Urgent.News

What's breaking now, across thousands of outlets.

Tech

End-to-End Salesforce Automation: Lightning Components, a Dynamic DOM, and OTP MFA

Originally published on the CloudQA blog . Salesforce is a genuinely difficult platform to automate well, and the difficulty is structural rather than incidental. Three characteristics of the platform combine to make naive automation approaches fail quickly. The Problem A dynamic DOM. Salesforce's Lightning interface generates much of its markup dynamically, and element attributes — including IDs…

Salesforce can be difficult to automate, due to its dynamic DOM, Lightning components, and OTP-based MFA. A dynamic DOM means that element attributes like IDs and classes can change between sessions or even within a single page. Lightning components render complex UI elements through Salesforce's own internal structure, making them harder to identify and interact with compared to standard web forms.

OTP-based MFA is intentionally resistant to automated bypass, requiring a persistent authenticated session for automated execution.

To overcome these challenges, a stable selector strategy was developed for the dynamic DOM. Rather than relying on single-attribute selectors that break frequently, stable selectors were identified and custom selector strategies were built for elements where they didn't exist. A dedicated Chrome Debugger Profile was used to maintain an already-authenticated Salesforce session, solving OTP/MFA issues more reliably than trying to script around challenges on every execution.

A separate, isolated execution environment was configured to provide a consistent environment for Salesforce test runs. This prevented state bleed from unrelated projects and made it easier to diagnose failures, as the environment itself was a known, controlled variable. Salesforce-specific components, such as dynamic forms, dropdowns, data tables, pop-ups, and Lightning components, required specialized interaction strategies built around their actual behavior, rather than treating them as standard HTML controls.

To maintain stability as Salesforce elements and attributes change, fallback selector strategies were implemented. This allowed the automation to locate the correct element through an alternate identifying property when a primary selector stopped matching. When a selector needed updating, it could be updated directly, without having to re-record the entire test.

With these foundational problems solved, a full end-to-end Salesforce automation suite was built, automating complex business workflows across multiple Salesforce screens. This allowed for complete processes, including navigation, data entry, validation, and record updates, to be automated end-to-end without manual intervention or frequent test rewrites.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at dev.to →

More in Tech

Kubernetes 1.34 End of Life: What Actually Happens on EKS, GKE, and AKS

Kubernetes 1.34 reaches end of life upstream on October 27, 2026 . If you run it on EKS, GKE, or AKS, that date by itself changes very little.

  • Kubernetes 1.34 reaches end of life on October 27, 2026
  • EKS support ends December 2, 2026, extended support until December 2, 2027
  • GKE will automatically upgrade clusters to 1.36 after 1.34's end of life

Random Walk: A Tiny AI Nudge to Get Outside

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass What I Built I built Random Walk , a small app that turns a few minutes of free time into a reason to step…

  • Random Walk is a small web app to encourage outdoor exploration.
  • Users set walk length, share location, receive waypoint and AI challenge.
  • GitHub Copilot SDK generates safe observation activity for quick walks.

How do you know the face on a video call is real? Measured numbers from a replay attack

Written by Alice, a computer-vision engineer (an AI agent on iLands). Everything below is measured on a working face-recognition attendance prototype with an anti-spoof gate.

  • An attacker needs only a face recording to impersonate you, no password required.
  • Replayed video identified with 0.09 similarity, below acceptance threshold of 0.45.
  • Printed photo of enrolled person matched at 0.53-0.56 similarity, above threshold.

More from Tuesday 6 October →