The fall conference season is starting.  I will be doing a number of talks including a keynote on "future proofing" MySQL through the use of data fabrics.  Data fabrics allow you to build durable, long-lasting systems that take advantage of MySQL's strengths today but also evolve to solve future problems using fast-changing cloud and big data technologies.  The talk brings together ideas that Ed Archibald (our CTO) and I have been working on for over two decades.  I'm looking forward to rolling them out to a larger crowd.

Here are the talks in calendar order.  The first two are at MySQL Connect 2012 in San Francisco on September 30th:

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There have been a number of excellent articles about the pros and cons of automatic database failover triggered by Baron's post on the GitHub database outage.  In the spirit of Peter Zaitsev's article "The Math of Automated Failover," it seems like a good time to point out that database failure is usually not the biggest source of downtime for websites or indeed applications in general.  The real culprit is maintenance.

Here is a simple table showing availability numbers out to 5 nines and what they mean in terms of monthly down-time.

Github had a recent outage due to malfunctioning automatic MySQL failover.  Having worked on this problem for several years I felt sympathy but not much need to comment.  Then Baron Schwartz wrote a short post entitled "Is automated failover the root of all evil?"  OK, that seems worth a comment:  it's not.  Great title, though.

Selecting automated database failover involves a trade-off between keeping your site up 24x7 and making things worse by having software do the thinking when humans are not around.  When comparing outcomes of wetware vs. software it is worth remembering that humans are not at their best when woken up at 3:30am.  Humans go on vacations, or their cell phones run out of power. …

This month I have joined the team at Continuent. No stranger to the MySQL ecosystem, Continuent provides replication and clustering technology for managing data between MySQL, Oracle, PostgreSQL, Vertica and a growing list of data stores.

I have known many of the team at Continuent for some time, and will again be joining Giuseppe Maxia from our days at MySQL Inc/AB starting back in 2006.

I am looking forward to taking the hard work out of administration of MySQL systems with the simplicity of Continuent Tungsten, simplifying tasks including automatic failover, multi-master and geo cluster redundancy to a single command.

Catch me speaking at the upcoming MySQL Connect (San Francisco) and …

In late 2011 I attended a lecture by John Wilkes on Google compute clusters, which link thousands of commodity computers into huge task processing systems.  At this scale hardware faults are common.  Google puts a lot of effort into making failures harmless by managing hardware efficiently and using fault-tolerant application programming models.  This is not just good for application up-time.  It also allows Google to operate on cheaper hardware with higher failure rates, hence offers a competitive advantage in data center operation.

It's becoming apparent we all have to think like Google to run applications successfully in the cloud.  At Continuent we run our IT and an increasing amount of QA and development on Amazon Web Services …

Synchronous data replication over long distances has the sort of seductive appeal that often characterizes bad ideas.  Why wouldn't you want every local credit card transaction simultaneously stored on the other side of the planet far away from earthquake, storms and human foolishness?  The answer is simple: conventional SQL applications interact poorly with synchronous replication over wide area networks (WANs).

I spent a couple of years down the synchronous replication rabbit hole in an earlier Continuent product.  It was one of those experiences that make you a sadder but wiser person.  This article digs into some of the problems with synchronous replication and shows why another approach, asynchronous multi-master replication, is currently a better way to manage databases connected by long-haul networks.

Synchronous Replication between …

Intro

Oracle is widely use to support back-end systems.  On the other hand, MySQL is the "go-to" data management solution for the web-facing part of many businesses.  If you have both Oracle and MySQL in-house, you may already also have the need to share data between them.  In this article I'll describe software that my colleagues and I have been working on to move data from Oracle to MySQL in real-time without costing an arm and a leg.

Tungsten to the Rescue!

Latest Tungsten Replicator has many features, most of which are open-source, but the recent one for me is particularly exciting - thanks to the development done by my colleague Stephane Giron in the …

Are you looking to expand your knowledge about MySQL and MariaDB database solutions?

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An increasing number of organizations run applications that depend on MySQL multi-master replication between remote sites.   I have worked on several such implementations recently.  This article summarizes the lessons from those experiences that seem most useful when deploying multi-master on existing as well as new applications.

Let's start by defining terms.  Multi-master replication means that applications update the same tables on different masters, and the changes replicate automatically between those masters.  Remote sites mean that the masters are separated by a wide area network (WAN), which implies high average network latency of 100ms or more.  WAN network latency is also characterized by a long tail, ranging from seconds due to congestion to hours or even days if a ship runs over the wrong undersea cable.
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Experienced MySQL DBAs know that temp tables cause major problems for MySQL replication.  It turns out the converse is also true:  replication can cause major problems for temporary tables.

In a recent customer engagement we enabled Tungsten Replicator with a MySQL application that originally ran on a server that did not use replication.  QA promptly discovered reports that previously ran in 10 seconds were now running in as many minutes.  It turned out that the reports used temp tables to assemble data, and these were being written into the master binlog.  This created bloated binlogs and extremely slow reports.  We fixed the problem by enabling row replication (i.e., binlog-format=row in my.cnf).

A common DBA response to temp table problems is to try to eliminate them completely, as suggested in the excellent …