vania-janet/multiturn-rag-retrieval-data huggingface dataset:
* UI
* API







 Managing volume spike protection and costs 

Configure index rates alerts in your Activity Tracker instance to monitor and be alerted of unexpected spikes in your data volumes. Use the index rate to analyze and predict costs associated with storage of searchable data.

Index rates are calculated based on data that is ingested over the last 30 days and collected in 5 minute intervals.

Data collection commences on January 31, 2022 for existing instances. For new instances, data collection starts from the day that the instance is provisioned.

The standard hourly index rate is used to identify spikes or deviations in data volumes. The standard deviation is calculated by comparing the average hourly index rate with the average of the same hour over a rolling 30 day period. The severity of a spike is measured in standard deviations.

The z-score represents the count of standard deviations. You can use it to predict costs associated with storage of searchable data.



 How are index rates calculated 

The number of log lines that are indexed, that is, the number of log lines that are available for search, are collected every 5 minutes.

A day is based on a 24 hour period that is based on UTC time zone.

To calculate the daily average index rate, the following formula is applied:



1. The total number of indexed lines for the past hour, that is, the number of log lines over 1 hour rolling period, is collected.
2. The total number of indexed lines per hour is then divided by 60 to get the average of log lines per minute.
3. The average log lines per minute is then divided by 60 to get the average of log lines per second.
4. The index rate is calculated as the average value of all index rates that are calculated over 24 hours.



To calculate the hourly average index rate, also known as the standard hourly index rate, the following formula is applied:



1. The total number of indexed lines for the past hour, that is, the number of log lines over 1 hour rolling period, is collected.
2. The total number of indexed lines per hour is then divided by 60 to get the average of log lines per minute.
3.
[Learn more](https://docs.sysdig.com/en/docs/sysdig-monitor/dashboards/configure-panels/types-of-panels/number-panel/).
* Table Panel: Use a table panel to monitor actual values instead of visual representations. The Table panel displays metric data in tabular form. [Learn more](https://docs.sysdig.com/en/docs/sysdig-monitor/dashboards/configure-panels/types-of-panels/table-panel/).
* Text: Use a text panel to provide context or information in the dashboard. [Learn more](https://docs.sysdig.com/en/docs/sysdig-monitor/dashboards/configure-panels/types-of-panels/text/).
* Toplist: Use a toplist panel to display metric values in order. [Learn more](https://docs.sysdig.com/en/docs/sysdig-monitor/dashboards/configure-panels/types-of-panels/toplist/).



You can copy, change the scope, duplicate, delete, export, and explore panels.

You can export data from a panel. Consider the following information when you export data:



* You can export data to a json file from a line chart.
* You can export data to a csv file from a table chart or from a line chart.



There is a limit of 10000 rows per export.





 Explore 

In the Explore section, you can view and troubleshoot key metrics and entities of your infrastructure stack through any of the following tabs:



* Metrics: Use this section to view and analyze individual metrics.

When you analyze metrics, you can drill down into layers of your infrastructure hierarchy and view granular-level data. You can use the Grouping selection to control how entities are organized in Explore such as All Workloads, Containerized Apps, DaemonSets, Deployments, and more.

In the metrics tab, you can view and analyze individual metrics.
)](https://cloud.ibm.com/docs/monitoring?topic=monitoring-platform_metrics_workingplatform_metrics_working_dash)[![Configuring an alert on a platform metric](https://cloud.ibm.com/docs-content/v1/content/bcd8b79ca2ed73bfcaefb20051f12cb6400286ab/atracker/images/platform_metrics_task_4.svg)](https://cloud.ibm.com/docs/monitoring?topic=monitoring-platform_metrics_workingplatform_metrics_working_alert)[![Controlling access by using teams](https://cloud.ibm.com/docs-content/v1/content/bcd8b79ca2ed73bfcaefb20051f12cb6400286ab/atracker/images/platform_metrics_task_5.svg)](https://cloud.ibm.com/docs/monitoring?topic=monitoring-platform_metrics_workingplatform_metrics_working_team)





 Viewing metrics for Activity Tracker Event Routing V1 API 

You monitor metrics in the Monitoring web UI.

