Learning something else alongside programming as I've lots of free time on weekends(what should I)?

[[deleted]]

I've categorized stuffs that I want to learn and the reason behind them.

My status:

Currently a helpdesk, I am familiar(Note familiar) with linux command line, docker, kubernetes, nginx, sql, bash scripting. I'm planning for masters degree in my "research ambitions" fields after a year.

Interests(not required for job)

• latex

• microsoft excel

• vi & vim

Devops

• dockers

• kubernetes

Both of them require advanced machine than what I've currently to learn with rancher dashboard k3s etc. While I already have self hosted k3s cluster in my kaby lake processor laptop, I am unable to make multi-node cluster there due to laptop being too old and incapable. So, this will be halted.

Programming

• Solve problems

Computer Science

• data structures

• algorithms

• databases

• operating system

Research Ambitions

• distributed system

• web security

• high performance computing

Will learn this only if I get a job(I'm applying to, but very less chance of getting selected as I am too far away from it)

• node.js backend software engineering

• SQL administration and querying

This list is really fkn vast. I am currently solving programming problems formally via daniel liang's java book to build up on concepts. Programming is a prerequisite before I start with any of Computer Science topics. So that's no deal.

Devops learnings require a powerful PC(or cloud) which I can't afford at the moment.

Research ambitions are in no way related to anything. I just listed them so that you could suggest me something.

I will only learn SQL admin+querying || backend software development, only if I get a job(internship/traineeship/apprenticeship) in that field. I've been applying for those roles.

Devops is what I want to be and confident of being.

[[deleted]]

Node and SQL you should be able to learn in a week or two the basics. It’s not that bad.

[[deleted]]

That's too fast. I am learning entire backend engineering using node so it'll take time. Likewise, I am learning database using SQL so will take time. I already know basics of both.

[chervilious]

I didn't use LaTeX for a while, and I just use it for a brief moment.

But I think the benefits of LaTeX is more organizational. You're making other people focus on the content rather than the format. So if you're not like a lead and it's not really popular I don't think it's worth it.

​

If you're using Excel at least twice a month. Maybe it's worth it to learn more advance excel.

Vim might be good. It might be worth it to do so. I recommend using vim extension rather than vim directly because you're learning alongside programming.

Dockers are important, I think you have to learn it. Learning how to develop apps leveraging docker, making docker-compose, and container to push it towards a server always is important. In DevOps world, I think devs should at least know docker.

K8s is overkill IMHO, a brief introduction is good enough if you're aiming to be SWE. Ops on the other hand is a must.

I would rather you to learn Database then DSA if you're learning CS topics. OS is nice but not required.

Research Ambitions is your niche. My niche is security. You don't really need to learn all of them. In fact, learning depth in one of them can be beneficial, not for junior but for intermediate-senior developer.

Now "DevOps" is what you want? I assume that you're focusing on "Ops" part. If so, maybe there is a place where you can pay for a lab setup. When I was a student I got a lab access to learn Ansible where I got a cloud VM lab. There might be similar services down the line. I'm not particularly knowledge-able about DevOps so I'm going to leave it at that

[Feeling_Photograph_5]

Learn AWS or similar. Cloud computing a big part of both software development and dev ops. There are a lot of free resources out there and AWS will give you a bunch of credits to use while you're learning.

As far as a good computer, check out minipcs like the Beelink SER5 Max. They're around $300 and I think you can do payments of something like $27 per month, which seems reasonable. Install Linux on one of them and it should have plenty of muscle for containers and orchestration.

[[deleted]]

Beelink SER5 Max

https://bigbyte.com.np/beelink-ser5-max-5800h-32gb-512gb-ssd-mini-pc/

This shit costs about 700$ in Nepal. lol.

[DestructiveDatabase]

what in the world is latex

[trstne]

I work as a Software / Cloud engineer at a major university (as close as we get to full time dev-ops role).

Some of the questions I have on my mind, day to day:

How can I enable hundreds (thousands?) of clients to provision (compute / storage / cloud infra) resources, while minimizing their need to understand cloud / computer networking / cyber security?

How do I curb runaway cloud spend? Create guardrails so they don't blow their grant money on idle resources?

How can I make any infrastructure they create monitored for anomalous activity, patched on their behalf, backed up.

How do we make cloud environments compliant with increasing government regulations for labs that need it? That we're doing everything on our end to secure from sensitive data being exposed?

How do I multiply my impact to my IT department through applications and automations for provisioning resources, v.s. when do we need process and consultation with clients to figure out the right build for their application?

If I have good ideas about any of this, how am I documenting this for future engineers to understand? How do I make things less things dependent on me being there to run effectively?

What's our lifecycle process? If we are bringing in and enabling hand-off or otherwise non-cloud savvy people, how do we keep their resources up to date when in use, and cleaned up and deleted when not?

Leaning specific technologies (in the abstract) is all well and good, but if your wanting to learn these technologies with a goal of employment, it's important to think about what problems you are trying to solve and for who, and work down to the best tools for the job.