MongoDB - OpenTelemetry Collector

MongoDB is a source-available cross-platform document-oriented database program. The Sumo Logic app for MongoDB supports logs and metrics from the open source version of MongoDB. The App is tested on the 4.4.4 version of MongoDB.

MongoDB logs are sent to Sumo Logic through OpenTelemetry filelog receiver.

Log types

The MongoDB logs are generated in files as configured in the configuration file /var/log/mongodb/mongodb.log. For more details on MongoDB logs, see this link.

Fields creation in Sumo Logic for MongoDB

Following are the Fields which will be created as part of MongoDB App install if not already present.

db.cluster.name. User configured. Enter a name to identify this MongoDb cluster. This cluster name will be shown in the Sumo Logic dashboards.
db.system. Has fixed value of mongodb.
deployment.environment. User configured. This is the deployment environment where the Mongodb cluster resides. For example: dev, prod or qa.
sumo.datasource. has a fixed value of mongodb.

Prerequisites

By default, MongoDB logs are stored in a log file.

Configure logging verbosity in MongoDB : MongoDB logs have six levels of verbosity. All logging settings are located in MongoDB.conf. To select a level, set loglevel to one of:
- 0 is the MongoDB's default log verbosity level, to include Informational messages.
- 1 to 5 increases the verbosity level to include Debug messages.
Configure MongoDB to log to a Local file: Configuring MongoDB logs to go to log files. By default, MongoDB logs are stored in /var/log/mongodb/mongodb.log. The default directory for log files is listed in the MongoDB.conf file. To configure the log output destination to a log file, use one of the following settings, either in the configuration file or command-line:
- Configuration file: The systemLog.destination option for file.
  - Command-line:
    - The --logpath option for mongod for file.
    - The --logpath option for mongos for file.

For Linux systems with ACL Support, the otelcol install process should have created the ACL grants necessary for the otelcol system user to access default log locations. You can verify the active ACL grants using the getfacl command. Install the ACL in your Linux environment, if not installed.

The required ACL may not be supported for some rare cases, for example, Linux OS Distro, which is officially not supported by Sumo Logic. In this case, you can run the following command to explicitly grant the permissions.

sudo setfacl -R -m d:u:otelcol-sumo:r-x,d:g:otelcol-sumo:r-x,u:otelcol-sumo:r-x,g:otelcol-sumo:r-x <PATH_TO_LOG_FILE>

Run the above command for all the log files in the directory that need to be ingested, which are not residing in the default location.

If Linux ACL Support is not available, traditional Unix-styled user and group permission must be modified. It should be sufficient to add the otelcol system user to the specific group that has access to the log files.

For Windows systems, log files which are collected should be accessible by the SYSTEM group. Use the following set of PowerShell commands if the SYSTEM group does not have access.

$NewAcl = Get-Acl -Path "<PATH_TO_LOG_FILE>"
# Set properties
$identity = "NT AUTHORITY\SYSTEM"
$fileSystemRights = "ReadAndExecute"
$type = "Allow"
# Create new rule
$fileSystemAccessRuleArgumentList = $identity, $fileSystemRights, $type
$fileSystemAccessRule = New-Object -TypeName System.Security.AccessControl.FileSystemAccessRule -ArgumentList $fileSystemAccessRuleArgumentList
# Apply new rule
$NewAcl.SetAccessRule($fileSystemAccessRule)
Set-Acl -Path "<PATH_TO_LOG_FILE>" -AclObject $NewAcl

Collection configuration and app installation

As part of data collection setup and app installation, you can select the App from App Catalog and click on Install App. Follow the steps below.

Step 1: Set up Collector

note

If you want to use an existing OpenTelemetry Collector, you can skip this step by selecting the Use an existing Collector option.

To create a new Collector:

Select the Add a new Collector option.
Select the platform where you want to install the Sumo Logic OpenTelemetry Collector.

This will generate a command that you can execute in the machine environment you need to monitor. Once executed, it will install the Sumo Logic OpenTelemetry Collector.

Step 2: Configure integration

In this step the user needs to provide the path to the mongo db log file configured as part of above steps. Typically the logs are located at the location: /var/log/mongodb/mongodb.log.

You can add any custom fields which you want to tag along with the data ingested in Sumo. Click on the Download YAML File button to get the yaml file.

Step 3: Send logs to Sumo Logic

Once you have downloaded the yaml file as described in the previous step, follow the below steps based on your platform.

Copy the yaml file to /etc/otelcol-sumo/conf.d/ folder in the Mongodb instance which needs to be monitored.
restart the collector using:

 sudo systemctl restart otelcol-sumo

Copy the yaml file to C:\ProgramData\Sumo Logic\OpenTelemetry Collector\config\conf.d folder in the machine which needs to be monitored.
Restart the collector using:

Restart-Service -Name OtelcolSumo

Copy the yaml file to /etc/otelcol-sumo/conf.d/ folder in the Mongodb instance which needs to be monitored.
Restart the otelcol-sumo process using:

 otelcol-sumo --config /etc/otelcol-sumo/sumologic.yaml --config "glob:/etc/otelcol-sumo/conf.d/*.yaml" 

Copy the yaml file into your Chef cookbook files directory files/<downloaded_yaml_file>.
Use a Chef file resource in a recipe to manage it. cookbook_file '/etc/otelcol-sumo/conf.d/<downloaded_yaml_file>' do mode 0644 notifies :restart, 'service[otelcol-sumo]', :delayed end
Add the recipe to your collector setup to start collecting the data. Every team typically has their established way of applying the Chef recipe. The resulting Chef recipe should look something like:
```
cookbook_file '/etc/otelcol-sumo/conf.d/<downloaded_yaml_file>' do
    mode 0644
    notifies :restart, 'service[otelcol-sumo]', :delayed
end
```

Place the file into your Ansible playbook files directory.

