vania-janet/multiturn-rag-retrieval-data huggingface dataset:
Metric Name ibm_databases_for_mongodb_oplog_window_hours 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance 







 Page faults 

The number of times per second that MongoDB had to request data from disk. Scale RAM to reduce the number of disk requests.



Table 17. Page faults metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_mongodb_page_faults 
 Metric Type gauge 
 Value Type count 
 Segment By Service instance 







 Process resident memory in bytes 

Amount of actual physical memory used by the MongoDB process. Resident memory (the number of megabytes resident): In a standard deployment resident is the amount of memory used by the WiredTiger cache plus the memory dedicated to other in-memory structures used by the mongod process. By default, mongod with WiredTiger reserves 50% of the total physical memory on the server for the cache and at a steady state, WiredTiger tries to limit cache usage to 80% of that total. For example, if a server has 16GB of memory, WiredTiger will assume it can use 8GB for cache and at steady state should use about 6.5GB. To learn more about the WiredTiger Storage Engine, reference the [MongoDB documentation](https://cloud.ibm.com/docs/databases-for-mongodb?topic=databases-for-mongodb-performancewiredtiger-cache-and-memory).



Table 18: Process resident memory in bytes metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_mongodb_process_resident_memory_bytes 
 Metric Type gauge 
 Value Type byte 
 Segment By Service instance 







 Process virtual memory in bytes 

Amount of virtual memory used by the mongod process. Generally, virtual memory should be slightly larger than mapped memory. If virtual memory is many gigabytes larger, it indicates that excessive memory is being used by other aspects than the memory mapping of files and is sub-optimal. The most common case of usage of a high amount of memory for non-mapped is excessive connections to the database. Each connection has a thread stack and the memory for those stacks can add up considerably.
See [Single Stat Panels Displays Latest Value](https://docs.sysdig.com/en/docs/release-notes/enhanced-metric-store/single-stat-panels-displays-latest-value)
* In the Overview section, you can view the latest data as opposed to an aggregated value for widgets over the time window that is selected.
* You can display metrics that are scraped at different intervals on the same graph. See [Mixed-Metric Granularity](https://docs.sysdig.com/en/docs/release-notes/enhanced-metric-store/mixed-metric-granularity) and [Improved Granularity for PromQL panels](https://docs.sysdig.com/en/docs/release-notes/enhanced-metric-store/improved-granularity-for-promql-panels).
* Realignment of time selections has been removed. See [Removed Re-Alignment](https://docs.sysdig.com/en/docs/release-notes/enhanced-metric-store/removed-re-alignment).



The following are known limitations in this release:



* Querying labels as metrics is limited to Infrastructure labels in Table panels.
* Panels that are not timecharts, such as Number panels, might not display aggregated data for the full requested time range.



Deprecated features:



* Topology Maps are deprecated due to their incompatibility with the new data store.
* Agent derived percentiles are deprecated.



For more information, see [Removed features](https://docs.sysdig.com/en/docs/release-notes/enhanced-metric-store/removed-featurees).

Impact to your environment:



* Your existing dashboards, alerts and notifications will be automatically migrated to the new metric naming convention.
* Notifications that are sent by alerts (webhooks, PagerDuty, and so on) will use the new metric and label convention. If you are doing further processing to parse metrics or labels, you will need to update your scripts accordingly.
Table 1: IBM Load Balancer for VPC active connections metrics metadata

 Metadata Description 

 Metric name ibm_is_load_balancer_active_connections 
 Metric type gauge 
 Value type none 
 Segment by IBM Load Balancer for VPC appliance metrics and IBM Load Balancer for VPC listener metrics 







 Connection rate 

Connection rate is the number of new, incoming active connections per second to your load balancer.



