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Simulado · HashiCorp

Simulado HashiCorp Certified: Terraform Associate (003)

50
questões
60
minutos
70%
para passar no simulado
60
questões no banco

Resposta curta

O simulado de HashiCorp Certified: Terraform Associate (003) tem 50 questões em 60 minutos, com nota de corte de 70%, conforme configurado aqui. O jeito mais rápido de saber se você está pronto é fazer uma prova completa no relógio e ler a nota por domínio, não só o total.

Domínios cobrados

  • HCP Terraform Capabilities
  • IaC Concepts and Terraform Purpose
  • Interact with Terraform Modules
  • Read, Generate, and Modify Configuration
  • Terraform CLI and Core Workflow
  • Terraform State

Questões de exemplo, com explicação

Três questões do banco, abertas para ler.

Questão 1 · HCP Terraform Capabilities

A platform team wants to standardize that all modules consuming the internal 'mycorp/vault' provider use any version in the 1.x line but never automatically jump to 2.0, which contains breaking changes. They add the constraint to required_providers. Which version constraint string correctly expresses 'any 1.x release, including future 1.x patches and minors, but not 2.0'?

  1. version = "~> 1.0" ✓ (correta)
  2. version = "= 1.0"
  3. version = "~> 1.2.0"
  4. version = ">= 1.0"
Por que esta é a correta

The pessimistic constraint operator '~>' with two version segments, '~> 1.0', allows the rightmost specified component (the minor) and the patch component to increment while pinning the leftmost (major) component, meaning >= 1.0.0 and < 2.0.0. That is exactly 'any 1.x but not 2.0'. '~> 1.2.0' is wrong because with three segments it only allows the patch to increment, meaning >= 1.2.0 and < 1.3.0, which excludes future minors like 1.4. '>= 1.0' is wrong because it permits 2.0 and beyond, exactly the breaking upgrade the team wants to block. '= 1.0' is wrong because it pins to a single exact version (1.0.0) and forbids any later 1.x patch or minor release.

Questão 2 · Terraform CLI and Core Workflow

An engineer wants to guarantee that the exact set of changes reviewed during planning is what actually gets applied, with no chance of drift or a recomputed diff between review and execution. Which workflow achieves this?

  1. Run `terraform plan -refresh=false` then `terraform apply -refresh=false`
  2. Run `terraform plan -out=tfplan`, then `terraform apply tfplan` ✓ (correta)
  3. Run `terraform apply -auto-approve` twice and compare outputs
  4. Run `terraform plan` then immediately `terraform apply` and type 'yes'
Por que esta é a correta

Saving a plan with `-out` and then applying that saved plan file makes Terraform execute exactly the recorded set of actions; no new plan is computed at apply time, so review and execution are identical. Running a bare `plan` then a bare `apply` is wrong because the apply recomputes a fresh plan against current state, which can differ from what was reviewed. Running `apply -auto-approve` twice is wrong because each apply computes its own plan and auto-approves it — comparing outputs does not lock the reviewed change set and skips review entirely. Using `-refresh=false` on both commands is wrong because, although it skips refresh, the apply still recomputes the diff from configuration and state and may not match the earlier plan; only a saved plan file guarantees identical actions.

Questão 3 · Read, Generate, and Modify Configuration

A resource attribute requires a value that may be absent. The author writes `bucket = coalesce(var.custom_bucket, "default-bucket")` expecting it to fall back to the literal when `var.custom_bucket` is an empty string. The plan errors or behaves unexpectedly with an empty string. What is the correct understanding?

  1. `coalesce` returns the first non-null, non-empty argument, so an empty string is skipped only if `coalesce` is given a non-empty fallback — but it errors when all arguments are empty/null. ✓ (correta)
  2. `coalesce` is not a valid Terraform function; the author should have used `try` to provide a fallback.
  3. `coalesce` always returns its last argument, so the default literal is what gets used regardless of the variable.
  4. `coalesce` only skips `null`, not empty strings, so an empty `var.custom_bucket` is returned and the default is never used.
Por que esta é a correta

`coalesce` returns the first argument that is neither null nor an empty string; given `("", "default-bucket")` it skips the empty string and returns `default-bucket`, but if every argument is empty/null it raises an error because there is nothing to return. That matches the described 'errors or behaves unexpectedly' when inputs are empty. The claim that `coalesce` only skips `null` and not empty strings is the misconception — that behavior describes a different fallback approach (e.g. `var.x != "" ? var.x : default` or `try`), not `coalesce`. `coalesce` does not 'always return its last argument'; it returns the first usable one. `coalesce` is indeed a real Terraform function, so the option claiming it is invalid is wrong, even though `try` is a legitimate but different tool for handling errors rather than empties.

Faça o simulado completo

  • 50 questões sorteadas do banco, com cronômetro de 60 minutos
  • Nota por domínio e revisão de cada questão
  • Tutor de IA para conversar sobre cada questão que você errar
  • O que você errou alimenta seu plano de estudo

Simulado independente e não oficial. HashiCorp e o nome da prova são marcas de seus donos; o UpSkillScore não é afiliado a eles. Formato e nota de corte são a configuração do simulado no UpSkillScore, não uma declaração oficial.

Perguntas frequentes

Quantas questões tem o simulado de HashiCorp Certified: Terraform Associate (003)?

Tem 50 questões e limite de 60 minutos. A nota de corte do simulado é 70%.

Este é o exame oficial de HashiCorp Certified: Terraform Associate (003)?

Não. É um simulado independente, montado para espelhar a estrutura da prova real. Ele não substitui o exame oficial.

Preciso de conta para fazer?

Você lê a estrutura e as questões de exemplo sem conta. Fazer o simulado completo cronometrado, a nota por domínio e o tutor de IA exigem conta.