5-Step Guide to Deploying Web Apps on Modern Cloud Platforms

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Modern platform-as-a-service (PaaS) providers like Railway, Render, and Fly.io have simplified cloud deployment by automating builds through Git-based workflows. Developers need a basic web application, Git, a GitHub account, and an account on one of these platforms to get started. Key preparation steps include using dynamic port binding, defining an explicit start script, and keeping sensitive credentials out of version control using a .gitignore file. Once a GitHub repository is linked to the chosen platform, it automatically detects the project type, injects environment variables securely, and triggers a live deployment. After a successful build, the platform assigns a public URL, and all future commits to the main branch trigger automatic redeployments without any manual intervention.

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Django 6.1's FETCH_PEERS cuts N+1 query loops from 2,001 queries to just 2

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ProgrammingDEV Community ·

Langfuse fills the observability gap left by traditional APM tools for AI agents

Conventional observability platforms like Grafana and Datadog excel at monitoring infrastructure and HTTP performance but cannot detect AI-specific failures such as hallucinations, wrong tool selection, or poor response quality. These semantic and reasoning-level issues leave no trace in standard metrics, making it nearly impossible to diagnose why an AI agent underperformed in a specific interaction. Langfuse is an open-source LLM engineering platform that addresses this blind spot through tracing, prompt management, evaluation, and experimentation features. Unlike general APM tools, it treats AI applications as continuously evolving systems that improve through iterative feedback loops driven by user signals and prompt version comparisons. The platform also solves the problem of hardcoded prompts by centralizing them with native versioning and environment-based deployment controls, removing the need for full code deployment cycles on every prompt adjustment.

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ProgrammingDEV Community ·

How to Build a RAG System on AWS Using Terraform, Bedrock, S3, and OpenSearch

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