To monitor Activity Tracker Event Routing metrics, you must launch the Monitoring UI for the instance that is enabled for platform metrics in the region where you are using Activity Tracker Event Routing. For more information, see [Launching the Monitoring UI from the Observability page](https://cloud.ibm.com/docs/monitoring?topic=monitoring-launchlaunch_step2).

You can use the IBM Activity Tracker Event Routing Overview predefined dashboard template to monitor Activity Tracker Event Routing in IBM Cloud.

To open the predefined Activity Tracker Event Routing template, complete the following steps from the Monitoring UI:



1. In the Monitoring UI, go to Dashboards > Dashboard templates > IBM.
2. Select IBM Activity Tracker Event Routing Overview.



You cannot modify a dashboard template. However, you can copy the template and create a custom dashboard that you can then configure.
Smart scaling 

Smart scaling uses machine learning to provide predictions based on historical workload patterns. By analyzing the data on the Administering > Workload patterns page, you can learn how to optimize the usage of your system resources.

You can obtain more information about the following system resources:



* Historical and Predicted NZP (Netezza Performance Metric)
* Historical or Suggested Contour Profile
* Confidence score





 Seed models 

Seed models are pretrained models that are uploaded on your temporary workspace. A prediction API uses these models for the duration of a training grace period (7 days or more), after the system is deployed, starting from after day 1. At this stage, the confidence score is low because the models do not reflect your workloads yet.

After the training grace period is over, the model is retrained with the datasets that were generated from the collected workload data. The prediction API runs inference based on the pretrained models. Then, the confidence score is updated based on the accuracy of the prediction, and system scheduler triggers the training model task daily for 2 weeks, and then on a weekly basis.





 Graph elements 



 Performance property 

Use the Performance property dropdown to navigate between different charts. The default Workload Utilization graph visualizes multiple data points that are related to your system resources.

When you are looking at the graph overall, use the legend to identify the contour profile.





 Time interval 

Use the Time interval dropdown to select different time intervals.

By default, the current date stays the same. When you select between the daily, weekly, or monthly view, the date is aggregated over time accordingly.

A line in the middle of the graph shows the cut off between historical and predicted or suggested data.

Predicted data is only displayed when the system has been collecting historical data for at least 7 days. Until then, the graph displays a data point for each day. After 7 days, a prediction for an extra two weeks' worth of information appears.





 Historical and Predicted NZP 

The purple and pink lines represent Historical NZP and Predicted NZP.

NZP (Netezza Performance Metric) is a measure of system utilization.
High level NZP indicates elevated levels of utilization.
[Three dots icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/monitor/images/actions.png) and select Copy to Dashboard![Copy to Dashboard icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/monitor/images/copy.png).
3. Select one of the dashboards that are listed, or enter a name for a new dashboard.
4. Click Copy and Open.







 Change the scope of a panel 

Complete the following steps to change the scope of a panel:



1. Navigate to the Dashboards section in the Web UI. Select a dashboard. Then, identify the panel that displays the metric for which you want to change the scope.
2. In the panel, click the Pencil icon ![Pencil icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/images/pencil.png) to Edit Dashboard Scope.
3. Define your dashboard scope.
4. Click Apply.







 Duplicate a panel 

Complete the following steps to duplicate a panel in the current dashboard:



1. Navigate to the Dashboards* section in the Web UI. Select a dashboard. Then, identify the panel that displays the metric that you want to copy.
2. Click the Actions icon ![Three dots icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/monitor/images/actions.png) and select Duplicate Panel!
* CLI







 Excluding metrics by using the drop action 

You can configure IBM Cloud® Metrics Routing to exclude (drop) metrics based on a configured rule. Dropped metrics are not sent on to a target.