Table 2: IBM Load Balancer for VPC connection rate metric metadata

 Metadata Description 

 Metric name ibm_is_load_balancer_connection_rate 
 Metric type gauge 
 Value type none 
 Segment by IBM Load Balancer for VPC appliance metrics and IBM Load Balancer for VPC listener metrics 









 Metric segmentation 

You can split the data that IBM Cloud Monitoring presents into various visualizations in the dashboard, allowing views of different metrics based on your preferences. For example, if you have multiple load balancers or accounts with different load balancers in each account, you might want to focus on a particular listener port.

For example, you can segment the active connections by IBM Load Balancer for VPC listener port to show how many active users are connected to the load balancer through each listener type. To illustrate this, let's assume that your network load balancer has listener protocol TCP on port 8080. The dashboard would contain different lines showing 10 users who are connected through HTTP on Port 80 in one color, and 6 users connected through TCP on port 8080 in another color.



 Global attributes 

The following attributes are available for segmenting the three metrics.



Table 3: Global attributes

 Attribute Attribute Name Attribute Description 

 Resource ibm_resource A load balancer's unique ID 
 Scope ibm_scope The account associated with a given load balancer 
 Service name ibm_service_name ibm-is-load-balancer 







 Additional attributes 

The following attributes are available to segment one or more of the global attributes. See the individual metrics for any segmentation options.



Table 4: Additional attributes

 Attribute Attribute Name Attribute Description
* CLI
* API







 About routes 

You can manage routes in your account by using the IBM Cloud® Metrics Routing CLI, IBM Cloud Metrics Routing REST API, and Terraform scripts. A route defines the rules that indicate what metrics are routed in a region and where to route them.



 Understanding how routes work in your account 

Note the following information about routes:



* Routes are global under an account and are evaluated in all regions where IBM Cloud® Metrics Routing is deployed.
* You can define a route from any of the supported locations where IBM Cloud Metrics Routing is available. For more information, see [Locations](https://cloud.ibm.com/docs/metrics-router?topic=metrics-router-regions).
* Routes may be accessed from any regional IBM Cloud Metrics Routing API endpoint.
* You can define up to 4 routes for an account.
* By default, the account has 0 routes configured.
* You can configure up to 4 rules for each route.
* You can configure up to 8 locations for each rule.
* You can configure up to 3 targets ({"targets":[{"id":ID1},{"id":ID2},{"id":ID3}]) for each rule.
* Routes are processed independently. If you have multiple routes with rules that match the same metric data, that data will be sent to multiple targets.
* Rules in 1 route definition are processed in order. The first matching rule (for example, location) that matches metrics data is used to process that data. When metrics are processed, they will not be processed by a subsequent rule within that route's definition. If you want to specify a default rule for all metrics that are not processed by other rules, you would specify the rule ("locations" : [""]) as the final rule in your rules definition for the route.
* If metrics data doesn't match any rule and no default target is configured, the metrics are dropped and not routed to any target.
* Any update to 1 or more rules in a route definition discards the existing rule set and replaces it with the specified configuration.
* [VPN server data bytes input](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_data_received_bytes)
* [VPN server data bytes output](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_data_sent_bytes)
* [VPN server CRL days until expiration](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_crl_days_expiry)
* [VPN server authentication failure count](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_authentication_failure_count)
* [VPN server active client count](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_active_client_count)
* [VPN server health status](https://cloud.ibm.com/docs/vpc?topic=vpc-vpn-client-to-site-monitoringibm_is_vpn_server_health_status)



These metrics help track the traffic and status for your VPN servers and can provide insight about peak traffic per minute and overall usage status.

Each metric is composed of the following metadata types:



* Metric name - Name of the collected metric.
* Metric type - Determines whether the metric value is a counter metric or a gauge metric. Each of these metrics is of the gauge type, which represents a single numerical value that can arbitrarily fluctuate over time.
* Value type - A unit of measurement for a specific metric. Examples include bytes or counts. A value type of none means that the metric value represents individual occurrences of that metric type.
Metadata Description 

 Metric Name ibm_eventstreams_instance_rest_producer_requests_per_sec 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name 



This is for information to help you monitor usage of the REST Producer API, including use of schema encoders.





