somurzakov

nation state spies can get fake identities issued legally by their own government and will be confirmed as usual during the background check

it is much easier for highly skilled hacker to get fake identity and get employed at SW than to compromise an employee - although this is longer term play

I am 99% percent sure the hackers are among the CUSTOMERS of Solar Winds.

That way they were able to live-test infected SolarWinds distro in their own controlled environment and develop all possible mitigations and techniques - the sheer amount of these evading techniques suggests they were built up over time, and not instantly.

Being Solar Winds customer and receiving infected updated versions every time gave them opportunity to perfect their techniques and hide for so long

At least that what I would do if I were a hacker and wanted to persist and be very careful about not getting detected

experienced data engineers should graduate to data architects/ML engineers and this way they can get on par with SWE, pls correct me if I am wrong.

distributed ML != Distributed DWH.

Distributed ML is tough to train because of very little control over train loop. I personally prefer using single server trainkng even on large datasets, or switch to online learning algos that do train/inference/retrain at the same time.

as for snowflake, I havent heard of people using snowflake to train ML, but sbnowflake is a killer in managed distribited DWH that you dont have to tinker and tune

I believe what you described is a job of Platform Engineer/Systems Engineer/Data lake Architect, especially JVM aspect of it. The interesting job is in the beginning when you build the cluster initially, or do major extension, after that the ops/maintenance is usually outsourced to cheap labor offshore - so this kinda job is personally not for me.

spark has dataframe API which is similar to pandas api and can be learned in one day, especially if you know python.

same for Airflow and other frameworks, it just a fancy scheduler that anyone can pick up in a couple days.

advanced proficiency in SQL and in any scripting language of your choice (C#/powershell, python) is enough to be a data engineer on any technical stack: windows/linux, on-prem/cloud, vendor specific/opensource, literally anything.

algorithmic problem solving is very close to IOI/ACM ICPC type problems, which test on combination of knowledge of data structures+algorithms and creative ability to combine both to create own algorithms while being under interview anxiety+time limti stress. Quite essential in everything internet-scale and filters top percentile candidates pretty well.

THis process is not required for your average company where IT is a cost center and CRUD-type apps generator.

an engine in electric vehicle is a commodity, heck even one from my GE washer would work for the EV

>>Safety is a characteristic of systems and not of their components >>Safety is an emergent property of systems; it does not reside in a person, device or department of an organization or system. Safety cannot be purchased or manufactured; it is not a feature that is separate from the other components of the system. This means that safety cannot be manipulated like a feedstock or raw material. The state of safety in any system is always dynamic; continuous systemic change insures that hazard and its management are constantly changing.

fits perfectly the description of Security of complex IT systems, nice way to explain why IT security marketplace is a wild wild west

Поздравляю, отличная работа! Не думали написать статью на habr.com ?

Sounds like Phoenix LiveView. I love phoenix <3

How does using Kafka come into play when implementing Actor model?

Anyone successfully implemented actor model framework over kafka?

interested in learning others' experience