<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Write-Ahead Log on Brave New Geek</title><link>https://bravenewgeek.com/tag/write-ahead-log/</link><description>Recent content in Write-Ahead Log on Brave New Geek</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 13 Sep 2018 23:39:30 -0500</lastBuildDate><atom:link href="https://bravenewgeek.com/tag/write-ahead-log/index.xml" rel="self" type="application/rss+xml"/><item><title>Introducing Liftbridge: Lightweight, Fault-Tolerant Message Streams</title><link>https://bravenewgeek.com/introducing-liftbridge-lightweight-fault-tolerant-message-streams/</link><pubDate>Fri, 27 Jul 2018 17:42:49 -0500</pubDate><guid>https://bravenewgeek.com/introducing-liftbridge-lightweight-fault-tolerant-message-streams/</guid><description>&lt;p&gt;&lt;a href="https://github.com/liftbridge-io/liftbridge"&gt;&lt;img loading="lazy" src="https://bravenewgeek.com/wp-content/uploads/2018/07/liftbridge.png"&gt;&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;&lt;a href="https://twitter.com/tyler_treat/status/1019281381493526529"&gt;Last week&lt;/a&gt; I open sourced &lt;a href="https://github.com/liftbridge-io/liftbridge"&gt;Liftbridge&lt;/a&gt;, my latest project and contribution to the &lt;a href="https://www.cncf.io/"&gt;Cloud Native Computing Foundation&lt;/a&gt; ecosystem. Liftbridge is a system for lightweight, fault-tolerant (LIFT) message streams built on &lt;a href="https://nats.io/"&gt;NATS&lt;/a&gt; and &lt;a href="https://grpc.io/"&gt;gRPC&lt;/a&gt;. Fundamentally, it extends NATS with a &lt;a href="https://kafka.apache.org/"&gt;Kafka&lt;/a&gt;-like publish-subscribe log API that is highly available and horizontally scalable.&lt;/p&gt;
&lt;p&gt;I’ve been working on Liftbridge for the past couple of months, but it’s something I’ve been thinking about for over a year. I sketched out the design for it last year and &lt;a href="https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-5-sketching-a-new-system/"&gt;wrote about it&lt;/a&gt; in January. It was largely inspired while I was working on &lt;a href="https://github.com/nats-io/nats-streaming-server"&gt;NATS Streaming&lt;/a&gt;, which I’m currently still the second top contributor to. My primary involvement with NATS Streaming was building out the early data replication and clustering solution for high availability, which has continued to evolve since I left the project. In many ways, Liftbridge is about applying a lot of the things I learned while working on NATS Streaming as well as my observations from being closely involved with the NATS community for some time. It’s also the product of scratching an itch I’ve had since these are the kinds of problems I enjoy working on, and I needed something to code.&lt;/p&gt;</description></item><item><title>Building a Distributed Log from Scratch, Part 5: Sketching a New System</title><link>https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-5-sketching-a-new-system/</link><pubDate>Tue, 23 Jan 2018 12:08:53 -0600</pubDate><guid>https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-5-sketching-a-new-system/</guid><description>&lt;p&gt;In &lt;a href="https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-4-trade-offs-and-lessons-learned/"&gt;part four&lt;/a&gt; of this series we looked at some key trade-offs involved with a distributed log implementation and discussed a few lessons learned while building NATS Streaming. In this fifth and final installment, we’ll conclude by outlining the design for a new log-based system that draws from the previous entries in the series.&lt;/p&gt;
&lt;h3 id="the-context"&gt;The Context&lt;/h3&gt;
&lt;p&gt;For context, &lt;a href="https://nats.io/"&gt;NATS&lt;/a&gt; and &lt;a href="https://nats.io/documentation/streaming/nats-streaming-intro/"&gt;NATS Streaming&lt;/a&gt; are two different things. NATS Streaming is a log-based streaming system built on top of NATS, and NATS is a lightweight pub/sub messaging system. NATS was originally built (and then open sourced) as the control plane for Cloud Foundry. NATS Streaming was built in response to the community’s ask for higher-level guarantees—durability, at-least-once delivery, and so forth—beyond what NATS provided. It was built as a separate layer on top of NATS. I tend to describe NATS as a dial tone—ubiquitous and always on—perfect for “online” communications. NATS Streaming is the voicemail—leave a message after the beep and someone will get to it later. There are, of course, more nuances than this, but that’s the gist.&lt;/p&gt;</description></item><item><title>Building a Distributed Log from Scratch, Part 2: Data Replication</title><link>https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-2-data-replication/</link><pubDate>Wed, 27 Dec 2017 12:26:55 -0600</pubDate><guid>https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-2-data-replication/</guid><description>&lt;p&gt;In &lt;a href="https://bravenewgeek.com/building-a-distributed-log-from-scratch-part-1-storage-mechanics/"&gt;part one&lt;/a&gt; of this series we introduced the idea of a message log, touched on why it’s useful, and discussed the storage mechanics behind it. In part two, we discuss data replication.&lt;/p&gt;
&lt;p&gt;We have our log. We know how to write data to it and read it back as well as how data is persisted. The caveat to this is, although we have a durable log, it’s a single point of failure (SPOF). If the machine where the log data is stored dies, we’re SOL. Recall that one of our three priorities with this system is high availability, so the question is how do we achieve high availability and fault tolerance?&lt;/p&gt;</description></item></channel></rss>