Announcing the release of LogCabin 1.1! This is the second stable release of the LogCabin coordination service, which includes a C++ implementation of the Raft consensus algorithm.
LogCabin 1.0
LogCabin 1.0 is out! This is the first stable release of the LogCabin coordination service, which includes a C++ implementation of the Raft consensus algorithm. If you're new to these, I recently spoke about Raft and a little about LogCabin at the Sourcegraph Hacker Meetup in San Francisco; watch the video for a visual walk-through of how Raft works.
LogCabin.
This is the sixth in a series of blog posts detailing the ongoing development of LogCabin. This entry describes progress towards the upcoming 1.0.0 release of LogCabin, a useful new command-line client to access LogCabin, and several other improvements.
LogCabin.
This is the fifth in a series of blog posts detailing the ongoing development of LogCabin. This entry describes a new cluster-wide monotonic clock used for client session expiry, a new tool to dump out the contents of a LogCabin server's log and snapshot, a couple of performance improvements, and several changes around how server IDs and addresses are assigned and used.
LogCabin.
This is the fourth in a series of blog posts detailing the ongoing development of LogCabin. This entry describes LogCabin's new storage module and several other recent improvements.
LogCabin.
This is the third in a series of blog posts detailing the ongoing development of LogCabin. This entry describes a new tool to extract information from LogCabin servers and a tricky bug that occurred when unregistering handlers from the event loop.
LogCabin.
This is the second in a series of blog posts detailing the ongoing development of LogCabin. This entry describes the battle of adding timeouts to the client library API. Timeouts are useful for implementing leases in client applications. For example, a client might want to assert its lease but give up after few seconds, and in case of a timeout, it might need to crash or stop other processes from doing things that may no longer be safe.
LogCabin.
This is the first in a series of blog posts detailing the ongoing development of LogCabin. This first entry catches up on the developments from when I started working with Scale Computing in November, so it's longer than most of the future updates will be.
The theme of this entry is getting started in a new environment. Up until now, I'd done nearly all of the development of LogCabin on my laptop and on the RAMCloud cluster. Running it somewhere new uncovered a bunch of implicit assumptions baked-in about the environment, so it exposed a new set of issues and bugs. This is fairly inevitable when it comes to low-level systems code, and there's a lot of value in working through it. LogCabin is significantly easier to run now than it was before, and it should be easier for the rest of you to install on your systems, too.
Grad School
Well, I spent the last five years getting my Ph.D. in Stanford's Computer Science department. I won't do that justice here, but I'll fill in the story briefly so that subsequent posts make sense. I was part of Professor John Ousterhout's group, which is primarily focused on RAMCloud, a large-scale in-memory distributed storage system.