pryz

4 ms·

1.
Firetiger: Long Horizon Agents in Production(blog.firetiger.com)
6 points by pryz 7mo ago|1 comments
2.
Worktrunk: Git worktree management for parallel AI agent workflows(worktrunk.dev)
4 points by pryz 9mo ago|0 comments
3.
by pryz 9mo ago
Jared: "We are sending out a proposal for Stacked Diffs on @GitHub to trusted design partners to gather initial feedback over the next few days. From there we’ll iterate and share the gameplan"
4.
Stacked Diffs on GitHub(twitter.com)
22 points by pryz 9mo ago|2 comments
5.
A New Chapter for Our Built World(bedrockrobotics.com)
3 points by pryz 1y ago|1 comments
6.
by pryz 1y ago
https://github.com/cloud-hypervisor/cloud-hypervisor or something else?
7.
by pryz 1y ago
Love Zed! Would love it even more with Helix/Kakoune style binding :)
8.
by pryz 2y ago
This is great! Are you considering opening a proposal for GORANDSEED? Could be really useful to generalize the approach!
9.
by pryz 2y ago
> By embracing DynamoDB as your metadata layer, systems stand to gain a lot. Yes yes yes. However, DynamoDB can be expensive very quickly :]
10.
Runtime code generation and execution in Go: Part 1(mathetake.github.io)
3 points by pryz 2y ago|0 comments
11.
by pryz 2y ago
Like many developers, we've built our fair share of workflows that export data to 3rd-party services. They always start simple: pull data, hit an API, job done! Then the problems show up. We hit API limits, services go down, and those
12.
Your async workflow needs an upgrade, not another queue(stealthrocket.tech)
1 points by pryz 2y ago|1 comments
13.
by pryz 2y ago
Distributed coroutines are a perfect fit for Python! We're excited to explain how they work and what you can do with them! Also happy to answer any questions :)
14.
by pryz 3y ago
Hi HN, We've had enough of traditional orchestration frameworks. That's why we created dispatch.run, aiming to streamline coding by integrating resilience more naturally. The core of our solution? Distributed Coroutines. These are
15.
by pryz 3y ago
Except that way many many AWS services can't do ipv6.
16.
Expert Eyes by Squint – Exclusively for Apple Vision Pro(squint.ai)
2 points by pryz 3y ago|0 comments
17.
by pryz 3y ago
The post from Polar Signal blog https://www.polarsignals.com/blog/posts/2023/12/13/embracing... Exciting!
18.
by pryz 3y ago
Forking Go means that you have to maintain a copy. That's a lot of work. Instead, the idea is to implement coroutine as a library and work toward an integration with the Go stblib.
19.
by pryz 3y ago
https://research.swtch.com/coro might be an interesting read.
20.
by pryz 3y ago
Congrats on the launch! Continuous profiling is a game changer and once you use it on your production systems you can't do without it.
21.
by pryz 3y ago
This is cool! Profiling interpreted languages is no easy task and it's nice to see eBPF leveraged for it.
22.
by pryz 3y ago
The answer is: it's complicated. Which is most of the time the answer in the WASI world. For this case it's complicated because some runtime supports https://github.com/WebAssembly/threads which mostly contai
23.
by pryz 6y ago
The idea is that we are running few multi-tenant Kafka clusters to amortize the operation cost. These clusters host many topics with different topology depending on different requirements, cost profile and scale. Some clusters are hosting h
24.
by pryz 6y ago
I guess we just haven't got the need to use ACL yet. This may be something we will look later on. We have been started to implement what's needed to leverage things like SASL in our instrumentation but we are not there yet (see h
25.
by pryz 6y ago
At Segment we manage clusters which are both on ECS and EKS. We didn't want to tie our Kafka management to the container orchestration. If I'm right the Strimzi operator is also managing the brokers. Here we only focus on the topi
26.
by pryz 6y ago
Segment employee here. Yes, we looked at Terraform to manage our topics. We are big Terraform user to manage our infrastructure. We mostly didn't go that way because we didn't want to have to manage the Terraform state. We also wa