Metric Sink
The Metric Sink microservice takes metrics that have been normalized and inserts them into the Metric database.
This microservice is part of the Metric microservice pipeline. See Understanding Microservice Pipelines in Unified Assurance Concepts for conceptual information.
Autoscaling is enabled by default for this microservice. You can optionally disable autoscaling when you deploy the microservice. See Configuring Autoscaling.
This microservice provides additional Prometheus monitoring metrics. See Metric Sink Self-Monitoring Metrics.
Metric Sink Prerequisites
Before deploying the microservice, confirm that the following prerequisites are met:
-
A microservice cluster is set up. See Microservice Cluster Setup.
-
The Apache Pulsar microservice is deployed. See Pulsar.
Deploying Metric Sink
To deploy the microservice, run the following commands:
su - assure1
export NAMESPACE=<namespace>
export WEBFQDN=<WebFQDN>
a1helm install <microservice-release-name> assure1/metric-sink -n $NAMESPACE --set global.imageRegistry=$WEBFQDN
In the commands:
-
<namespace> is the namespace where you are deploying the microservice. The default namespace is a1-zone1-pri, but you can change the zone number and, when deploying to a redundant cluster, change pri to sec.
-
<WebFQDN> is the fully-qualified domain name of the primary presentation server for the cluster.
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<microservice-release-name> is the name to use for the microservice instance. Oracle recommends using the microservice name (metric-sink) unless you are deploying multiple instances of the microservice to the same cluster.
You can also use the Unified Assurance UI to deploy microservices. See Deploying a Microservice by Using the UI for more information.
Changing Metric Sink Configuration Parameters
When running the install command, you can optionally change default configuration parameter values by including them in the command with additional --set arguments. You can add as many additional --set arguments as you need.
For example:
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Set a parameter described in Default Metric Sink Configuration by adding --set configData.<parameter_name>=<parameter_value>. For example, --set configData.LOG_LEVEL=DEBUG.
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Disable autoscaling for the microservice by adding --set autoscaling.enabled=false.
-
Set an autoscaling parameter described in Metric Sink Autoscaling Configuration by adding --set autoscaling.<parameter_name>=<parameter_value>. For example, --set autoscaling.thresholds.backlogSize=2000.
Default Metric Sink Configuration
The following table describes the default configuration parameters found in the Helm chart under configData for the microservice.
| Name | Default Value | Possible Values | Notes |
|---|---|---|---|
| LOG_LEVEL | INFO | FATAL, ERROR, WARN, INFO, DEBUG | Logging level used by application. |
| STREAM_INPUT | persistent://assure1/metric/sink | Text, 255 characters | Apache Pulsar topic path. Topic at end of path may be any text value. |
Metric Sink Autoscaling Configuration
Autoscaling is supported for the Metric Sink microservice. See Configuring Autoscaling for general information and details about the standard autoscaling configurations.
The Metric Sink microservice also supports the additional configurations described in the following table.
| Name | Default Value | Possible Values | Notes |
|---|---|---|---|
| thresholds.backlogSize | 1000 | Integer | The number of items that need to be in the backlog before the autoscaling starts additional processes. |
| thresholds.totalMetricsProcessed | 400 | Integer | Total metrics processed by the microservice. If the average of total metrics processed in five minutes exceeds the threshold, pods will be scaled. |
Metric Sink Self-Monitoring Metrics
The Metric Sink microservice exposes the self-monitoring metrics described in the following table to Prometheus.
| Metric Name | Type | Description |
|---|---|---|
| metric_sink_backlog_size | Gauge | Number of items pending in the backlog |
| total_metrics_processed | Counter | Number of metrics processed |
| processing_time_per_metric | Gauge | processing time per metric from receiving it to sending it to acknowledging it |
Note:
Metric names in the database include a prefix that indicates the service that inserted them. The prefix is prom_ for metrics inserted by Prometheus. For example, total_metrics_processed is stored as prom_total_metrics_processed in the database.
Sample JSON Metric Schema
The following example shows the expected JSON file schema formats for Metric Sink.
{
"@timestamp": "2021-05-06T18:40:00.000Z",
"measurement": "iot_test",
"tags": {
"host": "some_host",
"instance": "some_instance"
},
"fields": {
"availability": 1,
"value": 123456789000,
"utilization": 0.1,
"other": 1
}
}
Although you are responsible for defining the proper format, the Metric Sink microservice tries to match the current Metric schema. For example, it cleans up slash marks (), replaces dashes (-) and spaces with underscores (_) and capitalizes letters as needed.
Debugging Metric Sink
The Metric Sink microservice consists of two components: metric-sink and telegraf. To see logs for each of the components, run the following commands (replacing appropriate parameters).
For metric-sink logs:
a1k logs <pod_name> -n <namespace> metric-sink
For telegraf logs:
a1k logs <pod_name> -n <namespace> telegraf
You can get pod names and namespaces by running the following command:
a1k get pods --all-namespaces