A command line utility for a convenient access to Logentries logging infrastructure.
- How to use
- Repositories
- Configuration file
- Follow log files through server-side configuration
- Follow log files through your configuration file
- Using local configuration only
- List IP addresses the agent uses
- Follow logs that change their names
- Manipulate your data in transit
- Filtering file names
- System metrics (beta)
- Deployment best practices
- Linux Agent Installation
usage: le COMMAND [ARGS]
Where COMMAND is one of:
init Write local configuration file
reinit As init but does not reset undefined parameters
register Register this host
--name= name of the host
--hostname= hostname of the host
whoami Displays settings for this host
monitor Monitor this host
follow <filename> Follow the given log
--name= name of the log
--type= type of the log
followed <filename> Check if the file is followed
clean Removes configuration file
ls List internal filesystem and settings: <path>
ls ips List IP addresses used by the agent
rm Remove entity: <path>
pull Pull log file: <path> <when> <filter> <limit>
Where ARGS are:
--help show usage help and exit
--version display version number and exit
--account-key= set account key and exit
--host-key= set local host key and exit, generate key if key is empty
--no-timestamps no timestamps in agent reportings
--force force given operation
--datahub send logs to the specified data hub address
the format is address:port with port being optional
--suppress-ssl do not use SSL with API server
--yes always respond yes
--pull-server-side-config=False do not use server-side config for following files
For Debian/Ubuntu systems include this line in /etc/apt/sources.list.d/logentries.list:
deb http://rep.logentries.com/ XXX main
Replace XXX with the name of your system, i.e. one of wheezy, jessie,
lucid, precise, quantal, saucy, trusty, utopic. You also need to add Logentries
release key:
gpg --keyserver pgp.mit.edu --recv-keys C43C79AD && gpg -a --export C43C79AD | apt-key add -
Then run apt-get update and apt-get install logentries. If you want to run
the agent as daemon, install it via apt-get install logentries-daemon.
For rpm-based systems RH, CentOS, Fedora, add this in /etc/yum.repos.d/logentries.repo
[logentries]
name=Logentries repo
enabled=1
metadata_expire=1d
baseurl=http://rep.logentries.com/XXX/\$basearch
gpgkey=http://rep.logentries.com/RPM-GPG-KEY-logentries
Replace XXX with the name of your system, i.e. one of fedora18, fedora19,
fedora20, fedora21, rh5, rh6, amazonlatest, centos5, centos6. Then run yum update and yum install logentries. If you want to run the agent as daemon,
install it via yum install logentries-daemon.
The agent stores configuration in ~/.le/config for ordinary users and in
/etc/le/config for root (daemon). It is created with init or reinit
commands and can be created or modified manually.
The structure of the configuration file follows standard similar to what you
find in .git/config or Windows INI files. For example:
[Main]
user-key = e720a1e8-a7d5-4f8b-8879-854e51c9290d
agent-key = 428b888a-29ab-4079-99ec-9cb7aa2ffea7
[cassandra]
metrics-process = org.apache.cassandra.service.CassandraDaemon
path = /var/log/cassandra/system.log
token = a846bd59-a674-4088-b9fd-e72da1df5946
Main section [Main] contains agent-wide general configuration. Any other
section defines per-application settings such as log filenames and metrics.
In the main section, user-key (account key) which identifies account, and
agent-key which identifies host (host key).
Note the monitor command requires both user-key and agent-key defined.
After registering the host (via register command or specifying agent-key in
configuration) you can add a file to follow via follow command:
sudo le follow /srv/log/cassandra/system.out [--name Cassandra]
You can repeat the command for additional logs. The agent creates a new log entry in Logentries under the host specified. It will also enable the file to be followed by the agent.
Note --name is optional to specify log name as it will appear in UI and log
listing. If not specified, plain file name is used.
You need to restart the agent to pick up the new configuration:
sudo service logentries restart
Apart from server-side configuration you can configure log files to be followed locally. Locally configured logs use token-based inputs and enables to collect log entries from multiple sources into one destination log. This can be useful in an autoscaling environment. You can reuse the same configuration file multiple times without creating new hosts.
Each log to follow has a separate section in the configuration of the form:
[name]
path = /path/to/log/file
token = MY_TOKEN
Where:
- name is an identifier of the application that is added to your log entries
- path is an absolute path to the file you wish to follow
- token is the token for destination log created in Logentries
In an auto scaling environment you may not want to create a Host each time you install the agent.
To disable pulling server-side configuration (and thus avoiding communication
with Logentries API) add this line in the [Main] section of the configuration:
pull-server-side-config=False
Or specify --pull-server-side-config=False on the command like for the init
or reinit commands:
sudo le reinit --pull-server-side-config=False
Run the ls ips command to get a list of IP addresses the agent uses. These IP
addresses needs to be whitelisted in firewall.
