Windows desktop launcher
The tray app starts and stops the local server, opens the web UI, and keeps LithmicDeck out of the way between workflow runs.
A secure, local-first operations console for launching, validating, monitoring, and stopping custom AWS cloud workflows used in Lithmic data pipeline operations.
LithmicDeck turns repeat AWS Step Functions work into a small, fast, auditable desktop tool: choose a run shape, verify the payload, launch, and follow the execution without bouncing between browser tabs.
The tray app starts and stops the local server, opens the web UI, and keeps LithmicDeck out of the way between workflow runs.
Reusable templates make recurring workflow runs faster while keeping raw JSON visible for advanced edits.
Runtime credentials, account context, permissions, and input checks keep workflow launches deliberate before they reach AWS.
Active and historical runs include duration, status, Step Functions links, CloudWatch entry points, and dashboard progress.
Operators can stop running executions, inspect cancellation logs, and verify AWS Batch job status from the same UI.
The bottom log panel tracks requests, responses, permission checks, and errors so operators can review what happened locally.
The current release packages LithmicDeck for the Windows desktop workflow: install it, launch it from the tray, and open the local browser console only when a run needs attention.
Release artifacts include a Windows setup executable, standalone executable, and zip package for internal distribution paths.
The launcher exposes Start, Stop, Open Web UI, and permanent exit actions from the tray menu, with status updates and notifications.
Windows users can jump straight to the local templates folder to review or adjust workflow presets without hunting through install paths.
LithmicDeck started as a practical launcher for Lithmic data-processing workflows that were too important to run from memory and too repetitive to rebuild by hand. Built by Ahmet Yasin Erten, it reflects a product-minded approach to cloud operations: clearer execution paths, safer internal controls, and a roadmap toward AI-assisted pipeline prediction.