All the information is available to resolve provider types when building
the configuration, but some provider references still had no FQN. This
caused validation to assume a default type, and incorrectly reject valid
module calls with non-default namespaced providers.
Resolve as much provider type information as possible when loading the
config. Only use this internally for now, but this should be useful
outside of the package to avoid re-resolving the providers later on. We
can come back and find where this might be useful elsewhere, but for now
keep the change as small as possible to avoid any changes in behavior.
To ensure that the apply command can determine whether an operation is
executed locally or remotely, we add an IsLocalOperations method on the
remote backend. This returns the internal forceLocal boolean.
We also update this flag after checking if the corresponding remote
workspace is in local operations mode or not. This ensures that we know
if an operation is running locally (entirely on the practitioner's
machine), pseudo-locally (on a Terraform Cloud worker), or remotely
(executing on a worker, rendering locally).
Disabling the resource count and outputs rendering when the remote
backend is in use causes them to be omitted from Terraform Cloud runs.
This commit changes the condition to render these values if either the
remote backend is not in use, or the command is running in automation
via the TF_IN_AUTOMATION flag. As this is intended to be set by
Terraform Cloud and other remote backend implementations, this addresses
the problem.
Fix two bugs which surface when using the remote backend:
- When migrating to views, we removed the call to `(*Meta).process`
which initialized the color boolean. This resulted in the legacy UI
calls in the remote backend stripping color codes. To fix this, we
populate this boolean from the common arguments.
- Remote apply will output the resource summary and output changes, and
these are rendered via the remote backend streaming. We need to
special case this in the apply command and prevent displaying a
zero-change summary line.
Neither of these are coverable by automated tests, as we don't have any
command-package level testing for the remote backend. Manually verified.
Terraform v0.15 includes the conclusion of the deprecation cycle for some
renamed arguments in the "azure" backend.
We missed this on the first draft of the upgrade guide because this change
arrived along with various other more innocuous updates and so we didn't
spot it during our change review.
Unfortunately it seems that this link got lost in a merge conflict when
we did the big nav refactor earlier in the v0.15 cycle, so here we'll
retoractively add it to the new location for upgrade guide nav, in the
language layout rather than the downloads layout.
* website: v0.15 upgrade guide for sensitive resource attributes
Our earlier draft of this guide didn't include a section about the
stabilization of the "provider_sensitive_attrs" language experiment. This
new section aims to address the situation where a module might previously
have been returning a sensitive value without having marked it as such,
and thus that module will begin returning an error after upgrading to
Terraform v0.15.
As part of that, I also reviewed the existing documentation about these
features and made some edits aiming to make these four different sections
work well together if users refer to them all at once, as they are likely
to do if they follow the new links from the upgrade guide. I aimed to
retain all of the content we had before, but some of it is now in a new
location.
In particular, I moved the discussion about the v0.14 language experiment
into the upgrade guide, because it seems like a topic only really relevant
to those upgrading from an earlier version and not something folks need to
know about if they are using Terraform for the first time in v0.15 or
later.
* minor fixups
Co-authored-by: Kristin Laemmert <mildwonkey@users.noreply.github.com>
In the Terraform language we typically use lists of zero or one values in
some sense interchangably with single values that might be null, because
various Terraform language constructs are designed to work with
collections rather than with nullable values.
In Terraform v0.12 we made the splat operator [*] have a "special power"
of concisely converting from a possibly-null single value into a
zero-or-one list as a way to make that common operation more concise.
In a sense this "one" function is the opposite operation to that special
power: it goes from a zero-or-one collection (list, set, or tuple) to a
possibly-null single value.
This is a concise alternative to the following clunky conditional
expression, with the additional benefit that the following expression is
also not viable for set values, and it also properly handles the case
where there's unexpectedly more than one value:
length(var.foo) != 0 ? var.foo[0] : null
Instead, we can write:
one(var.foo)
As with the splat operator, this is a tricky tradeoff because it could be
argued that it's not something that'd be immediately intuitive to someone
unfamiliar with Terraform. However, I think that's justified given how
often zero-or-one collections arise in typical Terraform configurations.
