Used by elite engineering teams

  • UKG Logo
  • BMW Logo
  • Sony Logo
  • Infosys Logo
  • Gocardless Logo
  • Optim Logo
  • Line Logo
  • Jenkins Logo
  • Vitess Logo
  • Delphix Logo
  • Keyloop Logo

Your team drowns in a firehose of test failures before every release

We help them find calm amidst the chaos and ship with confidence.

Run

Rocket

Optimize tests to run

Filter

Filter

Filter away noise

Analyze

Dashboard and charts

Analyze the problem

Aware

Speaker

Raise awareness

Track

Chart and messages

Track the fix

SOC2 certified

It takes about one hour of a developer's time to set up Launchable

  • Four lines of changes in a CI Script
  • No developer support needed after setup
  • SOC 2 certified to keep your data safe
SOC 2 Type 1 Badge

The Five Problems Slowing the Dev-Test Iterative Loop

Tests are a significant component of the DevOps infinity loop. Every commit has to pass a series of test suites (unit, functional, regression, integration, smoke, UX, etc.) before it is certified as good enough to reach production. The workflow restarts if a test fails. Test suites grow over time and add execution time, slowing the delivery velocity.

Interative Loop
Interative Loop

Run

Rocket

Filter

Filter

Analyze

Dashboard and charts

Aware

Speaker

Track

Chart and messages

Long runtimes for tests that slow feedback signal to devs and QA

80% of tests are pointless for a given set of incoming changes—you don’t know which ones.

Thus, QA runs all the tests, spending time/effort and money.

The result is slow development velocity.

Rocket

Noise generated by Flaky & Unhealthy tests that take effort to sift through

Every test suite suffers from flaky and unhealthy tests.

QA lacks data insights to know which ones cause the most friction.

Eventually, developers lose trust in the test suite.

Filter

Manual root-cause analysis of test failures slows down dev-test iteration

There is a firehose of test failures from every test session.

QA manually goes through test failures to determine root-cause analysis and assign owners.

There is a never-ending pressure to be constantly ahead of failures while lacking tooling that helps.

Dashboard and charts

Test failure awareness propagates slowly, causing delays in root-cause analysis

Devs & QA poll CI tools or skim emails to determine if they broke post-merge builds.

Regular fire drills to raise awareness of issues.

Speaker

Tracking of issues and fixes

As test failures happen, the real work of tracking fixes starts.

QA jumps between test failure reports and the bug tracking system to keep track of what’s new and what’s fixed.

Tracking issues at individual test failure levels is cumbersome and time-consuming.

Chart and messages

A Multi-prong AI-Augmented Approach to Improve the Dev-Test Iterative Loop

Faster root-cause analysis by enhancing the innermost “dev-qa” workflow

PTS curve - Run 50% tests to find 99% of failing builds

Rocket Run

Improve the velocity of an iteration by focusing on tests that fail

Correlate code changes to tests to run an ML-based subset to find failing builds in a fraction of the time.

Github notification

Test session status on GitHub

Slack notification

Personalized notifications in Slack

Speaker Aware

Get to problems faster with personalized notifications when tests fail

The GitHub app notifies developers and QA of test failures, and the Slack App can inform the concerned developers if they break the tests.

Test sessionTest sessionFailed cases

Dashboard and charts Analyze

Failures are grouped into underlying issues to focus on the most critical problems

Launchable examines failed test cases and classifies them according to their underlying issues to reduce the cognitive load of analyzing failures.

Jenkins build failure

Dashboard and charts Analyze

Instant issue comprehension via summaries of logs

GenAI drives instant clarity on underlying software issues raised by test failures. Launchable transforms complex, voluminous error logs into succinct summaries to quickly identify the crux of issues.

Track issues

Chart and messages Track

A dashboard to pinpoint new and ongoing issues across test sessions and branches

Faster triaging with a view of issues and the ability to filter them by branches.

Test session dashboard

Dashboard and charts Analyze

Quickly pinpoint new and recurring issues in a test session failure

Quickly see information on issues to see if the issue is new or recurring.

Test session dashboard

Dashboard and charts Analyze

Priortize triaging using unhealthy test insights

Use test-related insights such as Flakiness, Never Failing, Longest, or Most Failed to prioritize attention on tests that matter.

TEST CASEtest_get_org_workspace_no_environment_variablestests/utils/test_authentication.pytest_subsettests/test_runners/test_minitest.pytest_authentication_headers_emptytests/utils/test_authentication.pytest_subsettests/test_runners/test_nunit.pytest_record_testtests/test_runners/test_nunit.pyFLAKINESS SCORE1.00 0.020.98 040.0.95 0.040.80 0.040.78TOTAL DURATION16,667 min / week 2,500 min3,334 min / week 417 min250 min / week 50 min134 min / week 9 min47 min / week
2,500 minTotal duration16,667 min / week

Filter Filter

Flaky tests prioritized by negative impact to the team

Use the Flakiness dashboard during sprint planning to prioritize which tests to fix first

  • Flakiness report of top flaky tests
  • Tests prioritized by wasted time for the team
Read the docs

Additional Signals include Never-Failing Tests, Longest Tests, and Most Failed Tests, as well as trends on test session duration, failure ratio, and more.

Read more about Test Insights

Your co-pilot for Triaging, Understanding and Managing Test Failures

Quality a focus? Working with nightly, integration or UI tests?
Our AI can help.