Logstash Filter Verifier

The Logstash program for collecting and processing logs from is popular and commonly used to process e.g. syslog messages and HTTP logs.

Apart from ingesting log events and sending them to one or more destinations it can transform the events in various ways, including extracting discrete fields from flat blocks of text, joining multiple physical lines into singular logical events, parsing JSON and XML, and deleting unwanted events. It uses its own domain-specific configuration language to describe both inputs, outputs, and the filters that should be applied to events.

Writing the filter configurations necessary to parse events isn't difficult for someone with basic programming skills, but verifying that the filters do what you expect can be tedious; especially when you tweak existing filters and want to make sure that all kinds of logs will continue to be processed as before. If you get something wrong you might have millions of incorrectly parsed events before you realize your mistake.

This is where Logstash Filter Verifier comes in. In lets you define test case files containing lines of input together with the expected output from Logstash. Pass one of more such test case files to Logstash Filter Verifier together with all of your Logstash filter configuration files and it'll run Logstash for you and verify that Logstash actually return what you expect.

Before you can run Logstash Filter Verifier you need to compile it. After covering that, let's start with a simple example and follow up with reference documentation.

Installing

All releases of Logstash Filter Verifier are published in binary form for the most common platforms at github.com/magnusbaeck/logstash-filter-verifier/releases.

If you need to run the program on other platforms or if you want to modify the program yourself you can build and use it on any platform for which a Go compiler is available. Pretty much any platform where Logstash runs should be fine, including Windows.

Many Linux distributions make some version of the Go compiler easily installable, but otherwise you can download and install the latest version. You should be able to compile the source code with any reasonable up to date version of the Go compiler. The build process also requires GNU make and other GNU tools. When building on a Windows system you need a basic cygwin installation.

To download and compile the source, run these commands (pick another directory name if you like):

$ mkdir ~/go
$ cd ~/go
$ export GOPATH=$(pwd)
$ go get -d github.com/magnusbaeck/logstash-filter-verifier
$ cd src/github.com/magnusbaeck/logstash-filter-verifier
$ make

If successful you'll find an executable in the current directory. The two last commands can be replaced with an invocation of the makefile with make.

The makefile can also be used to install Logstash Filter Verifier centrally, by default in /usr/local/bin but you can change that by modifying the PREFIX variable. For example, to install it in $HOME/bin (which is probably in your shell's path) you can issue the following command:

$ make install PREFIX=$HOME

Examples

The examples that follow build upon each other and do not only show how to use Logstash Filter Verifier to test that particular kind of log. They also highlight how to deal with different features in logs.

Syslog messages

Logstash is often used to parse syslog messages, so let's use that as a first example.

Test case files are in JSON or YAML format and contain a single object with about a handful of supported properties.

Sample with JSON format:

{
  "fields": {
    "type": "syslog"
  },
  "input": [
    "Oct  6 20:55:29 myhost myprogram[31993]: This is a test message"
  ],
  "expected": [
    {
      "@timestamp": "2015-10-06T20:55:29.000Z",
      "host": "myhost",
      "message": "This is a test message",
      "pid": 31993,
      "program": "myprogram",
      "type": "syslog"
    }
  ]
}

Sample with YAML format:

fields:
  type: "syslog"
input:
  - "Oct  6 20:55:29 myhost myprogram[31993]: This is a test message"
expected:
  - @timestamp: "2015-10-06T20:55:29.000Z"
    host: "myhost"
    message: "This is a test message"
    pid: 31993
    program: "myprogram"
    type: "syslog"

In this example, type is set to "syslog" which means that the input events in this test case will have that in their type field when they're passed to Logstash. Next, in input, we define a single test string that we want to feed through Logstash, and the expected array contains a one-element object with the event we expect Logstash to emit for the given input.

Note that UTC is the assumed timezone for input events to avoid different behavior depending on the timezone of the machine where Logstash Filter Verifier happens to run. This won't affect time formats that include a timezone.

This command will run this test case file through Logstash Filter Verifier (replace all "path/to" with the actual paths to the files, obviously):

$ path/to/logstash-filter-verifier path/to/syslog.json path/to/filters

If the test is successful, Logstash Filter Verifier will terminate with a zero exit code and (almost) no output. If the test fails it'll run diff -u to compare the pretty-printed JSON representation of the expected and actual events.

The actual event emitted by Logstash will contain a @version field, but since that field isn't interesting it's ignored by default when reading the actual event. Hence we don't need to include it in the expected event either. Additional fields can be ignored with the ignore array property in the test case file (see details below).

JSON messages

I always prefer to configure application to emit JSON objects whenever possible so that I don't have to write complex and/or ambiguous grok expressions. Here's an example:

{"message": "This is a test message", "client": "127.0.0.1", "host": "myhost", "time": "2015-10-06T20:55:29Z"}

When you feed events like this to Logstash it's likely that the input used will have its codec set to "json_lines". This is something we should mimic on the Logstash Filter Verifier side too. Use codec for that:

Sample with JSON format:

{
  "fields": {
    "type": "app"
  },
  "codec": "json_lines",
  "ignore": ["host"],
  "input": [
    "{\"message\": \"This is a test message\", \"client\": \"127.0.0.1\", \"time\": \"2015-10-06T20:55:29Z\"}"
  ],
  "expected": [
    {
      "@timestamp": "2015-10-06T20:55:29.000Z",
      "client": "localhost",
      "clientip": "127.0.0.1",
      "message": "This is a test message",
      "type": "app"
    }
  ]
}

