I Created a K8s Course to Help Engineers Gain Mechanical Sympathy

Hacker News

Hi HN, I wanted to share a personal journey that began in 2017 when Kubernetes was still a new and somewhat intimidating tool. Back then, I was working as a fullstack engineer, and most of my company's systems ran on Kubernetes. I knew nothing about it until a coworker conducted a hands-on session during lunch, explaining the basics and how to use it for deploying applications. This session was a turning point for me. It helped me develop what I like to call "mechanical sympathy" – understanding the tools we use and how they operate best. This concept has been incredibly valuable throughout my career, enabling me to work more effectively and smoothly across various projects. Since then, I've worked on numerous projects involving Kubernetes, even bootstrapping clusters from scratch. The knowledge I gained from that initial session has been a foundation for my growth as an engineer. Recognizing the impact of that experience, I've decided to create a practical, hands-on course to help others gain a similar understanding of Kubernetes. My goal is to demystify Kubernetes and provide a solid foundation for engineers who want to develop mechanical sympathy for the systems they work on. If you're interested in learning more, you can check out the course at ZenKubernetes.com. I'd love to hear your thoughts and experiences with Kubernetes as well. Cheers, Gunnar

Visit product View on Hacker NewsJul 17, 2024

Share card

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, plain · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

I created a tool to help engineers/developers get a job more easily54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I created a tool to help engineers/developers get a job more easily

Hacker News2

Cherry MX Mechanical Switches – KeyMouse46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Cherry MX Mechanical Switches – KeyMouse

Hacker News1

WristWatching – A Free Course About Mechanical Watches51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

WristWatching – A Free Course About Mechanical Watches

Hacker News2

I created a Udemy course about How to extend Keycloak(programmatically)70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I created a Udemy course about How to extend Keycloak(programmatically)

Hacker News8

Created TestAutomationU for QA engineers. Grew to 20k users in 6m51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Created TestAutomationU for QA engineers. Grew to 20k users in 6m

Hacker News1

I created a design course (free for a day)47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I created a design course (free for a day)

Hacker News3

NewsFreak: A newsreader I initially created for myself40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

NewsFreak: A newsreader I initially created for myself

Hacker News1

I'm tired of corrupt US politicians, so I created this38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I'm tired of corrupt US politicians, so I created this

Hacker News334

My grandfather died so I created RIP35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My grandfather died so I created RIP

Hacker News1

Why I created Picket35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Why I created Picket

Hacker News1

Browse all products Analyze your launch