 Mirroring throughput 

The bytes per second of mirroring throughput from the source Event Streams instance.



Table 33. Mirroring throughput

 Metadata Description 

 Metric Name ibm_eventstreams_instance_mirroring_throughput_bytes_per_second 
 Metric Type gauge 
 Value Type bytes_per_second 
 Segment By Service instance, IBM Event Streams Kafka topic, Service instance name 



This is useful to see whether mirroring is active and for capacity planning.





 Mirroring_latency 

The per-topic mirroring latency in seconds from the source Event Streams instance.



Table 34. Mirroring latency

 Metadata Description 

 Metric Name ibm_eventstreams_instance_mirroring_latency_seconds 
 Metric Type gauge 
 Value Type seconds 
 Segment By Service instance, IBM Event Streams Kafka topic, Service instance name 



This is useful to determine how far behind a topic on the target cluster is.





 Consumer group lag 

Lag for each consumer group for each topic-partition in an Event Streams instance. This metric indicates that the number of messages that are yet to be processed for each partition in a consumer group.



Table 35. Consumer group lag metric metadata

 Metadata Description 

 Metric Name ibm_eventstreams_instance_consumer_groups_lag 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance name, IBM Event Streams consumer groups, IBM Event Streams Kafka topic, IBM Event Streams Kafka partitions 



An increasing lag might highlight that the consumers in the group are not keeping pace with the rate that messages are being produced. This might require you to scale the number of consumers that process messages for the group.

It is normal for this metric to fluctuate when viewed over short time periods because of sampling and batch processing effects.





 Message rate per partition
: Activity Tracker Events for Audit log [feature description](https://cloud.ibm.com/docs/CDN?topic=CDN-at_events) (available through UI).





 October 2019 

Dynamic content acceleration and metrics report added
: Dynamic Content Acceleration [feature description](https://cloud.ibm.com/docs/CDN?topic=CDN-about-content-delivery-networks-cdn-dynamic-content-acceleration-description) (available through UI and API).

Metrics reports for overall CDN mappings added
: [Metrics reports](https://cloud.ibm.com/docs/CDN?topic=CDN-metrics) for overall CDN mappings (available through UI and API).





 August 2019 

New IBM CNAME suffix move
: Move to the new IBM CNAME suffix .cdn.appdomain.cloud. from .cdnedge.bluemix.net. to unify user experience (Existing CDNs that are mapped to .cdnedge.bluemix.net. are not impacted).





 March 2019 

Hotlink protection added for UI
: Hotlink Protection [feature description](https://cloud.ibm.com/docs/CDN?topic=CDN-about-content-delivery-networks-cdn-hotlink-protection) (available through UI).





 November 2018 

Hotlink protection added for API
: Hotlink Protection [feature description](https://cloud.ibm.com/docs/CDN?topic=CDN-about-content-delivery-networks-cdn-hotlink-protection) (available through the API).





 October 2018 

Max number of supported origins paths increased
: Increased the [maximum number of supported origins paths](https://cloud.ibm.com/docs/CDN?topic=CDN-known-limitationsknown-limitations) from 25 to 75.

Origin paths prefix change
: [Origin paths](https://cloud.ibm.com/docs/CDN?topic=CDN-adding-origin-path-details) no longer need to start with Mapping Path Prefix.

Minimum TTL value updated
Collecting metrics by infrastructure 

You can collect metrics from a number of platforms, orchestrators, and a wide range of applications such as Prometheus, JMX, StatsD, Kubernetes, and other application stacks, that are available in the IBM Cloud®, outside the IBM Cloud, or on-prem. You can also add more metrics by creating custom metrics and adding integrations.