Sample with YAML format:

fields:
  type: "app"
codec: "json_lines"
ignore:
  - "host"
input:
  - '{"message": "This is a test message", "client": "127.0.0.1", "time": "2015-10-06T20:55:29Z"}'
expected:
  - @timestamp: "2015-10-06T20:55:29.000Z"
    client: "localhost"
    clientip: "127.0.0.1"
    message: "This is a test message"
    type: "app"

There are a few points to be made here:

The double quotes inside the string must be escaped when using JSON format. YAML files sometimes require quoting too; for example if the value starts with [ or { or if a numeric value should be forced to be parsed as a string.
The filters being tested here use Logstash's dns filter to transform the IP address in the client field into a hostname and copy the original IP address into the clientip field. To avoid future problems and flaky tests, pick a hostname or IP address for the test case that will always resolve to the same thing. As in this example, localhost and 127.0.0.1 should be safe picks.
If the input event doesn't contain a host field, Logstash will add such a field containing the name of the current host. To avoid test cases that behave differently depending on the host where they're run, we ignore that field with the ignore property.

Test case file reference

Test case files are JSON files containing a single object. That object may have the following properties:

codec: A string value naming the Logstash codec that should be used when events are read. This is normally "line" or "json_lines".
expected: An array of JSON objects with the events to be expected. They will be compared to the actual events produced by the Logstash process.
fields: An object containing the fields that all input messages should have. This is vital since filters typically are configured based on the event's type and/or tags. Scalar values (strings, numbers, and booleans) are supported, as are objects (containing scalars, arrays and nested objects), arrays of scalars and nested arrays. The only combination which is not allowed are objects within arrays. You can use the "dot" or bracket notation field to write test in easy way. It means that fields: {"log.file.path": "/tmp/test.log"} is equivalent to fields: {"log": {"file": {"path": "/tmp/test.log"}}}. You can also write fields: {"[log][file][path]": "/tmp/test.log"} to do the same thing.
ignore: An array with the names of the fields that should be removed from the events that Logstash emit. This is for example useful for dynamically generated fields whose contents can't be predicted and hardwired into the test case file. If you need to exclude sub fields, you need to use dot or bracket notation, i.e. log.file.path or [log][file][path] will exclude field {"log": {"file": {"path": "something"}}}.
input: An array with the lines of input (each line being a string) that should be fed to the Logstash process. If you use json_lines codec you can use dot or bracket notation for fields, making {"message": "my message", "log.file.path": "/tmp/test.log"} and {"message": "my message", "[log][file][path]": "/tmp/test.log"} equivalent to {"message": "my message", "log": {"file": {"path": "/tmp/test.log"}}}.
testcases: An array of test case hashes, consisting of a field input and a field expected, which work the same as the above mentioned input and expected, but allow to have the input and the expected event close together in the test case file, which offers a better overview. An optional description field can be used to describe the test case, e.g. as documentation. The description will be included in the program's progress messages.

Migrate to testcases

To migrate test case files from the old to the new config format, which uses the testcases array to keep the fields input and expected next to each other, the following command using jq could be used (run this command in the directory containing the test case files):

for f in `ls -1 *.json`; do jq '{ codec, fields, ignore, testcases:[[.input[]], [.expected[]]] | transpose | map({input: [.[0]], expected: [.[1]]})}' $f > $f.migrated && mv $f.migrated $f; done

This command only works for test case files, where for every line in input an element in expected exists.

Notes about the flag --sockets

The command line flag --sockets allows to use unix domain sockets instead of stdin to send the input to Logstash. The advantage of this approach is, that it allows to process test case files in parallel to Logstash, instead of starting a new Logstash instance for every test case file. Because Logstash is known to start slowly, this increases the time needed significantly, especially if there are lots of different test case files.

For the test cases to work properly together with the unix domain socket input, the test case files need to include the property codec set to the value line (or json_lines, if json formatted input should be processed).

Notes about flag --logstash-arg

The --logstash-arg flag is used to supply additional command line arguments or flags for Logstash. Those arguments are not processed by Logstash Filter Verifier other than just forwarding them to Logstash. For flags consisting of a flag name and a value, for both a seperate --logstash-arg in the correct order has to be provided. Because values, starting with one or two dashes (-) are treated as flag by Logstash Filter Verifier, for those flags the value MUST not be separated using a space but they have to be separated from the flag with the equal sign (=).

For example to set the Logstash node name the following arguments have to be provided to Logstash Filter Verifier:

--logstash-arg=--node.name --logstash-arg MyInstanceName

Notes about Logstash compatibility

Different versions of Logstash behave slightly differently and changes in Logstash may require changes in Logstash Filter Verifier. Upon startup, the program will attempt to auto-detect the version of Logstash used and will use this information to adapt its own behavior.

Starting with Logstash 5.0 finding out the Logstash version is very quick but in previous versions the version string was printed by Ruby code in the JVM so it took several seconds. To avoid this you can use the --logstash-version flag to tell Logstash Filter Verifier which version of Logstash it should expect. Example:

logstash-filter-verifier ... --logstash-version 2.4.0

Known limitations and future work

Some log formats don't include all timestamp components. For example, most syslog formats don't include the year. This should be dealt with somehow.

fbaligand/logstash-filter-verifier