Set up network edge router via V2Ray


Hello! Long time no see! I have been heavily using an iOS app called “Quantumult X” (a.k.a. QX) these days, mainly for the following reasons:

  • Easy to setup and lots of tutorials/scripts online that you can add and learn
  • You can add VPN servers, add flexible routing rules e.g., SSID-based switching, and subscribe to public servers (not recommended out of privacy/security concerns)
  • You can do MITM rewrites that enable you to have premium features on other apps for free

Overall I’m very happy with this app but I do find some limitations:

Set up IKEv2 VPN on a Mikrotik Router


I got rid of my AT&T router a few days back and managed to have a Mikrotik router hAP ac² as an alternative. One benefit of using a mikrotik router, specifically, its RouterOS, is the customizability to add cool features to my home network. I have very slow traffic when using the AT&T home network when visiting some websites, e.g., weibo, so I want to route them via a VPN running on oracle cloud.

Notes on OCI (Oracle Cloud Infrastructure)


Some of my services are too light that I don’t want to run them endlessly on my beefy home server. One reason is that I want better availability and clearly it’s hard (a better word probably is expensive) to achieve that in my current set up. So I decided to go for the Cloud, after all… I was a cloud TA!

Private Docker Registry


I have been using docker containers for a while and quite amazed by its simplicity and power. Someday in the previous week when I was migrating/re-deploying my pleroma instance from my SurfaceGo ubuntu machine to my home lab, I found I need more private repos on docker hub. Docker hub by default only provides 1 private repo for normal users, which is clearly not what I want. So I decided to build my own docker registry and deploy it as a service in my home lab machine.



MLOps is an ML engineering culture and practice that aims at unifying ML system development (Dev) and ML system operations (Ops).

MLOps is the natural progression of DevOps in the context of AI… and emphasizes consistent and smooth development of models and their scalability.

In simple words, MLOps refers to applying DevOps principles to ML systems.