 Prereqs 



1. [Install the IBM Cloud CLI](https://cloud.ibm.com/docs/cli?topic=cli-install-ibmcloud-cli).
2. [Install the IBM Cloud Metrics Routing CLI](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-metrics-router-cli-config).
3. Ensure you have the [correct IAM permissions to configure IBM Cloud Metrics Routing routes.](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-iam)
4. Log in to IBM Cloud. Run the following command: [ibmcloud login](https://cloud.ibm.com/docs/cli?topic=cli-ibmcloud_cliibmcloud_login).







 Define the inclusion filter 

Inclusion filters determine which metrics are routed to the targets.

Inclusion filters are comprised of an operand, operator, and values:

operand
: Operand is the name of the property on which the operator test is run. The following operands are supported: location, service_name, service_instance, resource_type, and resource.

operator
: Two operators are supported: in and is.

in
: The value of the operand property is compared to a list of values.

You can define up to 20 values.

is
: The value of the operand property is compared to a single value.

When using is, only 1 value can be specified.

value
: A string, or an array of strings, to be compared with the operand property to determine whether the metric is routed or not. When the isoperator is used, value must include a single string.
Monitoring metrics 

After you set up your IBM® Key Protect service instance, you can manage monitoring metrics by using the service API.



 Metrics settings 

Metrics for Key Protect service instances is an extra policy that allows you to receive the operational metrics for your Key Protect instance. When you enable this policy, Monitoring can be used to monitor any operations that are performed on the resources in your Key Protect instance.

Enabling metrics is only available through the Key Protect API. To find out more about accessing the Key Protect APIs, check out [Setting up the API](https://cloud.ibm.com/docs/key-protect?topic=key-protect-set-up-api).

Before you enable operational metrics for your Key Protect instance, keep in mind the following considerations:



* When you enable metrics for your Key Protect instance, metrics are only reported after the time that the policy is enabled. Once your metrics policy is enabled, you will see operational metrics for all API requests that occur in your instance after the the policy is activated. You will not be able to view any metrics prior to the time that the policy is enabled.
* You will need to provision a Monitoring instance for your policy in order to see the metrics. You will need to [provision a Monitoring instance](https://cloud.ibm.com/docs/monitoring?topic=monitoring-provision) that is located in the same region as the Key Protect instance that you would like to receive operational metrics for. Once you provision the Monitoring instance, you will need to [enable platform metrics](https://cloud.ibm.com/docs/key-protect?topic=key-protect-operational-metricsconfigure-monitor).





 Enabling metrics for your Key Protect instance with the Console 

After creating a Key Protect instance, provisioning a Monitoring, and enabling platform metrics, complete the following steps to enable a metrics policy:



1. [Log in to the IBM Cloud console](https://cloud.ibm.com/login/).
2. Go to Menu > Resource List to view a list of your resources.
3.
For more information, see [Managing authorizations to grant access between services](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-iam-service-auth).

For each target that you define in a different account from the one where metrics are generated, you must define a service to service authorization in the account where the target resource is available between the IBM Cloud Metrics Routing service and the IBM Cloud Monitoring instance that you configured as your destination in the target. For more information, see [Managing authorizations to grant access between services](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-iam-service-auth).





 Default targets 

You can define up to 2 default targets in the account.



* Each target collects metrics that are not explicitly managed in the account's routing rules.
* Each target must be defined in the account before you can configure it as default one in the account.
* If you define more than 1 default target, all default targets get a copy of the metrics that does not have a clearly defined routing rule to indicate where to route them in the account.



Define 1 default target per account to configure where metrics that are not explicitly managed in the account's routing rules are routed. Consider defining a second default target per account when you want to collect the data in a backup location or account.





 Number and location of targets 

Define the targets where you plan to collect metrics based on your regulatory and corporate requirements.



* You can have 1 target per region to collect metrics for that region. Use this option to reduce latency and network connectivity issues.
* You can have 1 target to collect metrics across the entire account.
* You can define targets within the account or in a different account.