 Metrics collected 



Table 1. Metrics by infrastructure

 Type Infrastructure Metrics info 

 Orchestrated environment Kubernetes clusters [Metrics for orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/) 
 Orchestrated environment OpenShift clusters [Metrics for orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/) 
 Non-Orchestrated environment Virtual Machines (VM) [Metrics for non-orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/) 
 Non-Orchestrated environment Bare metal servers [Metrics for non-orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/) 
 Non-Orchestrated environment Linux based Virtual Machines (VM) [Metrics for non-orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/) 
 Non-Orchestrated environment Linux based Virtual Machines (VM) on VPC [Metrics for non-orchestrated environments](https://docs.sysdig.com/en/docs/sysdig-monitor/using-monitor/metrics/metrics-library/prometheus-format/)
[Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/icons/checkmark-icon.svg) ![Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/icons/checkmark-icon.svg) 







 Predefined alerts 

The following table outlines the pre-defined alerts that are available in Monitoring:



Table 4. Pre-defined alerts

 Alert Name Description 

 Continuous Delivery high pipeline queue time Use this alert to monitor the queue time for pipeline requests to let you know if a private worker pool is taking too long to process requests. 







 Continuous Delivery metrics dictionary 



 Pipeline queue time 

The elapsed time in seconds between the Continuous Delivery service receiving and queuing a request to run a pipeline, and a private worker pool dequeuing and commencing execution of the pipeline.



Table 5: Pipeline queue time metric metadata

 Metadata Description 

 Metric Name ibm_toolchain_pipeline_queue_time_seconds 
 Metric Type gauge 
 Value Type second 
 Segment By Service instance, Service instance name, Private worker pool ID 









 Attributes for segmentation 



 Global attributes 

The following attributes are available for segmenting all of the metrics listed in this topic.



Table 6. Global segmentation attributes

 Attribute Attribute Name Attribute Description Valid Values 

 Cloud Type ibm_ctype Type of Cloud Valid values are public or local. 
 Location ibm_location Location of the monitored resource. You can specify a region, a data center, or global. 
 Resource group ibm_resource_group_name Resource group that is associated with the service instance. Choose a resource group from the ones that are available in your account. 
 Scope ibm_scope The extent of the data samples that are considered. You can choose the scope to be the account, an organization, or a space GUID that is associated with this metric. 
 Service name ibm_service_name Name of the service that generates this metric. toolchain 







 Additional attributes 

The following attributes are available for segmenting one or more global attributes:

Check each individual metric for the supported segmentation options.



Table 7. Additional segmentation attributes
[Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/dad8f28785f0dc036aaae4b777787e73db9ff0d4/metrics-router/images/checkmark-icon.svg) 
 North America Dallas (us-south) ![Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/dad8f28785f0dc036aaae4b777787e73db9ff0d4/metrics-router/images/checkmark-icon.svg) 
 North America Washington DC (us-east) ![Checkmark icon](https://cloud.ibm.com/docs-content/v1/content/dad8f28785f0dc036aaae4b777787e73db9ff0d4/metrics-router/images/checkmark-icon.svg) 
 North America Toronto (ca-tor) 
 South America Sao Paulo (br-sao) 







 Features 



* Consolidate time series data to the region of your primary operations
* Route time series data to one or multiple locations
* Improve your data residency compliance stature, keeping data at-rest within certain regions
Metadata Description 

 Metric Name ibm_databases_for_mongodb_cpu_used_percent 
 Metric Type gauge 
 Value Type percent 
 Segment By Service instance 







 Used disk space for an instance 

How much disk your deployment is using.



Table 24. Used disk space for an instance metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_mongodb_disk_used_bytes 
 Metric Type gauge 
 Value Type byte 
 Segment By Service instance 







 Used memory for an instance 

How much memory your deployment is using.



