feat(metrics): Attach default SDK attributes to metrics

[szokeasaurusrex]

Set these metric attributes by default:

• sentry.environment
• sentry.release
• sentry.sdk.name
• sentry.sdk.version
• server.address

Preserve explicitly set metric attributes when applying those defaults.

Stacked on #1073

Co-authored-by: Joris Bayer joris.bayer@sentry.io
Closes #1059
Closes RUST-187

[linear-code]

RUST-187 Add trace metric default attribute enrichment in sentry-core

[github-actions]

	Messages
📖	Do not forget to update Sentry-docs with your feature once the pull request gets approved.

Generated by 🚫 dangerJS against 31ee7b5

[lcian]

LGTM

[sentry]

Bug: capture_metric performs unnecessary work in prepare_metric even when metrics are disabled, as it lacks an early return guard to check if enable_metrics is false.
_{Severity: MEDIUM}

Suggested Fix

Add an early return guard at the beginning of the capture_metric function to check the self.options.enable_metrics flag. If it's false, the function should return immediately, similar to how capture_log handles disabled logs. This will prevent the unnecessary execution of prepare_metric.

Prompt for AI Agent

Review the code at the location below. A potential bug has been identified by an AI
agent. Verify if this is a real issue. If it is, propose a fix; if not, explain why it's
not valid.

Location: sentry-core/src/client.rs#L579-L585

Potential issue: When `enable_metrics` is set to `false` in `ClientOptions`, the
`capture_metric` function is still called and proceeds to execute `prepare_metric`. This
function performs non-trivial work, including applying scope data, cloning attributes,
and inserting them into the metric. However, since the `metrics_batcher` is `None` when
metrics are disabled, the prepared metric is immediately discarded. This results in
wasteful CPU and memory usage in production scenarios where metrics are disabled at
runtime. This behavior is inconsistent with `capture_log`, which includes an early guard
for its corresponding feature flag.

_{Did we get this right? 👍 / 👎 to inform future reviews.}