For more information, see [Targets](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-target).





 Routing rules in the account 

Define the routing rules that indicate how to route metrics in your account.



* Routes are global.
* You can define up to 4 routes per account.
* UI
* CLI
* Terraform







 Managing custom roles 

The IBM Cloud® Metrics Routing service maps different sets of actions to different platform roles. However, you might want to combine some of the actions that are currently spread across multiple roles to make assigning meet your custom use case. With a custom role, you can pick and choose actions that are mapped to different roles so that next time you assign access to the service, you don't have to select three different roles, for example.

You can create new roles that are scoped to the IBM Cloud Metrics Routing service. This means that you can't combine actions for two different services in a custom role, but you can combine as many actions that you want into a new role for a single service. After you create a custom role with a name of your choosing, anyone in the account who can assign access to the IBM Cloud Metrics Routing service can use that role when assigning access.



 Permissions to manage custom roles 

Anyone can view the pre-defined roles for the IBM Cloud Metrics Routing service in the account.

However, to view, create, edit, or delete a custom role, you must be assigned specific access for the IAM Access Management service and the resource type Role Management.



Table 1. Actions for Role management service

 Action Administrator Operator Editor Viewer 

 View custom roles ![Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/dad8f28785f0dc036aaae4b777787e73db9ff0d4/icons/checkmark-icon.svg) ![Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/dad8f28785f0dc036aaae4b777787e73db9ff0d4/icons/checkmark-icon.svg) !
To save the scope, you must click Save at the panel level.







 Configuring an alert on a platform metric 



 Configuring an alert from a panel 

Complete the following steps to define an alert on a metric:



1. [Launch the monitoring UI](https://cloud.ibm.com/docs/monitoring?topic=monitoring-launch).
2. Verify that you have a notification channel that defines how you want to be notified.

You can enabled 1 or more notification channels when you configure an alert. If you need multiple notification channels, check they are available.
3. Navigate to the Dashboards section (![dashboard section](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/images/dashboards.png)) in the Web UI.
4. Select a custom dashboard in the My Dashboards section.
5. Select the panel for which you want to define the alert.

Before you create the alert, check the scope of the metric that is configured in the panel. This scope is automatically included in the alert definition.
6. Click the Actions icon ![Three dots icon](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/images/actions.png) and select Create Alert.

Zoom

![Panel options](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/platform/images/sysdig-platform-15.png)

Panel options

If you have multiple queries defined in a panel, you are prompted to select the metric for which you want to create an alert.
7. Configure the alert. Set the following fields:
In your monthly usage charges, consumption is measured hourly and your bill breaks down into the following concepts:



Table 2. Billing usage metrics

 Metric Description 

 NODE_HOURS Tracks the number of agents that are running in an agent for orchestrated environments.<br><br>This does not include the agents tracked by LITE_NODE_HOURS<br><br>For example, if you have 1 agent connected continuously, that agent will be billed 720 NODE_HOURS at the end of the month. 
 TIME_SERIES_HOURS Reflects the total number of custom metrics time series you are sending to IBM Cloud Monitoring during a 1 hour time window. This is an aggregation of all time series from agents and other metrics sources. Platform metrics, Prometheus remote write, metric streaming and custom metrics collected with the agent (Prometheus, JMX or StatsD) contribute to TIME_SERIES_HOURS.<br><br>Only custom metrics are counted for TIME_SERIES_HOURS. Default infrastructure metrics (such as host, container, program, or Kubernetes state) and CPU, memory, disk, and network are included in the agent price and do not contribute to TIME_SERIES_HOURS. 
 LITE_NODE_HOURS Tracks the number of agents that are monitoring non-containerized infrastructures such as VMs or bare metal servers, and are using the agent for non-orchestrated environments. 
 API_CALL_HOURS Represents how many calls are being made to the API per month. All instances include 1M API calls. 
 CONTAINER_HOURS Represents how many containers are monitored across all hosts that are being monitored by agents. 



