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I wanted to learn Kubernetes, but the options were either "build a local lab" or pay for expensive classes built around cloud environments. I wanted something you could just open and learn from. So I built a browser-based cluster simulation with lessons to follow along.
It behaves like Kubernetes, but it's just JavaScript under the hood. Enough to run kubectl commands, create resources, and watch their lifecycle play out. There's also a live cluster visualizer so you can see your nodes, Pods, and containers in real time.
Once you've covered the concepts, you can jump into CKA drills. Each drill is a standalone, time-boxed scenario that mirrors the real exam format: a broken cluster state, a concrete task, and a pass-or-fail outcome.
The goal isn't to simulate the exam. It's to build the reflex of diagnosing and fixing things quickly, so that when you sit the real exam, the commands and the reasoning are already automatic.
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# 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 / about 22 hours 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 / 6 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 / 13 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 / 14 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 14 days ago
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