One of the biggest mistakes in cloud architecture is overprovisioning infrastructure. Recently, I...

One of the biggest mistakes in cloud architecture is overprovisioning infrastructure. Recently, I...One of the biggest mistakes in cloud architecture is overprovisioning infrastructure. Recently, I...

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afor ever

• Jun 2

One of the biggest mistakes in cloud architecture is overprovisioning infrastructure.

Recently, I analyzed a setup where a simple Flask API was running on an oversized EC2 instance:

🔹 EC2 m5.4xlarge 🔹 16 vCPUs 🔹 64 GB RAM 🔹 Single Flask process on port 5000 🔹 No redundancy or high availability

The result?

A monthly infrastructure cost of nearly $600/month for a workload that didn’t actually require that level of compute power.

This is where cloud cost optimization becomes important.

In many systems, performance problems are not solved by “adding bigger servers” — they are solved by: ✅ Better architecture ✅ Proper scaling strategies ✅ Load balancing ✅ Containerization ✅ Monitoring actual utilization

Cloud is powerful, but inefficient architecture can silently burn thousands of dollars every year.

What I’m learning is: A good cloud engineer doesn’t just deploy infrastructure.

They design systems that are scalable, reliable, and financially efficient.

#AWS #CloudComputing #DevOps #CostOptimization #EC2 #CloudArchitecture #Flask #Tech #LearningInPublic

Shivil Bhasin

• Jun 2

A deep understanding of infrastructure optimization and calibration is crucial for maximizing efficiency and performance.

Ojaswi Barotia

• Oct 8

Enterprise RAG AI: Private Doc Intelligence A fast-growing B2B software firm needed a secure, enterprise-grade Retrieval-Augmented Generation (RAG) system to query thousands of confidential internal documents (legal contracts, technical architecture specs, Notion pages, and employee SOPs) in real time without third-party data leakage.

Key Challenges:

High hallucination risk and irrelevant context retrieval using standard keyword search.

Managing multi-format files (scanned PDFs, tables, markdown) with strict access control based on user hierarchy.

Technical Implementation & Solution: • Engineered an automated ingestion pipeline in Python with LlamaIndex and LangChain for semantic chunking and metadata preservation. • Integrated a hybrid vector search architecture pairing dense embeddings (OpenAI text-embedding-3) with sparse BM25 indexing in Qdrant. • Added a cross-encoder re-ranking layer (Cohere Re-ranker) to prune low-relevance chunks, reducing API token costs by 40%. • Built robust Role-Based Access Control (RBAC) via FastAPI endpoints, ensuring departmental data isolation.

Results & Impact: • Dropped internal information retrieval time from 20 minutes to under 4 seconds. • Attained 98% factual precision with traceable in-line page citations. • Full on-prem Docker deployment ensuring 100% private data security.

Python LangChain AWS AI Automation AI Development Software Development

Nick Rudnyk

pro

• Oct 6

Which design feels more professional and trustworthy for a B2B company?

A recent website redesign for Ecoaera, a UK-based IT asset disposal company. We transformed their existing site into a modern B2B website with improved UX, stronger service pages, and SEO + AI optimisation.

Framer seo Web Design

1 voted

10 voted

91%

11 votes

Closed

Sahil Dobariya

pro

• Oct 8

Looks great !

Widada W

• Oct 7

In 2024 I took over a vet telehealth app. The previous developer was gone, nothing was in version control, and it had never made it to production.

My first instinct was to start fixing bugs. Glad I didn't. I spent the first days getting it into GitHub, setting up Docker so local dev actually worked, and wiring GitHub Actions to deploy to the server. Boring work, but after that every fix could actually ship.

Then came the real features: scheduling, Stripe, Zoom calls etc.

Lesson I keep relearning: on a stuck project, get a reliable way to ship first. Nothing fancy here, just a plain nginx server and an automated deploy. The point is that every fix goes out the same way.