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
Back to feedPost
I recently mapped out a complete CI/CD pipeline for a Flask application running on AWS.
The workflow looked solid:
š¹ GitHub for source control
š¹ AWS CodePipeline for orchestration
š¹ CodeBuild for testing and Docker image creation
š¹ Amazon ECR for image storage
š¹ CodeDeploy for blue/green deployments
š¹ SNS notifications for deployment status
š¹ CloudWatch for monitoring
With a simple git push, the application could be tested, containerized, and deployed automatically.
But while analyzing the architecture, I noticed something interesting.
The entire CI/CD pipeline cost approximately $8/month.
The EC2 instance hosting the application cost approximately $587/month.
The lesson?
Many organizations focus heavily on deployment automation while overlooking infrastructure optimization.
A mature cloud strategy requires both:
ā
Fast and reliable deployments
ā
Cost-efficient infrastructure
ā
Continuous monitoring
ā
Right-sized resources based on actual usage
Building CI/CD pipelines is important.
But understanding where the money is actually being spent is what transforms a cloud engineer into a cloud architect.
Technology decisions should optimize not only for speed, but also for business value.
#AWS #CloudComputing #DevOps #CICD #CodePipeline #Docker #EC2 #CloudArchitecture #CostOptimization #GitHub #LearningInPublic
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
Related posts
Title:
I built a design system generator inside Figma Make. Here's the workflow.
The problem I kept running into: every new client project meant re-explaining the brand to every AI tool from scratch. Figma Make didn't know the colors. Cursor didn't know the tokens. Claude didn't know the rules. I was the shared memory ā and I kept losing things.
So I built Design System Gen. Entirely inside Figma Make. Powered by Claude API.
The workflow:
Upload brand references ā Claude API analyzes them across 8 dimensions (palette, mood, typography, composition, lighting, texture, motion, UI DNA) ā structured data, not vibes ā generates 11 files, each formatted for a specific tool in your stack.
figma-make.md ā paste once, Figma Make knows your entire design system
design-system.css ā all tokens as CSS custom properties
tokens.json ā W3C format, imports directly into Figma Variables
starter.tsx ā React starter with tokens already bound
.cursorrules ā Cursor knows your system from root
Claude.md ā Claude reads it automatically every session
+ 5 more for docs, LLMs, prompts, components
Every tool gets its own context file. All consistent with each other.
The part I'm most proud of: I'm a designer. I don't write code. The entire tool ā UI, API integration, file generation logic ā was built and shipped inside Figma Make. No external hosting. No separate codebase.
Live at:Ā vibecodingdsgen.figma.site
Add your Claude API key and try it with your own moodboard.
#FigmaMake #DesignSystem #VibeCoding #AI #Claude #UXUI #DesignSystems #ConfigMakeathon
ā¢ 2d
As someone who constantly jumps between Figma, Claude, ChatGPT, Cursor, Lovable, and other AI tools, this problem feels very familiar š
The tools are getting smarter, but keeping context consistent is still surprisingly manual. Love seeing people tackle that gap.
Brand and Product Design for Aquapatina a ETH Staking
platform from Switzerland
š Goodbye expensive software, hello custom AI automation!
Tired of paying hefty monthly subscriptions for clunky outreach tools and getting zero replies from generic templates?
Same here. So, I decided to build my own. š ļø
Late last night, I successfully deployed a 100% custom, automated AI cold outreach engine. I'm keeping the exact tech stack under wraps for now š¤«, but the workflow is an absolute game-changer.
Here is what my proprietary system does on autopilot:
Smart Data Ingestion: I simply drop a prospect's basic info into my secure database.
Hyper-Personalization: My integrated AI model instantly analyzes the context and writes a highly personalized, natural-sounding email based on my specific commands. Zero robotic, copy-paste templates!
Seamless Auto-Sending: The system automatically dispatches the customized email directly from my native inbox, maximizing deliverability and bypassing the dreaded spam folder.
š° The Best Part? The ROI.
Standard lead-gen and outbound email platforms can easily drain $100 to $250+ EVERY single month.
By building this custom system from scratch, I am saving around $150+ USD monthly (that's nearly $2,000 a year!) all while achieving a significantly higher response rate.
Hitting major professional targets requires more than just hard work; it requires building smart, scalable systems.
Are you still paying monthly fees for expensive outreach tools, or are you exploring custom AI automation for your workflow?
Letās chat in the comments! š
#AI #Automation #LeadGeneration #ColdOutreach #GrowthHacking #B2BSales #TechBuild #SmartWork #BusinessGrowth
Trending
Claude
Claude has entered the design space. How are you using Claude Design?
Contra University
Learn from expert creatives how to earn more using next-gen AI tools.
MagicPath
The canvas is infinite, and exploration is becoming the workflow. How are you using MagicPath?
creativeaiflow
Creative AI workflows are evolving. What tools do you use, and what are their strengths and weaknesses?
freelancerlife
Freelancer life is wins, pivots, and everything in between. Whatās yours right now?