Run the Ansible playbook.

ansible-playbook -i inventory install_sumologic_otel_collector.yaml
-e '{"installation_token": "<YOUR_TOKEN>", "collector_tags": {<YOUR_TAGS>}, "src_config_path": "files/conf.d"}'

Place the file into your Puppet module files directory modules/install_otel_collector/files/<downloaded_yaml>.

Use a Puppet file resource to manage it.

file { '/etc/otelcol-sumo/conf.d/<downloaded_yaml_file>':
    ensure => present,
    source => 'puppet:///modules/install_otel_collector/<downloaded_yaml_file>',
    mode => '0644',
    notify => Service[otelcol-sumo],
  }

Apply the Puppet manifest. Every team typically has their established way of applying the Puppet manifest. The resulting Puppet manifest should look something like:

node 'default' {
    class { 'install_otel_collector'
      installation_token => '<YOUR_TOKEN>',
      collector_tags => { <YOUR_TAGS> },
    }

    service { 'otelcol-sumo':
      provider => 'systemd',
      ensure => running,
      enable => true,
      require => Class['install_otel_collector'],
    }

    file { '/etc/otelcol-sumo/conf.d/<downloaded_yaml_file>':
      ensure => present,
      source => 'puppet:///modules/install_otel_collector/<downloaded_yaml_file>',
      mode => '0644',
      notify => Service[otelcol-sumo],
    }
  }

After successfully executing the above command, Sumo Logic will start receiving data from your host machine.

Click Next. This will install the app (dashboards and monitors) to your Sumo Logic Org.

Dashboard panels will start to fill automatically. It's important to note that each panel fills with data matching the time range query and received since the panel was created. Results won't immediately be available, but within 20 minutes, you'll see full graphs and maps.

Sample log messages

{
   "t":{
       "$date":"2021-05-21T10:22:57.373+00:00"
   },
   "s":"I",
   "c":"NETWORK",
   "id":51800,
   "ctx":"conn500659",
   "msg":"client metadata",
   "attr":{
       "remote":"127.0.0.1:49472",
       "client":"conn500659",
       "doc":{
           "application":{
               "name":"MongoDB Shell"
           },
           "driver":{
               "name":"MongoDB Internal Client",
               "version":"4.4.4"
           },
           "os":{
               "type":"Linux",
               "name":"PRETTY_NAME=\"Debian GNU/Linux 10 (buster)\"",
               "architecture":"x86_64",
               "version":"Kernel 4.4.0-62-generic"
           }
       }
   }
}

Sample queries

Dashboard: MongoDB - Errors and Warnings, Panel: Errors by Component

deployment.environment=* db.cluster.name=* sumo.datasource=mongodb  | json "log"  as _rawlog nodrop
| if  (isEmpty(_rawlog), _raw, _rawlog)  as _raw
| json field=_raw "t.$date"  as  timestamp
| json field=_raw "s"  as severity
| json field=_raw "c"  as component
| json field=_raw "ctx"  as context
| json field=_raw "msg"  as msg
| where severity in ("E")
| count by component

Viewing MongoDB dashboards

If no relevant data was received within the time range of the Panel, the Panel will be empty.

Overview

The MongoDB - Overview dashboard provides an at-a-glance view of MongoDB health, performance and problems causing errors.

Use this dashboard to:

Identify Slow CRUD and DB commands.
Gain insights into Errors logs by component and context.
Number of up servers.

Errors and Warnings

The MongoDB - Errors and Warnings dashboard shows errors and warnings by the MongoDB component.

Use this dashboard to:

Determine components producing multiple errors or warnings.

Logins and Connections

The MongoDB - Logins and Connections dashboard shows geo location of client connection requests, failed connection logins by geo location, and count of failed login attempts.

Use this dashboard to:

Determine potential hacking attempts.
Determine location of attacks.

Query Logs

The MongoDB - Query Logs dashboard shows read and write query trends.

Use this dashboard to:

Monitor abnormal spikes in Query volume.
Identify the read versus write ratio of your application queries. Adjusting indexes to improve query performance.

Replication Logs

The MongoDB - Replication Logs dashboard shows replica deletes/updates/inserts trend and replica state.

Use this dashboard to:

Monitor replication state and replication events like inserts/updates/commands per second.
Track Replication Oplog window to identify replication delay.

Sharding

The MongoDB - Sharding dashboard dashboard shows sharding related errors, events, failures and number of chunks moving between shards.

Use this dashboard to:

Identify Sharding errors and warnings.
Gain insights into Chunk operations.

Log types​

Fields creation in Sumo Logic for MongoDB​

Prerequisites​

Collection configuration and app installation​

Step 1: Set up Collector​

Step 2: Configure integration​

Step 3: Send logs to Sumo Logic​

Sample log messages​

Sample queries​

Viewing MongoDB dashboards​

Overview​

Errors and Warnings​

Logins and Connections​

Query Logs​

Replication Logs​

Sharding​

Log types

Fields creation in Sumo Logic for MongoDB

Prerequisites

Collection configuration and app installation

Step 1: Set up Collector

Step 2: Configure integration

Step 3: Send logs to Sumo Logic

Sample log messages

Sample queries

Viewing MongoDB dashboards

Overview

Errors and Warnings

Logins and Connections

Query Logs

Replication Logs

Sharding