Most of my work in DevOps isn’t in front of my text editor writing scripts. It’s spent hopping between dashboards, drafting emails, doing RCA, teaching dev team members how to use pipelines, and getting requirements from them for designing new pipelines. Then inevitably debating with them about design considerations when they ask for a set of procedures that won’t pan out.
Until your AI is a fully fledged team member who everyone can feel comfortable engaging with as if they were a real human, you cannot possibly begin to automate this.
Most of my work in DevOps isn’t in front of my text editor writing scripts.
Mine either - we use azure devops, octopus, etc - tools that automate devops. Most of devops is automated across the board - no big companies are manually kicking off builds for every PR and pushing the files around the place and then manually deploying them - it’s all automated using devops tools. Having AI build and manage these pipelines seems like a logical place to use it, as they are all just about creating steps using pieces from previous steps and other systems.
You absolutely could have AI create a pipeline to build, test, and deploy a solution, and then test the actual deployed solution. The AI is essentially just the coordinator here, tying together the other devops tools.
Why do you think AI can’t easily be the supervisor for pipelines and create new ones? It’s basically just creating steps that are well known from building a branch to deploying it.
While the job does deal heavily in automating things, it only automates Boolean things. Looking at a platform and seeing why and where it’s failing is not a Boolean thing, and never will be. It’s the same reason we still don’t have machines that repair cars over 100 years after their introduction.
Okay bud, go and tell AWS, Google, Salesforce, and any other of these companies who think “AI” is an answer to everything, because they’ve all had very public outages due to this exact same thing in the past few months.
You have no idea what DevOps is or how it works if you think any of this is easily done or solved with these junk tools.
Been running Ops teams for decades, kid. Look at alllll the people agreeing with me, and disagreeing with you. You have the unearned wisdom of a struggling Junior Dev. If you had any experience, you’d know how embarrassing it would be to attempt to brag about working for “multi-billion dollar companies” 🤣🤣🤣🤣
Yes, those big, big companies are where ALL the good engineering jobs are at. Where all the interesting work is being done 🤣🤣🤣🤣
Exactly. DevOps engineers are already super skilled at using automation where appropriate, but knowing how and when to do that is still an extremely human task
Tried to figure out yesterday why a user couldn’t ssh into a server, tried LLMs to figure it out, completely useless. Had to go into some log file somewhere to find out the one who set up the server made a specific group for ssh and if a user wasn’t in that group they couldn’t connect. The LLMs (ChatGPT and Gemini) gave me bullshit about changing flags in the sshd config…
Cool story. LLMs can’t see error messages in logs if you don’t give them access to it. Had you given the AI agent access to those files? Or were you just using a standalone LLM with no access to the system?
DevOps cannot be automated away. So stupid.
DevOps is one of the most automated parts of software development and deployment actually.
Article seems like complete bullshit anyway.
Most of my work in DevOps isn’t in front of my text editor writing scripts. It’s spent hopping between dashboards, drafting emails, doing RCA, teaching dev team members how to use pipelines, and getting requirements from them for designing new pipelines. Then inevitably debating with them about design considerations when they ask for a set of procedures that won’t pan out.
Until your AI is a fully fledged team member who everyone can feel comfortable engaging with as if they were a real human, you cannot possibly begin to automate this.
Mine either - we use azure devops, octopus, etc - tools that automate devops. Most of devops is automated across the board - no big companies are manually kicking off builds for every PR and pushing the files around the place and then manually deploying them - it’s all automated using devops tools. Having AI build and manage these pipelines seems like a logical place to use it, as they are all just about creating steps using pieces from previous steps and other systems.
You absolutely could have AI create a pipeline to build, test, and deploy a solution, and then test the actual deployed solution. The AI is essentially just the coordinator here, tying together the other devops tools.
Devops is often figuring out why automation didn’t work.
Absolutely, but that’s not an argument against what i said.
I feel like it’s directly contradicting what you were implying…
It absolutely isn’t. Doing the automation is DevOps as well. Do you think that tools like Octopus Deploy or Azure DevOps don’t work, or aren’t DevOps?
DevOps is not executing the automation, but designing it. DevOps is not manually spinning up pods but writing the automation that does so.
Why do you think AI can’t easily be the supervisor for pipelines and create new ones? It’s basically just creating steps that are well known from building a branch to deploying it.
Try it out and you’ll see. Amazon seems to be doing great with it.
…noooooo, it most definitely isn’t.
While the job does deal heavily in automating things, it only automates Boolean things. Looking at a platform and seeing why and where it’s failing is not a Boolean thing, and never will be. It’s the same reason we still don’t have machines that repair cars over 100 years after their introduction.
AI can see why and where it’s failing too if it has the appropriate permissions and access.
No it’s not. DevOps is all software, repairing cars is not. Car ECUs can tell you exactly what is wrong with your car.
🤣
Okay bud, go and tell AWS, Google, Salesforce, and any other of these companies who think “AI” is an answer to everything, because they’ve all had very public outages due to this exact same thing in the past few months.
You have no idea what DevOps is or how it works if you think any of this is easily done or solved with these junk tools.
AI in devops caused their outages?
Do you even know what Octopus is for example? Azure DevOps?
Again, refer to my first comment because you’re out of your league here 🤣🤦
Already replied to that and showed why you’re wrong.
I do DevOps and Software Dev for multi-billion dollar companies btw.
Been running Ops teams for decades, kid. Look at alllll the people agreeing with me, and disagreeing with you. You have the unearned wisdom of a struggling Junior Dev. If you had any experience, you’d know how embarrassing it would be to attempt to brag about working for “multi-billion dollar companies” 🤣🤣🤣🤣
Yes, those big, big companies are where ALL the good engineering jobs are at. Where all the interesting work is being done 🤣🤣🤣🤣
My GAWD, child. W O W 🤦
Exactly. DevOps engineers are already super skilled at using automation where appropriate, but knowing how and when to do that is still an extremely human task
Tried to figure out yesterday why a user couldn’t ssh into a server, tried LLMs to figure it out, completely useless. Had to go into some log file somewhere to find out the one who set up the server made a specific group for ssh and if a user wasn’t in that group they couldn’t connect. The LLMs (ChatGPT and Gemini) gave me bullshit about changing flags in the sshd config…
Cool story. LLMs can’t see error messages in logs if you don’t give them access to it. Had you given the AI agent access to those files? Or were you just using a standalone LLM with no access to the system?
Easy fix: give an LLM root access to all production critical servers and allow everyone in the company to chat with it.
First reaction: fear.
Second: I chuckled. Because I thought of some VP-level enforcing this joke as SOP.
And then a little more fear, as a treat.
Haha if that happens it is time to get out fast
Automation with a lot of validation steps that are not very obvious. Because if they were, we’d have automated them away.