CloudNestle AWS Solution Finder
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AWS Solution Finder is an AI-powered search engine for the AWS ecosystem. It indexes 10,000+ repositories from five official AWS GitHub organizations โ aws-samples, awslabs, aws-solutions, aws-ia, and aws-solutions-library-samples.
Search with plain English and get ranked results in ~10 seconds. Each repository is classified by Amazon Bedrock (Nova Pro) across 22 metadata fields including solution type, AWS services used, complexity level, freshness, and estimated setup time.
The search engine uses a hybrid approach โ 70% BM25 keyword matching + 30% FAISS semantic vector search โ delivering results that are both precise and contextually relevant. AI-generated answers are grounded in real repository data, not hallucinated.
Auto-indexed twice daily via EventBridge, so new AWS repos are searchable within 12 hours of being published.
Built solo by an AWS Community Builder with 25 years of enterprise architecture experience. Fully serverless on AWS โ Lambda, API Gateway, DynamoDB, CloudFront, S3, CDK.
Free to try โ 3 searches without signup, 10/day with a free account, unlimited with Pro.
CloudNestle AWS Solution Finder
GitHubNo CloudNestle AWS Solution Finder videos yet. You could help us improve this page by suggesting one.
CloudNestle AWS Solution Finder's answer
Unlike ChatGPT or Google, AWS Solution Finder searches real GitHub repositories โ not training data or web pages. It indexes 10,000+ repos from AWS's official GitHub organizations, classifies each with 22 metadata fields using AI, and auto-updates twice daily. You get ranked results with quality scores, freshness, complexity, and setup time estimates in ~10 seconds. Grounded in real code, not hallucinated answers.
CloudNestle AWS Solution Finder's answer
GitHub Search gives you raw results with no context. ChatGPT hallucinates repos that don't exist. AWS docs are scattered across hundreds of pages. AWS Solution Finder combines all three โ real repos, AI-powered understanding, and structured metadata โ in one search. Every result is a real, working repository with quality scores, last-updated dates, and setup time estimates. It's the fastest way to go from "which AWS service should I use?" to actual working code.
CloudNestle AWS Solution Finder's answer
AWS developers, solutions architects, and DevOps engineers who work with AWS daily and spend hours searching for the right architecture patterns, sample code, and reference implementations across GitHub, documentation, and Stack Overflow.
CloudNestle AWS Solution Finder's answer
After 25 years as a Solutions Architect, I was tired of spending 2+ hours every time I needed to find the right AWS reference architecture. 47 browser tabs, scattered docs, outdated blog posts โ and still not confident I picked the right approach. So I built what I wished existed: an AI-powered search engine that indexes all 10,000+ repos from AWS's official GitHub organizations and gives you ranked, contextual answers in 10 seconds. Built solo, bootstrapped, running entirely on AWS credits. Now sharing it with the community.
CloudNestle AWS Solution Finder's answer
Amazon Bedrock (Nova Pro), FAISS vector search, AWS Lambda, API Gateway, DynamoDB, CloudFront, EventBridge, S3, AWS CDK (TypeScript), Python 3.12
Based on our record, GitHub seems to be more popular. It has been mentiond 2476 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 4 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 5 days ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 9 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 17 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 17 days ago
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