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The biggest automation mistake I see?
Building it once and never touching it again.
Your business changes. Your processes change. Your tools change.
But that automation you built last year is still running the same logic.
That’s when things start to break:
• Leads get missed
• Notifications go to the wrong place
• Data gets duplicated
• Workflows trigger at the wrong time
Automation isn’t “set it and forget it.”
It needs regular testing, optimization, and maintenance, just like software.
Build it. Monitor it. Improve it.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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"I'm watching everything" sounds like "I'm watching you" 😊 😂
Great design!
MyCarrier: DevOps & Cloud Transformation for Scalable Logistics SaaS
Preview description:
We helped MyCarrier move toward cloud-ready DevOps: adapted the system for microservices, implemented CI/CD and test automation, moved workloads to Azure, achieved 99.9% availability, decreased update delivery time to minutes.
Full description:
Problem
MyCarrier was growing fast, and the monolithic codebase became harder and more expensive to maintain. It was heavy, resource-consuming, and less suitable for the client’s long-term scaling plans. The team also needed faster delivery processes, but changes in the codebase and cloud migration had to stay unnoticed by users. Their logistics workflows could not be interrupted.
Solution
IT Craft aligned the project infrastructure with a microservices architecture and prepared the system for cloud operation. The team started with a technical audit and developed the migration strategy consisting of 20-28 items. The process was divided into pre-migration, migration, and post-migration phases, thus the product could keep running while infrastructure changed step by step.
The team moved non-critical standalone jobs to the cloud, connected virtual machines to Azure Storage Account, moved logging to MongoDB Atlas, and transferred user data and related processes to the cloud. New app functionality was released as microservices. IT Craft also designed and fine-tuned a CI/CD pipeline, automated infrastructure deployments, and reduced update delivery time through regression test automation.
Results
· Achieved 99.9% system availability.
· Maintained high fault tolerance using three shared clusters.
· Reduced update delivery time from hours to minutes.
· Enabled Sprint focus changes every two weeks based on client priorities.
Tech Stack:
· Azure Cloud
· MongoDB Atlas
· Azure SQL
· Azure App Service
· Azure Functions
· Azure Storage Account
Lately been testing out @MagicPath ,@Claude and @Figma workflow for designing graphics.
While AI tools can get you till 80-90% , you can export and tweak the details in Figma until you're happy with the final output.
80-90% with AI tools tracks with what I've seen too. Where does that last stretch usually go, mostly typography and spacing tweaks, or does the output sometimes need bigger structural fixes before it's client ready?
