You: Uploaded image System Design — Metrics Monitoring & Alerting System how to approach this problem (thinking steps ) and design HLD , ChatGPT: Designing a High-Level Design (HLD) for a Metrics Monitoring & Alerting System, as illustrated in your diagram, involves several key steps and components. Here’s a structured approach to tackle this:

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+ DOCKER + DOCKER compose + k8s setup | 3min | mac | tested # https://youtu.be/LtooWDUL1Js (install docker + docker compose + k8s) Test Minikube/k8s : $minikube dashboard -> open k8s dashboard +method 1 : use above docker setup k8s +method 2: Minikube/k8s Setup : https://minikube.sigs.k8s.io/docs/start/ 1. run below command $curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-darwin-amd64 $sudo install minikube-darwin-amd64 /usr/local/bin/minikube

issue Error: INSTALLATION FAILED: Kubernetes cluster unreachable: Get "https://kubernetes.docker.internal:6443/version": dial tcp 127.0.0.1:6443: connect: connection refused or I0512 09:50:11.168857 94624 versioner.go:58] Get "https://kubernetes.docker.internal:6443/version?timeout=5s": dial tcp 127.0.0.1:6443: connect: connection refused or

Your thinking is mostly correct. Here are some popular examples and their approaches: Google Search:Approach: Semantic Search Explanation: Uses natural language processing to understand the meaning of the query and find relevant documents, even if they don't contain the exact keywords. Vector Database: Yes Google Image Search: Approach: Similarity Search Explanation: Finds images similar to the query image by comparing vector representations of images.