Unlike the splat operator, it should at least be easier to search for its
name and find its documentation the first time you see it in a
configuration.
My expectation that this will become a common pattern is also my
justification for giving it a short, concise name. Arguably it could be
better named something like "oneornull", but that's a pretty clunky name
and I'm not convinced it really adds any clarity for someone who isn't
already familiar with it.
Calling the nonsensitive function with values which are not sensitive
will result in an error. This restriction was added with the goal of
preventing confusingly redundant use of this function.
Unfortunately, this breaks when using nonsensitive to reveal the value of
sensitive resource attributes. This is because the validate walk does
not (and cannot) mark attributes as sensitive based on the schema,
because the resource value itself is unknown.
This commit therefore alters this restriction such that it permits
nonsensitive unknown values, and adds a test case to cover this specific
scenario.
When returning generic grpc errors from a provider, use
WholeContainingBody so that callers can annotate the error with all the
available contextual information. This can help troubleshoot problems by
narrowing down problems to a particular configuration or specific
resource instance.
Add an address argument to tfdiags.InConfigBody, and store the address
string the diagnostics details. Since nearly every place where we want
to annotate the diagnostics with the config context we also have some
sort of address, we can use the same call to insert them both into the
diagnostic.
Perhaps we should rename InConfigBody and ElaborateFromConfigBody to
reflect the additional address parameter, but for now we can verify this
is a pattern that suits us.
* Optimize (m ModuleInstance) String()
Optimize (m ModuleInstance) String() to preallocate the buffer and use strings.Builder instead of bytes.Buffer
This leads to a common case only doing a single allocation as opposed to a few allocations which the bytes.Buffer is doing.
* adding a benchmark test
Result:
```
$ go test -bench=String ./addrs -benchmem
BenchmarkStringShort-12 18271692 56.52 ns/op 16 B/op 1 allocs/op
BenchmarkStringLong-12 8057071 158.5 ns/op 96 B/op 1 allocs/op
PASS
$ git checkout main addrs/module_instance.go
$ go test -bench=String ./addrs -benchmem
BenchmarkStringShort-12 7690818 162.0 ns/op 80 B/op 2 allocs/op
BenchmarkStringLong-12 2922117 414.1 ns/op 288 B/op 3 allocs/op
```
* Update module_instance_test.go
switch spaces to tabs
Dependencies are tracked via configuration addresses, but when dealing
with depends_on references they can only apply to resources within the
same module instance. When determining if a data source can be read
during planning, verify that the dependency change is coming from the
same module instance.
When rendering the JSON plan sensitivity output, if the plan contained
unknown collection or structural types, Terraform would crash. We need
to detect unknown values before attempting to iterate them.
Unknown collection or structural values cannot have sensitive contents
accidentally displayed, as those values are not known until after apply.
As a result we return an empty value of the appropriate type for the
sensitivity mapping.
When applying sensitivity marks to resources, we previously would first
mark any provider-denoted sensitive attributes, then apply the set of
planned-change sensitive value marks. This would cause a panic if a
provider marked an iterable value as sensitive, because it is invalid to
call `MarkWithPaths` against a marked iterable value.
Instead, we now merge the marks from the provider schema and the planned
change into a single set, and apply them with one call. The included
test panics without this change.
We previously added a hint to both resource for_each and dynamic blocks
about using the "flatten" and "setproduct" situations to construct
suitable collections to repeat over.
However, we used the same text in both places which ended up stating that
dynamic blocks can only accept map or set values, which is a constraint
that applies to resource for_each (because we need to assign a unique
identifier to each instance) and not to dynamic blocks (which don't have
any uniqueness enforced by Terraform Core itself).
To remove that contradiction with the text above which talks about what
is valid here, I've just generalized this to say "collection", because
the primary point of this paragraph is the "one element per desired nested
block" part, not specifically what sort of collections are permitted in
this location. (Text further up describes the supported types.)
Kristin Laemmert