To monitor how the IBM Cloud Monitoring service is used and the costs associated to its usage, see [Viewing your usage](https://cloud.ibm.com/docs/billing-usage?topic=billing-usage-viewingusageviewingusage).

All metrics that start with sysdig_* and kube_ are collected automatically by an agent and are included in the agent price.





 Service plans 

The following service plans are available when you provision an instance of the IBM Cloud Monitoring service:



 Lite plan 

You can provision a Monitoring instance with the Lite service plan to try out the Monitoring service for free for 30 days.
After a policy is defined with autoscaling rules, you can view the metric values and metrics history for the previous 2 hours.

The metric value is not the raw data from each app instance, but the metric values averaged over all the app instances.





 Scaling history 

Use the Scaling history tab to view the autoscaling events for the past 30 days. If autoscaling attempts failed, the tab also shows the error messages.







 Managing autoscaling from the CLI 

You can also use the App Autoscaler command-line interface (also known as the AutoScaler CLI) to manage policies, query metrics, and view the scaling history.



 Installing or updating the AutoScaler CLI 

Use the following command to install the AutoScaler CLI, which is a plug-in to the IBM Cloud Foundry CLI.

ibmcloud cf install-plugin -r CF-Community app-autoscaler-plugin

If the AutoScaler CLI plug-in is already installed, you can use the same command to update the plug-in to the latest version.





 Using the AutoScaler CLI 

If you are already logged in to an IBM Cloud Foundry environment on IBM Cloud® and have running apps in your space as described in the [deploying apps guide](https://cloud.ibm.com/docs/cloud-foundry-public?topic=cloud-foundry-public-deployingapps), do the following to create a scaling policy for your app, access query metrics, and view the autoscaling history.



 Creating autoscaling policies 



1. (Optional) Confirm that the App Autoscaler API endpoint is set correctly.

If the IBM Cloud Foundry API endpoint is api.<DOMAIN>, the App Autoscaler API endpoint must be autoscaler.<DOMAIN>.

To check the App Autoscaler API endpoint setting, run the following command:

ibmcloud cf asa

If the App Autoscaler API endpoint is incorrect, set it with the following command.

ibmcloud cf asa autoscaler.<DOMAIN>
2. Create a JSON policy file on your local machine. The following code is an example policy file.
After you create your IBM Cloud Monitoring instance, you must collect the following two pieces of information.



* The Monitor API token
* The endpoint of your IBM Cloud Monitoring instance



To collect this information and work with your IBM Cloud Monitoring instance by using metric query API, follow these steps:



1. Access the [Monitoring home page](https://cloud.ibm.com/observe/monitoring).
2. Click Open Dashboard next to the instance that you want to work with.
3. After the IBM Cloud Monitoring dashboard is displayed, select your Account Profile icon on the sidebar and select Settings. You now see your account settings.
4. Your Monitor API token is an alphanumeric string that is located in the Sysdig Monitor API Token field. Click the Copy button to copy the token to your clipboard.

Do not share this API token. Anyone who has this API token has full access to your metrics.
5. The endpoint of your IBM Cloud Monitoring instance is per region. For example, if your IBM Cloud Monitoring instance exists in us-south, then its endpoint is:

https://us-south.monitoring.cloud.ibm.com/api/data/batch
6. After you have both the API token and the endpoint, you can format your POST request. The following POST request is an example, with all the parameters that you can modify. The following are parameters:



* The Monitor API token.
* The endpoint of your IBM Cloud Monitoring instance.
* The value for ibm_is_vpn_gateway_name (the VPN gateway name that you want to see metrics for).



If you want to see this metric for all of your VPN gateways, do not enter a value for the scope attribute. For example, use "scope" : "".



* The metric type that you want to see the results for. This example uses ibm_is_vpn_gateway_status.
* The from and to attributes define the timeframe to focus the scan, set in epoch time, and in microseconds.