Due to rollover policies logs are often renamed using a sequential number or the current timestamp. Luckily the Logentries agent can handle this for you. The Logentries agent can be pointed at particular folders to gather any active logs from that directory or its subdirectories using wildcards in file names. For example, the following patterns can be used with the follow command to gather logs from the given directories:
/var/log/mysystem/mylog-*.log
Using wildcards when specifying the log to follow allows for situations where you need to follow the most recent log in a particular folder. The Logentries agent looks for any active log in the folder and will monitor the events in that log.
If you want to modify log entries before they are sent to Logentries, the agent enabled you to do so via filters. Filters are useful for filtering sensitive information, obfuscating, or explicit parsing (adding key-value pairs).
Specify a Python module directory in your configuration by adding a line in the form of:
filters=/opt/le/le_filters
Create empty __init__.py to set up a module. Then add filters.py file which
contains filters dictionary. The dictionary informs the agent that for the
given log name, log ID, or token, the specified filtering function should be
used. For example the following dictionary:
filters={
"example.log": filter_logname,
"7e518e54-40e4-4c5a-88df-4559d03126e6": filter_logid,
}
Where filter_logname and filter_loguuid are functions which filters events
for the respective log. Filtering functions receive a single string containing
log entries terminated with a new line. Function can modify lines in any way
and return them back for sending to Logentries servers. Do not forget to keep
new line termination. The following skeleton displays typical structure of the
filtering function:
def filter_example( events):
# Split the block into individual log entries
parts = events.split( '\n')[:-1]
# Collect modified parts
new_parts = []
for entry in parts:
# Do something with entry
new_entry = entry # XXX
# Append new entry
new_parts.append( new_entry)
# Return modified output
return ''.join( x+'\n' for x in new_parts)
Typical filtering function is much simpler though. For example the following filtering function removes all occurrences of credit card numbers:
import re
# Credit card number matcher
CREDIT_CARD = re.compile( r'\d{4}-\d{4}-\d{4}-\d{4}')
# Credit card number replacement
CC_REPLACEMENT = 'xxxx-xxxx-xxxx-xxxx' # '-'.join( ['x'*4]*4) if you prefer
def filter_credit_card( events):
return CREDIT_CARD.sub( CC_REPLACEMENT, events)
If you want to explicitly restrict which files can the agent follow, create the
filters module as described in the previous section and define the
filter_filenames function. The filter_filenames function accepts full path to a
file which is about to be followed. The function returns True if the file name
is acceptable or False otherwise. The agent will ignore files which does not
pass this test. The following example defines filter which allows the agent to
follow log files only:
def filter_filenames( filename):
return filename.endswith( '.log')
Alternatively, the following example defines filter which denies to follow any file outside /var/log/ directory:
def filter_filenames( filename):
return filename.startswith( '/var/log/')
Note the examples above do not take into account symbolic links.
Note: The agent requires psutil library
installed. This library is commonly available from OS repositories named
python-psutil.
The agent collects system metrics regarding CPU, memory, network, disk, and processes. Example configuration may look like this:
[Main]
user-key = ...
agent-key = ...
metrics-interval = 5s
metrics-token = ...
