Create CSV provider instances
To create an instance of the CSV provider, build a YAML file (instance.yml
in this example) with the definition of the instance:
Then you can create the instance for the system
using the Akamas CLI:
timestampFormat
format
timestampFormat
formatRegarding 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 resideusername
- the username used when connecting to the hostauthType
- the type of authentication to use when connecting to the file host; eitherpassword
orkey
auth
- the authentication credential; either a password or a key according toauthType
. When using keys, the value can either be the value of the key or the path of the file to import fromremoteFilePattern
- a list of remote files to be imported
Optional properties
protocol
- the protocol to use to retrieve files; eitherscp
orsftp
. Default isscp
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 isCOMPONENT
timestampColumn
- the header of the column containing the timestamp. Default isTS
timestampFormat
- the format of the timestamp (e.g.yyyy-MM-dd HH:mm:ss zzz
). Default isYYYY-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 AkamasdatasourceMetric
- 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:
Telemetry instance reference
The following represents the complete configuration reference for the telemetry provider instance.
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.
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.
Using the configured instance, the CSV File provider will perform the following operations to import the metrics:
Retrieve the file "/csv/sar.csv" from the server "127.0.0.1" using the SCP protocol authenticating with the provided password.
Use the column
hostname
to lookup components by name.Use the column
timestamp
to find the timestamps of the samples (that is expected to be in the format specified bytimestampFormat
).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.
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