how state addresses resources, and why an index is a fragile key.

Everyone can say state maps config to reality. The follow-up that separates candidates is what else is in the file, and what that means for who may read it.

Everyone answers state locking. The follow-up is what happens when locking is not configured, and what you do with a stale lock at 2am, which is where the answer gets real.

State layout needs an access boundary. Separate environment credentials and restrict who can assume them; a directory name cannot contain a mistaken apply.

The services-market question that decides who can actually run a migration. Import is the easy part; the hard parts are resource-for-resource fidelity and proving the first plan is empty.

Drift is a governance problem wearing a tooling costume. Detection is easy; the scored content is attribution (who changed it and why) and the policy decision that most teams avoid making.

Extract too early and you maintain a wrapper nobody thanks you for. Here is the extraction trigger, the semver contract that maps onto Terraform surfaces, and the parallel-release path for breaking changes.

Everyone recites that depends_on forces ordering. The stronger half of the answer is the graph you never see: implicit edges from references, why file layout orders nothing, and what explicit edges cost.

HashiCorp calls provisioners a last resort and expects you to say why in concrete terms: tainted resources, invisible drift, SSH reachability. Then name what replaces each legitimate use.

The table is half the answer. The other half is who holds credentials, who repairs a stuck lock at night, and why the boring option usually wins until RBAC demands grow teeth.

sensitive = true stops the echo, not the storage. The complete answer walks the value through git, plan artifacts, state, and provider side effects, naming which mitigation closes which leak.

A green plan is evidence, not proof. Build the pyramid: lint in seconds, policy on every PR, real-cloud verification only where shared modules and money justify the burn.

One ForceNew attribute turns an edit into a destroy. Know the schema mechanics, the four lifecycle levers, and why create_before_destroy trades downtime for name collisions.

Three lifecycle arguments influence replacement and drift handling: create_before_destroy, prevent_destroy, and ignore_changes. Each earns its place through an incident story, and each has a failure mode that is worth naming before you reach for it.

Managed platforms sell governance, not execution: locked state with RBAC, plans on every pull request, and audit logs. Price them per resource under management against the engineering hours self-hosting quietly burns.

OpenTofu is the Linux Foundation fork of Terraform 1.5 under MPL, drop-in compatible for most code, with distinct features such as native state encryption. Removed blocks and provider mocking also exist in Terraform. Portability survives by pinning version floors and testing both binaries in CI.

state rm, import, moved and removed blocks each treat a different wound. The commands are the easy part. What makes the operation safe is the backup, lock and plan ritual wrapped around touching production state.

Generation works when the inputs are genuinely data and dies when YAML grows loops. The line between encoding decisions and writing a worse programming language is where these interviews are actually scored.

A mock can confirm that a module requests private storage while missing the IAM denial that stops creation. Separate configuration contracts from provider behavior, and make the costly tests deliberate.

It copies a small Python program to the target over SSH, runs it, and deletes it. Once that is clear, the agentless claim, the performance characteristics and the idempotency requirement all stop being separate topics.

A staple of services-company interviews, and the boring answer (provisioning versus configuration) is only half of it. The useful half is what happens when you push either tool past its model.

The question that finds out whether someone writes playbooks or writes shell scripts wrapped in YAML. Idempotence is a property of the module you chose, not of Ansible.

Reading a plan is a skill separate from writing HCL. People trusted with production approves read the diff in a fixed order, and one of the checks is what the plan does not contain.

The right answer depends on who owns the truth: the platform, the caller, or nobody. At scale there is a fourth option most candidates miss, where your image pipeline publishes values instead of Terraform hunting for them.

Stack boundaries follow blast radius and change frequency, not the org chart. The monorepo only pays for itself while a machine can answer, from a commit, exactly which roots need planning.