metrics-cpu = system
metrics-vcpu = core
metrics-mem = system
metrics-swap = system
metrics-net = sum eth0
metrics-disk = sum sda4 sda5
metrics-space = /
[cassandra]
metrics-process = org.apache.cassandra.service.CassandraDaemon
Example output may look like this:
<14>1 2015-01-28T23:42:03.668428Z myhost le - cpu - user=1.1 nice=0.0 system=0.2 load=1.3 idle=98.6 iowait=0.0 irq=0.0 softirq=0.1 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668566Z myhost le - vcpu - vcpu=0 user=14.4 nice=0.0 system=0.0 load=14.4 idle=785.6 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668588Z myhost le - vcpu - vcpu=1 user=24.0 nice=0.0 system=1.6 load=25.6 idle=774.4 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668603Z myhost le - vcpu - vcpu=2 user=12.8 nice=0.0 system=1.6 load=14.4 idle=785.6 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668617Z myhost le - vcpu - vcpu=3 user=11.2 nice=0.0 system=1.6 load=12.8 idle=785.6 iowait=0.0 irq=0.0 softirq=1.6 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668631Z myhost le - vcpu - vcpu=4 user=0.0 nice=0.0 system=0.0 load=0.0 idle=800.0 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668645Z myhost le - vcpu - vcpu=5 user=4.9 nice=0.0 system=4.9 load=9.9 idle=780.3 iowait=0.0 irq=0.0 softirq=9.9 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668658Z myhost le - vcpu - vcpu=6 user=6.4 nice=0.0 system=1.6 load=8.0 idle=792.0 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668673Z myhost le - vcpu - vcpu=7 user=0.0 nice=0.0 system=0.0 load=0.0 idle=800.0 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
<14>1 2015-01-28T23:42:03.668762Z myhost le - mem - total=16770625536 available=86.8 used=45.2 free=54.8 active=12.1 inactive=26.9 buffers=0.7 cached=31.2
<14>1 2015-01-28T23:42:03.668853Z myhost le - swap - total=0 used=0.0 free=0.0 in=0 out=0
<14>1 2015-01-28T23:42:03.668977Z myhost le - disk - device=sum reads=0 writes=0 bytes_read=0 bytes_write=0 time_read=0 time_write=0
<14>1 2015-01-28T23:42:03.669071Z myhost le - disk - device=sda4 reads=0 writes=0 bytes_read=0 bytes_write=0 time_read=0 time_write=0
<14>1 2015-01-28T23:44:29.185629Z myhost le - disk - device=sda5 reads=19 writes=2135 bytes_read=81920 bytes_write=1005879296 time_read=29 time_write=33004
<14>1 2015-01-28T23:42:03.669123Z myhost le - space - path="/" size=638815010816 used=87.8 free=7.1
<14>1 2015-01-28T23:42:03.669212Z myhost le - net - net=eth0 sent_bytes=36230 recv_bytes=1260226 sent_packets=481 recv_packets=848 err_in=0 err_out=0 drop_in=0 drop_out=0
<14>1 2015-01-28T23:52:48.741521Z myhost le - cassandra - cpu_user=0.6 cpu_system=0.0 reads=250 writes=0 bytes_read=0 bytes_write=8192 fds=141 mem=4.4 total=16770625536 rss=734867456 vms=3441418240
Specify the metrics-cpu parameter to collect CPU metrics. Allowed values are
system which will normalize usage of all CPUs to 100%, or core which will
normalize usage to single CPU (typical for top command).
Example:
metrics-cpu = core
metrics-cpu = system
Example log entry:
<14>1 2015-01-28T23:42:03.668428Z myhost le - cpu - user=1.1 nice=0.0 system=0.2 load=1.3 idle=98.6 iowait=0.0 irq=0.0 softirq=0.1 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
Fields explained:
- user time spent processing user level processes with normal or negative nice value (higher priority)
- nice time spent processing user level processes with positive nice value (lower priority)
- system time spent processing system level tasks
- usage total time spent processing
- idle time spent idle, with no outstanding tasks and no incomplete I/O operations
- iowait time spent waiting for I/O operation to complete (idle)
- irq time spent servicing/handling hardware interrupts
- softirq time spent servicing/handling soft interrupts. Commonly servicing tasks scheduled independently of hardware interrupts.
- steal time not available for the virtual machine, i.e. stolen by hypervisor in concurrent virtual environments
- guest time spent running guest operating systems with normal nice value
- guest_nice time spent running guest operating systems with positive nice value
- vcpus total number of CPUs
Specify the metrics-vcpu parameter to collect metrics for each individual CPU.
The only viable value is core which will normalize usage to single CPU.
Example:
metrics-vcpu = core
Example log entry:
<14>1 2015-01-28T23:42:03.668566Z myhost le - vcpu - vcpu=0 user=14.4 nice=0.0 system=0.0 load=14.4 idle=785.6 iowait=0.0 irq=0.0 softirq=0.0 steal=0.0 guest=0.0 guest_nice=0.0 vcpus=8
Fields are similar to CPU section.
Specify the metrics-mem parameter to collect memory metrics. The only viable
value is system.
Example:
metrics-mem = system
Example log entry:
<14>1 2015-01-28T23:42:03.668762Z myhost le - mem - total=16770625536 available=86.8 used=45.2 free=54.8 active=12.1 inactive=26.9 buffers=0.7 cached=31.2
Fields explained:
- total physical memory size in bytes
- available amount of memory that is available for processes, typically free + buffers + cached
- used memory used by OS (includes caches and buffers)
- free memory not used by OS
- active memory marked as recently used (dirty pages)
- inactive memory marked as not used (old pages)
- buffers memory reserved for temporary I/O storage
- cached part of the memory used as disk cache, tmpfs, vms, and memory-mapped files
Specify the metrics-swap parameter to collect swap area metrics. The only
viable value is system.