Table 25. Used memory for an instance metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_mongodb_memory_used_bytes 
 Metric Type gauge 
 Value Type byte 
 Segment By Service instance 









 Attributes for Segmentation 



 Global Attributes 

The following attributes are available for segmenting all of the metrics listed above



Table 26. Global Attributes Metadata

 Attribute Attribute Name Attribute Description 

 Cloud Type ibm_ctype The cloud type is a value of public, dedicated, or local. 
 Location ibm_location The location of the monitored resource - this may be a region, data center, or global. 
 Resource ibm_resource The resource being measured by the service - typically a identifying name or GUID. 
 Resource Type ibm_resource_type The type of the resource being measured by the service. 
 Scope ibm_scope The scope is the account, organization, or space GUID associated with this metric. 







 Additional Attributes 

The following attributes are available for segmenting one or more attributes as described in the reference above. Please see the individual metrics for segmentation options.



Table 27. Additional Attributes Metadata

 Attribute Attribute Name Attribute Description 

 Service instance ibm_service_instance The service instance segment identifies the instance the metric is associated with. 
 Service instance name ibm_service_instance_name The service instance name provides the user-provided name of the service instance, which isn't necessarily a unique value depending on the name provided by the user. 
 Resource group ibm_resource_group_name The resource group where the service instance was created.
* [Locations of platform metrics](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_monitor_locations)
* [Where to look for metrics](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_monitor_ui)



* [Monitoring metrics](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_monitor_ui_at)



* [Viewing metrics](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_view_metrics)



* [Starting the Monitoring UI from the Observability page](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_view_metrics_opt2)



* [Predefined dashboards](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitorregistry_dashboards_dictionary)
* [Platform metrics](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitormetrics)



* [Pull Traffic](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitoribm_containerregistry_pull_traffic)
* [Pull Traffic Quota](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitoribm_containerregistry_pull_traffic_quota)
* [Storage Quota](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitoribm_containerregistry_storage_quota)
* [Storage](https://cloud.ibm.com/docs/Registry?topic=Registry-registry_monitoribm_containerregistry_storage)





[Auditing events](https://cloud.ibm.com/docs/Registry?topic=Registry-at_eventsat_events)
Cache hit ratio 

Cache hit ratio



Table 6: Cache hit ratio metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_enterprisedb_cache_hit_ratio 
 Metric Type gauge 
 Value Type percent 
 Segment By Service instance 







 Deadlocks count 

Deadlocks count



Table 7: Deadlocks count metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_enterprisedb_deadlocks_count 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance 







 Deadlocks rate 

Deadlocks rate



Table 8: Deadlocks rate metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_enterprisedb_deadlocks_rate 
 Metric Type gauge 
 Value Type rate 
 Segment By Service instance 







 Disk read latency mean 

Disk read latency mean



Table 9: Disk read latency mean metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_enterprisedb_disk_read_latency_mean 
 Metric Type gauge 
 Value Type count 
 Segment By Service instance 







 Disk write latency mean 

Disk write latency mean



Table 10: Disk write latency mean metric metadata

 Metadata Description 

 Metric Name ibm_databases_for_enterprisedb_disk_write_latency_mean 
 Metric Type gauge 
 Value Type count 
 Segment By Service instance 







 IO utilization in percent 5 minute average 

How much disk I/O was used over 5 minutes as a percentage of total disk I/O available.



Table 11. IO utilization in percent 5 minute average metric metadata

 Metadata Description 

 Metric Name ibm_databases-for-enterprisedb_disk_io_utilization_percent_average_5m 
 Metric Type gauge 
 Value Type percent 
 Segment By Service instance 







 IO utilization in percent 15 minute average 

How much disk I/O has been used over 15 minutes as a percentage of total disk I/O available.



Table 12. IO utilization in percent 15 minute average metric metadata

 Metadata Description 

 Metric Name ibm_databases-for-enterprisedb_disk_io_utilization_percent_average_15m 
 Metric Type gauge 
 Value Type percent 
 Segment By Service instance 







 IO utilization in percent 30 minute average