hermanb
I think within the next few months we can actually get her to go to the potty by herself. She’s 15 months now.
This industry wasn’t just good. It did destroy babies sensitivity to soiling.
You can also integrate it in clients by adding payment/reward claim headers.
We disallow writing back to GitHub to avoid this issue, and manage stages through branches, combined with directories for overlays. Things can get out of sync, but comparing branches is easily automated.
How can you forge a token? Did they use quantum machinery to retrieve a JWT Private Key? Did they factor RSA keys?
But no, they used a bug/weakness to exchange a token.
This is the point of the article. There is no software involved. It can’t be hacked.
Or why aren’t more people interested in this?
Not sure, but maybe injecting into commonly used libraries via subdependencies is seen as a more effective method, getting more focus. Would be interesting to have a broader analysis of malicious artifacts!
Is GitHub storing those published tags and avoiding tampering by only letting you use those tags once? Are they warning or blocking runs if you tamper? …
I’m really curious because it seems like SUCH a giant risk otherwise.
I believe this is now hardened a bit by setting the CNAME to a GitHub domain with the user/org as subdomain.
I was actually in the process of tweaking Netlify CMS to be more easily hostable yourself without depending on the Netlify Pro plans as much. Basically involves hosting a combination of Netlify Identity and Git Gateway compliant backends in GCP CloudRun or AWS Lambda. Maybe even making it easy to configure a build pipeline on CloudBuild.
I wanted to use this for small business websites, but also configuration management and translations for projects at work. Sounds like FlyCode is a great (not self-built) alternative I can recommend. Great business model as well. Almost no databases needed (auth only?) and easy to host stateless on serverless offerings. Scales linearly
https://www.cell.com/cell-reports-physical-science/pdf/S2666...
If processing units store all data in memory, it doesn’t scale linearly. Maybe sharing is assumed?
I’d like to see some better examples of this if anyone has any!
The advantages of RxFiddle above Zipkin-likes are: - the means to extract the right information. The tool integrates with RxJS, and the format is universal accross Rx’s of other languages. - the visualization which is a better fit, compared to trace spans. I didn’t use Zipkin in practice though, does it have other visualizations than spans?
Of course RxFiddle is nothing like zipkin in terms of how polished it is and how much it is carried by the community. RxFiddle so far has been my research result and while it is open source, I’ve not received contributions, so feel free to share more insights or efforts!