[Apr 12, 2022] TA-002-P Ultimate Study Guide – DumpsTests [Q58-Q73]

https://www.terraform.io/docs/registry/modules/publish.html

Check resource addressing
https://www.terraform.io/docs/internals/resource-addressing.html

Explanation
The existence of a provider plugin found locally in the working directory does not itself create a provider dependency. The plugin can exist without any reference to it in the terraform configuration. https://www.terraform.io/docs/commands/providers.html

Explanation
The terraform validate command validates the syntax and arguments of the Terraform configuration files.
Reference: https://www.terraform.io/docs/cli/code/index.html

By default, Terraform uses the “local” backend, which is the normal behavior of Terraform you’re used to.
https://www.terraform.io/docs/backends/index.html

Explanation
Collection Types
A collection type allows multiple values of one other type to be grouped together as a single value. The type of value within a collection is called its element type. All collection types must have an element type, which is provided as the argument to their constructor.
For example, the type list(string) means “list of strings”, which is a different type than list(number), a list of numbers. All elements of a collection must always be of the same type.
The three kinds of collection type in the Terraform language are:
* list(…): a sequence of values identified by consecutive whole numbers starting with zero.
The keyword list is a shorthand for list(any), which accepts any element type as long as every element is the same type. This is for compatibility with older configurations; for new code, we recommend using the full form.
* map(…): a collection of values where each is identified by a string label.
The keyword map is a shorthand for map(any), which accepts any element type as long as every element is the same type. This is for compatibility with older configurations; for new code, we recommend using the full form.
* set(…): a collection of unique values that do not have any secondary identifiers or ordering.
https://www.terraform.io/docs/configuration/types.html
Structural Types
A structural type allows multiple values of several distinct types to be grouped together as a single value.
Structural types require a schema as an argument, to specify which types are allowed for which elements.
The two kinds of structural type in the Terraform language are:
* object(…): a collection of named attributes that each have their own type.
The schema for object types is { <KEY> = <TYPE>, <KEY> = <TYPE>, … } – a pair of curly braces containing a comma-separated series of <KEY> = <TYPE> pairs. Values that match the object type must contain all of the specified keys, and the value for each key must match its specified type. (Values with additional keys can still match an object type, but the extra attributes are discarded during type conversion.)
* tuple(…): a sequence of elements identified by consecutive whole numbers starting with zero, where each element has its own type.
The schema for tuple types is [<TYPE>, <TYPE>, …] – a pair of square brackets containing a comma-separated series of types. Values that match the tuple type must have exactly the same number of elements (no more and no fewer), and the value in each position must match the specified type for that position.
For example: an object type of object({ name=string, age=number }) would match a value like the following:
{
name = “John”
age = 52
}
Also, an object type of object({ id=string, cidr_block=string }) would match the object produced by a reference to an aws_vpc resource, like aws_vpc.example_vpc; although the resource has additional attributes, they would be discarded during type conversion.
Finally, a tuple type of tuple([string, number, bool]) would match a value like the following:
[“a”, 15, true]
https://www.terraform.io/docs/configuration/types.html

The Terraform language will automatically convert number and bool values to string values when needed, and vice-versa as long as the string contains a valid representation of a number or boolean value.
Example
* true converts to “true”, and vice-versa
* false converts to “false”, and vice-versa
* 15 converts to “15”, and vice-versa
Where possible, Terraform automatically converts values from one type to another in order to produce the expected type. If this isn’t possible, Terraform will produce a type mismatch error and you must update the configuration with a more suitable expression.
https://www.terraform.io/docs/configuration/expressions.html#type-conversion

https://www.terraform.io/docs/state/remote.html

In particular, organizations commonly want to create a strong separation between multiple deployments of the same infrastructure serving different development stages (e.g. staging vs. production) or different internal teams. In this case, the backend used for each deployment often belongs to that deployment, with different credentials and access controls. Named workspaces are not a suitable isolation mechanism for this scenario.
https://www.terraform.io/docs/state/workspaces.html

Explanation
Named workspaces allow conveniently switching between multiple instances of a single configuration within its single backend. … A common use for multiple workspaces is to create a parallel, distinct copy of a set of infrastructure in order to test a set of changes before modifying the main production infrastructure.
Workspaces, allowing multiple states to be associated with a single configuration. The configuration still has only one backend, but multiple distinct instances of that configuration to be deployed without configuring a new backend or changing authentication credentials.
https://www.terraform.io/docs/state/workspaces.html

Explanation
https://learn.hashicorp.com/terraform/getting-started/destroy

Explanation
workspaces allow conveniently switching between multiple instances of a single configuration within its single backend. They are convenient in a number of situations, but cannot solve all problems.
A common use for multiple workspaces is to create a parallel, distinct copy of a set of infrastructure in order to test a set of changes before modifying the main production infrastructure. For example, a developer working on a complex set of infrastructure changes might create a new temporary workspace in order to freely experiment with changes without affecting the default workspace.
Non-default workspaces are often related to feature branches in version control. The default workspace might correspond to the “master” or “trunk” branch, which describes the intended state of production infrastructure.
When a feature branch is created to develop a change, the developer of that feature might create a corresponding workspace and deploy into it a temporary “copy” of the main infrastructure so that changes can be tested without affecting the production infrastructure. Once the change is merged and deployed to the default workspace, the test infrastructure can be destroyed and the temporary workspace deleted.
https://www.terraform.io/docs/state/workspaces.html
https://www.terraform.io/docs/state/workspaces.html#when-to-use-multiple-workspaces

Explanation
Terraform Enterprise runs on Linux instances, and you must prepare a running Linux instance for Terraform Enterprise before running the installer. You will start and manage this instance like any other server.
Terraform Enterprise currently supports running under the following operating systems:
Standalone deployment:
Debian 7.7+
Ubuntu 14.04.5 / 16.04 / 18.04
Red Hat Enterprise Linux 7.4 – 7.8
CentOS 6.x / 7.4 – 7.8
Amazon Linux 2014.03 / 2014.09 / 2015.03 / 2015.09 / 2016.03 / 2016.09 / 2017.03 / 2017.09 / 2018.03 / 2.0 Oracle Linux 7.4 – 7.8
https://www.terraform.io/docs/enterprise/before-installing/index.html