Example:
metrics-swap = system
Example log entry:
<14>1 2015-01-28T23:42:03.668853Z myhost le - swap - total=0 used=0.0 free=0.0 in=0 out=0
Fields explained:
- total size of all swap areas
- used % of swap areas being used
- free % of swap areas being unused
- in input traffic in bytes
- out output traffic in bytes
In the metrics-net configuration parameter specify network interfaces for
which the agent will collect metrics.
Special interfaces are all which instructs the agent to follow all interfaces
(including lo), select which will follow selected interfaces such as eth and
wlan, and sum which aggregates usage of all interfaces in the system.
Example:
metrics-net = eth0
metrics-net = sum select
metrics-net = all
Example log entry:
<14>1 2015-01-28T23:42:03.669212Z myhost le - net - net=eth0 sent_bytes=36230 recv_bytes=1260226 sent_packets=481 recv_packets=848 err_in=0 err_out=0 drop_in=0 drop_out=0
Fields explained:
- net network interface
- bytes_sent number of bytes sent since last record
- bytes_recv number of bytes received since last record
- packets_sent number of packets sent since last record
- packets_recv number of packets received since last record
- err_in number of errors while receiving
- err_out number of errors while sending
- drop_in number of incoming packets which were dropped
- drop_out number of outgoing packets which were dropped
In the metrics-disk configuration parameter specify devices for which will the agent
collect metrics.
Special device is all which instructs the agent to collect metrics for all devices.
Example:
metrics-disk = sum sda4 sda5
metrics-disk = all
Example log entry:
<14>1 2015-01-28T23:44:29.185629Z myhost le - disk - device=sda5 reads=19 writes=2135 bytes_read=81920 bytes_write=1005879296 time_read=29 time_write=33004
Fields explained:
- device device name
- reads number of read operations since last record
- writes number of write operations since last record
- bytes_read number of bytes read since last record
- bytes_write number of bytes written since last record
- time_read time spent reading from device in milliseconds since last record
- time_write time spent writing to device in milliseconds since last record
In the metrics-space configuration parameter specify mount points for which
will the agent collect usage metrics.
Example:
metrics-space = /
Example log entry:
<14>1 2015-01-28T23:42:03.669123Z myhost le - space - path="/" size=638815010816 used=87.8 free=7.1
Fields explained:
- path disk mount point
- size size of the disk in bytes
- used % of disk space used
- free % of disk space free
Note that used + free might not reach 100% in certain cases.
To follow a particular process, specify a pattern matching process' command
argument in metrics-process. Specify this parameter in a separate section.
Example:
[cassandra]
metrics-process = org.apache.cassandra.service.CassandraDaemon
Example log entry:
<14>1 2015-01-28T23:52:48.741521Z myhost le - cassandra - cpu_user=0.6 cpu_system=0.0 reads=250 writes=0 bytes_read=0 bytes_write=8192 fds=141 mem=4.4 total=16770625536 rss=734867456 vms=3441418240
Fields explained:
- cpu_user the amount of time process spent in user mode
- cpu_system the amount of time process spent in system mode
- reads the number of read operations since last record
- writes the number of write operations since last record
- bytes_read the number of bytes read since last record
- bytes_write the number of bytes written since last record
- fds the number of open file descriptors
- mem % of memory used
- total total amount of memory
- rss resident set size - the amount of memory this process currently has in main memory
- vms virtual memory size - the amount of virtual memory the process has allocated, including shared libraries
Logentries agent provides several methods of configuration. The method you choose depends on the size and structure of your environment. You are free to combine both methods.
For small systems such as single web server, mail server, workstation, the easiest way is to register the host and logs followed via the agent. The agent will create a Host entry in the UI and send log entries to this Host for each followed file. Configuration will be stored on Logentries systems and the agent will pull the latest configuration during startup.
For large systems such as computational clusters, autoscaling setups, the meaning of particular host is losing its meaning as they are becoming ephemeral. The best option for these systems is to share the same configuration across servers in the cluster, using locally defined logs only with pull-server-side-config set to False. Logs are separated per application. Applications of the same type (i.e. web, mail, DB) will send data to their own log. Hosts are distinguished by their hostname which is appended to each log entry.
There are two ways to install the LE Agent.
- Interactive - Simply run
sudo bash logentries_install.sh. This will download and install the LE Agent on your machine and prompt you for your Logentries account email and Logentries account password. - Automated, using your Logentries' account key - Run the Linux installer using your Logentries Account Key as the first command line arguemnt as in
sudo bash logentries_install.sh <account_key>for examplesudo bash logentries_install.sh xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. This will bypass the prompts for your Email or password and simply download and install the LE Agent adding this Host and its Logs to your Account.
To attain your Logentries Account Key from the Logentries web UI see: https://logentries.com/doc/accountkey/