AnarchyApe

Fault injection tool for hadoop cluster from yahoo anarchyape

Compilation

[Java]

cd src/main/java
download log4j.ar and commons-cli.jar

javac -cp .:log4j-1.4.12.jar:commons-cli-1.2.jar ape/*.java

[Perl]

   perl Makefile.PL
   cpan -i JSON
   make
   make test
   make install

Running

[Perl] ./ape.pl [remote_ip_list_file]

[Java]

java -cp .:log4j-1.4.12.jar apr/Main

log file: /var/log/ape.log

Currently, to create a scenario, the user constructs a shell script specifying the types of errors to be injected or fail- ures to be simulated, one after another. A sample line in a scenario file could be as follows:

java -jar ape.jar -remote cluster-ip-list.xml -fb lambda -k lambda
	where the -fb is a “Fork Bomb” injection, the -k is a “Kill
	One Node” command, and the lambda specifies the failure rates.

Users can define lambda parameters by computing Mean Time Between Failures (MTBF) of a system. MTBF is defined to be the average (or expected) lifetime of a system and is one of the key decision-making criteria for data center infrastructure systems [1]. Equipment in data centers is going to fail, and MTBF helps with predicting which systems are the likeliest to fail at any given moment. Based on previous failure statistics, users can develop an estimate of MTBF for various equipment failures; however, determining MTBFs for many software failures is challenging.

[1] W. Torell and V. Avelar. Performing effective MTBF comparisons for data center infrastructure. http://www.apcmedia.com/salestools/ASTE-5ZYQF2_R1_EN.pdf.

Available Commands

Here are some common failures in Hadoop environments:

• Data node is killed
• Application Master (AM) is killed
• Application Master is suspended
• Node Manager (NM) is killed
• Node Manager is suspended
• Data node is suspended
• Tasktracker is suspended
• Node panics and restarts
• Node hangs and does not restart
• Random thread within data node is killed
• Random thread within data node is suspended
• Random thread within tasktracker is killed
• Random thread within tasktracker is suspended
• Network becomes slow
• Network is dropping significant numbers of packets
• Network disconnect (simulate cable pull)
• One disk gets VERY slow
• CPU hog consumes x% of CPU cycles
• Mem hog consumes x% of memory
• Corrupt ext3 data block on disk
• Corrupt ext3 metadata block on disk