To install the CSV File provider, create a YAML file (called provider.yml in this example) with the specification of the provider:

Then, you can then install the provider with the Akamas CLI:

To create an instance of the CSV provider, build a YAML file (instance.yml in this example) with the definition of the instance:

# CSV Telemetry Provider Instance
provider: CSV File
config:
 address: host1.example.com
 authType: password
 username: akamas
 auth: akamas
 remoteFilePattern: /monitoring/result-*.csv
 componentColumn: COMPONENT
 timestampColumn: TS
 timestampFormat: YYYY-MM-dd'T'HH:mm:ss
metrics:
 - metric: cpu_util
   datasourceMetric: user%

Then you can create the instance for the system using the Akamas CLI:

akamas create telemetry-instance instance.yml system

timestampFormat format

Regarding the timestamp format, please notice that while the week-year format YYYY is compliant with the ISO-8601 specification, but you should replace it with the year-of-era format yyyy if you are specifying a timestampFormat different from the ISO one. For example:

• Correct: yyyy-MM-dd HH:mm:ss

• Wrong: YYYY-MM-dd HH:mm:ss

You can find detailed information on timestamp patterns in the Patterns for Formatting and Parsing section on the DateTimeFormatter (Java Platform SE 8) page.

Configuration options

When you create an instance of the CSV provider, you should specify some configuration information to allow the provider to correctly extract and process metrics from your CSV files.

You can specify configuration information within the config part of the YAML of the instance definition.

Required properties

• address - a URL or IP identifying the address of the host where CSV files reside

• username - the username used when connecting to the host

• authType - the type of authentication to use when connecting to the file host; either password or key

• auth - the authentication credential; either a password or a key according to authType. When using keys, the value can either be the value of the key or the path of the file to import from

• remoteFilePattern - a list of remote files to be imported

Optional properties

• protocol - the protocol to use to retrieve files; either scp or sftp. Default is scp

• fieldSeparator - the character used as a field separator in the csv files. Default is ,

• componentColumn - the header of the column containing the name of the component. Default is COMPONENT

• timestampColumn - the header of the column containing the timestamp. Default is TS

• timestampFormat - the format of the timestamp (e.g. yyyy-MM-dd HH:mm:ss zzz). Default is YYYY-MM-ddTHH:mm:ss

You should also specify the mapping between the metrics available in your CSV files and those provided by Akamas. This can be done in the metrics section of the telemetry instance configuration. To map a custom metric you should specify at least the following properties:

• metric - the name of a metric in Akamas

• datasourceMetric - the header of a column that contains the metric in the CSV file

The provider ignores any column not present as datasourceMetric in this section.

The sample configuration reported in this section would import the metric cpu_util from CSV files formatted as in the example below:

TS,                   COMPONENT,  user%
2020-04-17T09:46:30,  host,       20
2020-04-17T09:46:35,  host,       23
2020-04-17T09:46:40,  host,       32
2020-04-17T09:46:45,  host,       21

Telemetry instance reference

The following represents the complete configuration reference for the telemetry provider instance.

provider: CSV File            # this is an instance of the Csv provider
config:
 address: host1.example.com   # the adress of the host with the csv files
 port: 22                     # the port used to connect
 authType: password           # the authentication method
 username: akamas             # the username used to connect
 auth: akamas                 # the authentication credential
 protocol: scp                # the protocol used to retrieve the file
 fieldSeparator: ","          # the character used as field separator in the csv files
 remoteFilePattern: /monitoring/result-*.csv    # the path of the csv files to import
 componentColumn: COMPONENT                     # the header of the column with component names
 timestampColumn: TS                            # the header of the column with the time stamp
 timestampFormat: YYYY-mm-ddTHH:MM:ss         # the format of the timestamp
metrics:
 - metric: cpu_util                             # the name of the Akamas metric
   datasourceMetric: user%                      # the header of the column with the original metric
   staticLabels:
    mode: user                                  # (optional) additional labels to add to the metric

The following table reports the configuration reference for the config section

The following table reports the configuration reference for the metrics section

Use cases

Here you can find common use cases addressed by this provider.

Linux SAR

In this use case, you are going to import some metrics coming from SAR, a popular UNIX tool to monitor system resources. SAR can export CSV files in the following format.

hostname, interval,     timestamp, 		        %user,	%system,      %memory
machine1, 600,		2018-08-07 06:45:01 UTC,	30.01,	20.77,		96.21
machine1, 600,		2018-08-07 06:55:01 UTC,	40.07,	13.00,		84.55
machine1, 600,		2018-08-07 07:05:01 UTC,	5.00,	90.55,		89.23

Note that the metrics are percentages (between 1 and 100), while Akamas accepts percentages as values between 0 and 1, therefore each metric in this configuration has a scale factor of 0.001.

You can import the two CPU metrics and the memory metric from a SAR log using the following telemetry instance configuration.

provider: CSV File
config:
  remoteFilePattern: /csv/sar.csv
  address: 127.0.0.1
  port: 22
  username: user123
  auth: password123
  authType: password
  protocol: scp
  componentColumn: hostname
  timestampColumn: timestamp
  timestampFormat: yyyy-MM-dd HH:mm:ss zzz
metrics:
- metric: cpu_util
  datasourceMetric: %user
  scale: 0.001
  staticLabels:
    mode: user
- metric: cpu_util
  datasourceMetric: %system
  scale: 0.001
  staticLabels:
    mode: system
- metric: mem_util
  scale: 0.001
  datasourceMetric: %memory

Using the configured instance, the CSV File provider will perform the following operations to import the metrics:

1. Retrieve the file "/csv/sar.csv" from the server "127.0.0.1" using the SCP protocol authenticating with the provided password.

2. Use the column hostname to lookup components by name.

3. Use the column timestamp to find the timestamps of the samples (that is expected to be in the format specified by timestampFormat).

4. Collect the metrics (two with the same name, but different labels, and one with a different name):

   • cpu_util: in the CSV file is in the column %user and attach to its samples the label "mode" with value "user".

   • cpu_util: in the CSV file is in the column %system and attach to its samples the label "mode" with value "system".

   • mem_util: in the CSV file is in the column %memory.

The CSV provider collects metrics from CSV files and makes them available to Akamas. It offers a very versatile way to integrate custom data sources.

Prerequisites

This section provides the minimum requirements that you should match before using the CSV File telemetry provider.

Network requirements

The following requirements should be met to enable the provider to gather CSV files from remote hosts:

• Port 22 (or a custom one) should be open from Akamas installation to the host where the files reside.

• The host where the files reside should support SCP or SFTP protocols.

Permissions

• Read access to the CSV files target of the integration

Akamas supported version

• Versions < 2.0.0 are compatibile with Akamas until version 1.8.0

• Versions >= 2.0.0 are compatible with Akamas from version 1.9.0

Supported component types

The CSV File provider is generic and allows integration with any data source, therefore it does not come with support for a specific component type.

Setup the data source

To operate properly, the CSV file provider expects the presence of four fields in each processed CSV file:

• A timestamp field used to identify the point in time a certain sample refers to.

• A component field used to identify the Akamas entity.

• A metric field used to identify the name of the metric.

• A value field used to store the actual value of the metric.

These fields can have custom names in the CSV file, you can specify them in the provider configuration.