How Low-Code Enables Continuous Testing in DevOps
summary
Argues that low‑code plus machine intelligence actually raises deployment confidence by plugging tests into each pipeline stage using mabl — examples include mabl CLI to run tests on every commit, auto healing that updates locators when DOM IDs change, import and export of existing Selenium scripts to avoid vendor lock‑in, built‑in coverage and cross‑browser/mobile runs, Jira bug creation from failed runs, data tables with faker/math.js, and reported order‑of‑magnitude reductions in maintenance.
AI-written summary · about
chapters (14)
- 0:00Intro
- 0:53Outline
- 1:53We want high velocity, high throughput
- 5:21Low-code: Separate intent and implementation
- 9:13E2E test automation in the code phase
- 10:50Pair on E2E tests in the code phase
- 12:29E2E testing in the (pivotal) pull request phase
- 13:26Collaborate on test review
- 14:59Run regression tests against preview environments
- 15:44Low-code testing in the deployment phase
- 16:22Take the back-and-forth out of defect reporting
- 17:12Develop a shared view into issues and trends
- 19:04Add responsive test coverage in a couple clicks
- 20:33Intelligent test automation for Agile teams
related talks
40mDoes Low-Code mean Low Testing?
46mDoes Low Code Mean Low Testing?
35mBridging Speed and Stability: DevOps in the Low-Code World
44mSimplifying and Scaling Software Delivery
32mWhy testing is a developer's problem
15mTransforming Testing: The Power of TestOps
45mLow Code Visual Testing of an Enterprise Scenario
26mThe Impact of Testing on a DevOps Pipeline
