更新日志

Teams can now choose who is allowed to upload cache artifacts from the account Cache page. Keep uploads open to members, CI, and account tokens, or switch to CI and account tokens only so developers can keep downloading trusted cache artifacts without publishing local branch builds back into the cache.

This is useful when CI is your trusted cache producer. CI OIDC logins and scoped account tokens can write to the cache, while members using normal login sessions stay read-only. That helps teams avoid one-off local uploads, reduce cache storage growth, and remove upload wait time from developer machines.

A failed test run doesn't always mean a test failed. Sometimes a target's .xctest bundle won't load, or the app under test never launches, so the tests never get to run at all. Xcode treats these as errors rather than test failures, and now Tuist does too: run and target-level errors show up in a dedicated Errors section on the test run page, each with the target that hit it and the underlying message.

Pulling these out of your test cases keeps your counts honest, an error is no longer miscounted as a failed test, and makes the two kinds of problem easy to tell apart. We also renamed the failures section to Test Failures, so each reads as what it is: Errors stopped your tests from running, Test Failures are the assertions that didn't hold.

Your module cache hit rate tells you how many modules you skipped rebuilding. It never told you how much data that cache actually moved, or how quickly. Now it does.

Every run's Module Cache tab surfaces the network side of your cache. Alongside cache hits, misses, and hit rate, you'll now see:

• Downloaded and Uploaded: the total size of prebuilt modules the run pulled from and pushed to the remote cache.
• Download throughput and Upload throughput: how fast those transfers actually moved, as a time-weighted average.

Every job that runs on Tuist Runners now records how hard its machine worked. CPU, memory, network, CPU I/O wait, and storage are captured for the full duration of the run and plotted on the job page, so you can stop guessing whether a build is CPU-bound, starved for memory, or filling up the disk.

Use it to right-size your runner profiles: move a job that barely touches the CPU onto a smaller machine, or give a job pinned at 100% more cores so it ships faster. Hover a step and the charts highlight that window, so you can tell which step pinned the CPU or filled the disk.

Tuist uses your project's default branch as the baseline for analytics, insights, and comparisons, from bundle size checks to test reliability and flaky test detection. It was already configurable through the CLI, and now you can view and change it directly from your project's settings too. When you connect a GitHub repository, Tuist also adopts the repository's default branch automatically.

Module Cache can now cache framework targets that support your tests, even when they link XCTest or Swift Testing. This helps projects with shared assertion helpers, fixtures, or test utilities reuse binary cache artifacts instead of rebuilding those helper modules from source every time.

Test bundles themselves are still left out of the binary cache. The change only applies to regular framework products that tests depend on, so your test targets keep their normal behavior while their reusable support modules can benefit from local and remote cache hits.

Module Cache can now cache static and dynamic library targets, not only framework targets. Library products are warmed, stored, and consumed as XCFramework artifacts, including Swift modules and public headers, so projects with mixed framework and library graphs can reuse binary cache artifacts across local and CI builds.

Test bundles remain excluded from the binary cache, but reusable library targets that support tests can now benefit from the same cache flow as test-support frameworks.

Build and test times are coming to Grafana. The new Tuist data source plugin pulls the same p50, p90, p99, and average durations you see in your Tuist dashboard and renders them as native Grafana time series, so build and test performance can sit next to the rest of your observability. You configure it with a Tuist account token, then pick a project and an environment (CI or local) and the percentiles you want to chart. Project and environment are dashboard variables, so a single dashboard works across every project the token can reach, and you can watch how your pipelines trend as you optimize them.

The plugin is not published to the Grafana catalog yet. We are getting it ready for release and will update this entry once it is available.

Some tests are not intermittently flaky; they are broken, or failing so often that they drown out useful signal. Automations can now monitor Test reliability across branches and trigger when it drops below your chosen threshold. Pair it with actions like changing the test's quarantine state, marking it as flaky, or notifying Slack, so broken or consistently failing tests can be handled automatically.

When Tuist runs in GitHub Actions, it now writes a Tuist Run Report to the Actions job summary. The test and build results for the run show up right on the workflow run page, with a link to the full report on Tuist, and nothing extra to set up.

This is especially useful with merge queues. A merge queue run is not attached to a pull request, so there is no comment to post, and until now you had to wire up your own JUnit reporting to see results. The summary now shows up for every authenticated run, whether it came from a pull request or a queue.