ThinkPad Thunderbolt 3 Dock | Suspend Problem

Thursday, Oct 11, 2018 | 2 minute read

Ricardo Ferreira

As mentioned in this post; I have acquired a new laptop from Lenovo, the ThinkPad X1 Extreme. Since I will be working from home sometimes, I thought it would be a good idea to buy an dock station for it.

So I decided to buy the following dock station:

ThinkPad Thunderbolt 3 Dock

It is a nice dock station solution, especially because it connects everything to the laptop via Thunderbolt 3. However; since I am running Fedora in my laptop, things couldn’t be that easy right?

Firstly, by default any bolt-based device is not enabled in Fedora. So I have found this blog that helped on this matter. After that all ports were working as expected. FYI, I haven’t had to turn the SELinux off in order to work.

Secondly; I have found that any time I boot the laptop with the lid closed, the O.S would turn to a suspended state after the login. It was like if after the login - I would have closed the lid off. After some digging across many Fedora forums, I found a thread where people were discussing some-old-knobs-that-used-to-work-on-previous-versions.

Anyone that uses Linux might be used to these kind of thing, but I guess I haven’t used Linux as much as I should to get used to it. Anyway, in one of those threads I have found the proper solution. Here are the steps:

   1) sudo vi /etc/systemd/logind.conf
   2) Uncomment the property **HandleLidSwitch
**   3) Set the value of this property to "ignore"
   4) sudo systemctl restart systemd-logind

That is it. After that you should have everything working =)

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Open Source

I contribute to LangChain4j, an idiomatic open source Java library for building LLM-powered applications on the JVM. Recent work includes adding native vector search embedding stores so developers can build RAG, recommendation engines, and AI memory systems.

I also ported RedisVL to Go, an open source, AI-native client that brings vector search, semantic caching, LLM memory, semantic routing, rerankers, and an MCP server to the Redis ecosystem for Golang developers.

Speaking

I’ve been speaking at conferences since 2008 and doing it full time as part of my work since 2018. Some of the events I’ve spoken at include AWS re:Invent, Microsoft Ignite, Google Cloud Next, KubeCon, Oracle OpenWorld, QCon, Strange Loop, Kafka Summit, Pulsar Summit, JavaOne, DevNexus, JFokus, JNation, and All Things Open.

Recordings of my talks live on my YouTube channel, and the code I write for talks, demos, and tutorials is on my GitHub.

Who am I?

I work at the intersection of distributed systems, AI, and data infrastructure, turning complex technology into things developers can understand, adopt, and build with.

Lately, that means hands-on AI engineering: building vector search, semantic caching, agent memory, and RAG into the data layer; contributing to LangChain4j and RedisVL for Golang; and figuring out how to make AI agents secure enough to ship.

The AI-native work isn’t a pivot. It draws on the same systems-design foundation I’ve built for 20+ years, moving data fast, at scale, close to compute, watching where systems break; now applied to vectors and agents. I have worked on event streaming with Apache Kafka and Flink at AWS and Confluent; observability at Elastic; as well as RDBMS, NoSQL, and Big Data at Oracle. That foundation is exactly what separates AI demos that work on stage from AI systems that survive production.

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