How to connect Supabase with Orkes Conductor in minutes

If you’re building on Supabase, you can trigger durable Orkes Conductor workflows without changing your app logic. Clean way to avoid glue code + background job chaos. Happy to chat if you’re exploring this.

Troubleshooting open table formats just got a lot easier! With Metadata Explorer, a Streamlit-in-Snowflake app, you can securely preview file contents and metadata for Iceberg tables without disconnecting steps. Learn how to deploy this powerful tool 👇

Troubleshooting open table formats just got a lot easier! With Metadata Explorer, a Streamlit-in-Snowflake app, you can securely preview file contents and metadata for Iceberg tables without disconnecting steps. Learn how to deploy this powerful tool 👇

Speed Up Your Power Apps with Parallel API Calls! Are your Power Apps taking forever to load? Here's a game changing tip that can reduce your loading time by up to 70%! Most developers make API calls sequentially (one after another), but Power Apps has a powerful Concurrent() function that lets you run multiple API calls in PARALLEL The Difference: Sequential Approach: • Call 1: 3 seconds • Call 2: 3 seconds • Call 3: 3 seconds Total: 9 seconds Parallel Approach: - All 3 calls: 3 seconds (simultaneously) Total: 3 seconds That's 3X faster! Here's how simple it is: Instead of: Set(varData1, API1.GetData()); Set(varData2, API2.GetData()); Set(varData3, API3.GetData()); Use: Concurrent( Set(varData1, API1.GetData()), Set(varData2, API2.GetData()), Set(varData3, API3.GetData()) ); Benefits: 1- Dramatically faster load times 2- Better user experience 3- More efficient resource usage 4- Happier end users! Pro Tips: • Only use for independent API calls • Watch out for API rate limits • Add proper error handling • Limit to ~10 concurrent operations Perfect for dashboard apps data heavy screens and OnStart scenarios where you are loading from multiple data sources. #PowerApps #MicrosoftPowerPlatform #LowCode #AppDevelopment #PowerPlatform #TechTips #ProductivityHack #API #Performance

Hey everyone! I recently deployed a new app designed specifically for H-E-B Curbside bagging operations. With this tool, we now have a more organized structure for our new bagging system and the ability to monitor bagging productivity in real time! I’ve uploaded a short video of myself explaining how the app works and the impact it can make on daily operations. If you have any questions about the technical side (front-end or back-end) feel free to reach out! I had a lot of fun designing this and can’t wait to see the positive changes it brings to our team! #HEB #DataScience #DataAnalytics #Innovation #React #Supabase

Still figuring out how to take an AI-builder prototype and turn it into a production-ready app? Chris Caruso put together a super practical walkthrough on how our enterprise customers at Supabase are doing it: - Iterate fast with Lovable - Use GitHub for version control - Build production apps with your team using Supabase Branching If you’ve got 15 minutes, this is worth a watch: https://lnkd.in/gJwyCD6X AI MVPs are easy. Turning them into real, scalable apps is where the magic (and the headaches) happen.

Feels like observability is finally growing up. Instead of staring at 10 dashboards and praying the error shows itself, you can just ask your system what happened, and it actually answers. Logs, traces, vector search all wired together so the stack basically explains itself. It’s weirdly satisfying (and honestly a little scary) when your app tells you why it broke.

Tech With Tim: Learn Fast API With This ONE Project Learn FastAPI With a Real Project Ever dreamed of building a production-ready FastAPI app from scratch? This tutorial teams FastAPI with ImageKit to handle all your image/video needs and takes you through everything from basic setup and routing (GET, POST, path/query params) to Pydantic models, error handling, and database integration. Along the way you’ll add user authentication with JWT tokens, protect endpoints, and even whip up a Streamlit frontend. By the end, you’ll have a full-featured photo/video sharing app that’s ready for the real world. Watch on YouTube https://lnkd.in/gxZqyTcM

🔧 Feature Friday Spotlight: Scheduler Data Manager in IBM Maximo Check out this great walk-through by John Q. Todd on how the Scheduler Data Manager application helps ensure your work schedules are built on solid, validated data. In asset-intensive environments, even small data inconsistencies can derail scheduling efforts. This tool helps identify and correct issues like: -Missing planned labor -Schedule windows outside the calendar -Labor mismatches (e.g., needing 3 electricians but only having 2 available) You can access Scheduler Data Manager from the Administration menu, or directly within: -Graphical Scheduling -Graphical Scheduling – Large Projects -Graphical Assignment -Graphical Work Week ✅ Validating your schedule data upfront leads to better results and fewer surprises downstream. Thanks to John for continuing to share practical insights that help Maximo users get the most out of their tools! #Maximo #SchedulerDataManager #AssetManagement #Utilities #EnterpriseSoftware #FeatureFriday

I'll add some more, short & to the point: ReplicaSet: Used for running identical pods [Stateless apps]. DaemonSet: A single pod which runs on each worker node in a cluster. StatefulSet: Pods which need persistent storage [Stateful apps]. Annotation: Metadata about cluster objects with additional info. Configmap: Stores non-confidential data in key-value pairs. You can add too in the comments in plain English 😊