TILs
Fueling Curiosity, One Insight at a Time
At Codemancers, we believe every day is an opportunity to grow. This section is where our team shares bite-sized discoveries, technical breakthroughs and fascinating nuggets of wisdom we've stumbled upon in our work.
- Borg was/is google's internal container management system for more than 10 years, basically a pre-curser to K8 https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43438.pdf
- about alias_method, alias_method_chain and then prepend https://hashrocket.com/blog/posts/module-prepend-a-super-story
- nice one on schedulers (kubernetes et al) https://medium.com/@cindysridharan/schedulers-kubernetes-and-nomad-b0f2e14a896
- Go doesn't have Functional generics like map, reduce, fold etc because it encourages imperative for loops
- https://github.com/mperham/sidekiq/wiki/Signals Sidekiq can't be restarted. It will always be
TERM -t+ Start - monitoring sneakers via statsd https://github.com/jondot/sneakers/wiki/Metrics
- was wonderring why google has a seperate email and password page for login https://support.google.com/mail/forum/AAAAK7un8RUoAsE-6wmaSU/?hl=en
- Imgix has got face detection https://docs.imgix.com/apis/url/size/crop This is very cool, and interesting :)
- If you want to know when a file is removed, run this command
git log -1 -- <path>. In order to get path, you can search for the file content ingit log -p - Javascript has a
withstatement https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Statements/with - Add Lets Encrypt certs to Ruby apps might be easier with https://github.com/sdaubert/letscert
- Add Lets Encrypt certs to Ruby apps might be easier with https://github.com/sdaubert/letscert
- subdomain attacks http://resources.infosecinstitute.com/attacks-over-dns/
- Elixir/Phoenix framework packages bootstrap 3.3.5, but doesn't say explicitly
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Your competitors are already using AI. The question is how fast you want to unlock the value.
Don't know where to start?
AI is everywhere but it's unclear which investments will actually move your metrics and which are expensive experiments.
Your data isn't ready
Most AI projects fail at the data layer. Pipelines, quality, access all need work before LLMs can deliver value.
Internal teams are stretched
Your engineers are shipping product. They don't have capacity to also become AI specialists with production-grade experience.
Legacy systems block everything
Aging, undocumented codebases make AI integration slow, risky, and expensive. They need to move first.
Don't worry. We've got you covered.
Start with the audit.