81–90 of 374 posts
Genuine question: how did the IBM acquisitions of Red Hat and HashiCorp turn out? For Red Hat, there's no longer an official "public" distribution of RHEL, but apart from that they seemingly have been left alone and able to continue to develop their own products. But that's only my POV as a user of OSS Red Hat products at home and of RHEL and OpenShift at work.
I migrated our company off Terraform to Pulumi as a direct result of the acquisition.
I worked for IBM Cloud about 6+ years ago. While there, we had to connect to a Softlayer VPN to get into our Jira instance. My VPN account and Jira account never got provisioned so I couldn't connect nor see the Jira board. My team-mates couldn't even assign a ticket to me b/c of this. They would just put my initial's in the ticket summary and send me a slack of the details. It was right before I left that we got our…
Kafka is already past it's prime time. Time for new solutions for the oldest problem - sending a message.
I'm still convinced the vast majority of kafka implementations could be replaced with `SELECT * FROM mytable ORDER BY timestamp ASC`
The second you approach any kind of scale, this falls apart and/or you end up with a more expensive and worse version of Kafka.
Kafka is already past it's prime time. Time for new solutions for the oldest problem - sending a message.
Earlier quoted context omitted.
I hope Hashicorp survives. A few higher ups I’ve talked to there made it seem like IBM wants to learn from them, not force their old ways onto Hashicorp. We’ll see. That one is still pretty new.
Not to be cynical but that's said a lot in acquisitions by bigger companies to motivate some people to stay, but just doesn't seem to happen.
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I was in the midst of writing a snarky reply and then realized my actual issue with Kafka is that people reach for it way too often and use it in ways that don't really make sense. Kind of like how people use docker for evrything, when what you really should be doing is learn how to package software.
Ops here, Docker is packaging software. Agree on the Kafka thing though. I've seen so many devs trip over Kafka topics, partitions and offsets when their throughput is low enough that RabbitMQ would do fine.
The people distributing software should shut them damn up about how the rest of the system it runs in is configured. (But not you, your job is packaging full systems.)
That said, it seems to me that this is becoming less of a problem.
Earlier quoted context omitted.
I'm still convinced the vast majority of kafka implementations could be replaced with `SELECT * FROM mytable ORDER BY timestamp ASC`
Sure, if you're working on a small homelab with minimal to no processing volume. The second you approach any kind of scale, this falls apart and/or you end up with a more expensive and worse version of Kafka.
I was surprised how far sqlite goes with some sharding on modern SSDs for those in-between scale services/saas
This is so fascinating to me. I mean how IBM keeps taking over other companies, but they consistently deliver low quality/bottom-tier services and products. Why do they keep doing the same thing again and again? How are they generating actual revenue this way? Ok, so does anyone remember 'Watson'? It was the chatgpt before chatgpt. they built it in house. Why didn't they compete with OpenAI like Google and Anthropic…
I do. I remember going to a chat once where they wanted to get people on-board in using it. It was 90 minutes of hot air. They "showed" how Watson worked and how to implement things, and I think every single person in the room knew they were full of it. Imagine we were all engineers and there were no questions at the end.
Comparing Watson to LLMs is like comparing a rock to an AIM-9 Sidewinder.
This is so fascinating to me. I mean how IBM keeps taking over other companies, but they consistently deliver low quality/bottom-tier services and products. Why do they keep doing the same thing again and again? How are they generating actual revenue this way? Ok, so does anyone remember 'Watson'? It was the chatgpt before chatgpt. they built it in house. Why didn't they compete with OpenAI like Google and Anthropic…
Why in the world would economists need to study this? It's been known that large bureaucracies have been dysfunctional for over a couple of decades now if not centuries. The large reason is because 1) the incentives to do great work are not there (most of the credit for a huge company's success goes to the CEO who gets 100X the salary of a regular worker while delivering usually pretty much nothing) 2) politics usual…