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lb - LDAP benchmarking tool like an Apache Bench

lb is simple benchmarking tool for LDAP Server. This tool is designed to allow perform by command line such as Apache Bench.

Build

Build requirements

  • Golang 1.16 or later

Install lb command

$ go get github.com/longsleep/lb/cmd/lb

Usage

lb have setup sub-command that preparing for benchmarking.

Setup subcommand

  • Add base entry
$ lb setup base -b 'dc=example,dc=com' ldap://localhost/

This command add base entry.

  • Add single entry
$ lb setup person --cn 'test' ldap://localhost/
  • Add range entries
$ lb setup person --cn 'user%d' --last 10 ldap://localhost/

ADD Benchmarking

$ lb add -c 10 -n 1000 ldap://localhost/

This command add following entries 1000 times with 10 threads.

dn: cn=${THREADID}-${COUNT},dc=example,dc=com
cn: ${THREADID}-${COUNT}
sn: sn
userPassword: secret

Use --uuid option if you want to use UUID for cn.

$ lb add -c 10 -n 1000 --uuid ldap://localhost/
dn: cn=${UUID},dc=example,dc=com
cn: ${UUID}
sn: sn
userPassword: secret

DELETE Benchmarking

$ lb delete -c 10 -n 1000 ldap://localhost/

This command make delete request with following DNs:

cn=0-0,dc=example,dc=com
...
cn=9-999,dc=example,dc=com

BIND Benchmarking

  • BIND Benchmarking with single entry
$ lb bind -c 10 -n 1000 -D cn=user,dc=example,dc=com -w secret ldap://localhost/

This command make 1000 times bind request with 10 threads.

  • BIND Benchmarking with ranged random entries
$ lb bind -D 'cn=user%d,dc=example,dc=com' -w secret --last 10 ldap://localhost/

SEARCH Benchmarking

  • Search Benchmarking with random filters
$ lb search -c 10 -n 1000 -a "(cn=user%d)" --last 1000 -s sub ldap://localhost/

This command make 1000 times search request with following random filters:

(cn=user1)
...
(cn=user1000)

MODIFY Benchmarking

$ lb modify -c 10 -n 1000 --attr sn --value modified ldap://localhost/

This command make modify request with following DNs:

cn=0-0,dc=example,dc=com
...
cn=9-999,dc=example,dc=com

TODO

  • modrdn benchmarking

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LDAP benchmarking tool like an Apache Bench

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