22.4 enhancements and patches
BMC applies upgrades as described in the BMC Helix Upgrade policy. BMC applies upgrades and patches during Maintenance windows..
22.4.02
Verify the status of remote components
On the Status page, review the current status of remote components such as Remote ETL Engines and Gateway Servers. Use this information to identify the components that have issues, update the components that have outdated status, and deactivate or activate Remote ETL Engines. For details, see Checking-the-status-of-remote-components.
Detect data abnormalities by analyzing metric behavior against a baseline
As an administrator, create and manage baselines to compare metric behavior in an analysis or in a custom optimizer rule. For example, you can create a baseline to produce an average weekly profile over the last 30 days and use this baseline to compare with historical data.
When using a baseline in the analysis, compare the baseline with historical data to analyze any abnormality in the metric behavior. When using a baseline in the custom optimizer rule, an alert is generated when the metric has different behavior against the baseline. For details, see Managing-baselines.
Migrate rule-based custom statistics from TrueSight Capacity Optimization
Use the Migration toolkit to migrate rule-based custom statistics from TrueSight Capacity Optimization in BMC Helix Continuous Optimization. The custom statistics appear as baselines in BMC Helix Continuous Optimization. For details, see Key-considerations-for-migration.
Use REST APIs to manage Agent lists
Use the Agent list REST APIs to automate the process of adding, removing, and updating the agent lists definitions in the gateway server. The APIs help in reducing the time required to maintain the agent list by using the user interface. For details, see Continuous-Optimization-REST-API-endpoints.
Enhancements in the K8S (Kubernetes) Prometheus ETL
The Moviri – k8s (Kubernetes) Prometheus Extractor includes the following enhancements:
- Support for the recovery mode
- Modified RESTART_COUNT metric that shows incremental updates instead of cumulative values
22.4.01
Updates to the custom optimizer rules
The following enhancements are added to the custom optimizer rules:
Specify a namespace to choose a data source for a metric
Create an alert based on a hypervisor metric, an operating system-level metric, or a derived metric by selecting a namespace. When you select Formula as the condition type, enter the namespace for each metric within that formula according to the defined syntax. For other condition types, select the required namespace.
Compare the day profile baseline data against the same day of the week or month
For the Data vs. Baseline condition type, select the data to be evaluated against the baseline over the specified condition period. An alert is generated when a metric of the entity has different behavior with respect to the baseline when compared against the same day of the week or month.
For details, see Adding-a-custom-Optimizer-rule.
Create a composite report based on a report template
In the Workspace, create a composite report for a parent domain by using a report template. The report is created by combining all the leaf domain reports that are generated at runtime. This runtime report generation saves time required to manually create a separate report for each leaf domain. For more information, see Creating-reports.
Reimport data by running an ETL in the data repair mode
Use the Run in data repair mode option to overwrite the existing data collected by an ETL. You can repair data if you have imported incorrect data and want to overwrite it. For details, see Working with ETLs.
Specify multiple golden model scenario IDs in a summary data mart
Specify multiple scenario IDs for the golden models by using the contextids property in a summary data mart to avoid creating separate data marts for each scenario ID. For details, see Using-the-advanced-editor-of-the-summary-data-mart-wizard.
Enhanced IND_USAGE_SCORE indicator
The IND_USAGE_SCORE indicator is produced by considering the average usage of the CPU, memory, and storage resources, when they are available. If any of the resources is missing for the entity, the missing resource is excluded, and the indicator is produced by rescaling the weight of the available resources. For details, see Indicators.
ETL module enhancements
ETL module | Enhancement |
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22.4.00
The following video (2:54) provides a high-level summary of the new features and enhancements in version 22.4 of BMC Helix Continuous Optimization.
Get insights into the overall health and status of business services in BMC Helix Dashboards
Create a custom dashboard in BMC Helix Dashboards for business services by using the Service Risk and Mitigation query type and visualization plug-in. Use this plug-in to visualize the business service performance based on the correlation between business drivers and resources of a pool. Service owners can use this information to get insights into the overall health and status of business services in BMC Helix Dashboards.
For details, see Using-BMC-Helix-Dashboards.
Manage the capacity of your mainframe environment
ETL to import data from the mainframe environment
Use the BMC Mainframe CDB Extractor to collect configuration and performance data of mainframe resources. For details, see BMC-Mainframe-CDB-Extractor.
Out-of-the-box view for mainframe
Analyze and manage the mainframe resources, such as CPCs, LPARs, and Storage Controllers by using the Mainframe View. For details, see Mainframe-view.
Nonnegative percentile-shift linear trend algorithm in Time Forecasting Model
The Nonnegative percentile-shift linear trend algorithm is a variant of the Robust linear regression algorithm. In this algorithm, the predicted linear trend is constrained to have a nonnegative slope. Additionally, the prediction starts from a user-defined percentile level of the historical data.
Use this algorithm to prevent modeling the forecasted data that has a negative slope and to perform a conservative prediction.
For details, see Time-forecasting-model-algorithms-for-detecting-monotonic-trends-in-data.
Visualize server capacity data by using the Maps page
Use the Maps page in the Servers Overview view to visualize the server capacity data in a hierarchical structure as a set of nested rectangles. For details, see Maps-page-in-the-Servers-Overview-view.
Export and import ETL configuration by using APIs
Use the ETL configuration APIs to export the existing ETL configuration from an environment and to import it into another environment. You can also use these APIs to modify, delete, and stop the ETL configuration. For more details, see Continuous-Optimization-REST-API-endpoints and ETL-configuration-API-endpoints.
Add and edit string configuration metrics
Define string configuration metrics for an entity in the Workspace. Use these metrics to specify the configuration details that do not frequently change, such as region name, type of storage, and location. You can add and edit configuration metrics for systems, business drivers, and domains. For details, see Adding-and-editing-string-configuration-metrics.
Filter data based on domains and tags for Optimize data marts in BMC Helix Dashboards
In BMC Helix Dashboards, use the Domain Filter and Tag Filter to search for and filter data based on a specific domain or tag. Configure these filters in the Optimize data marts query type to filter data based on domains, such as AWS and KVM, or based on tags, such as high priority and medium priority.
For details, see Using-BMC-Helix-Dashboards.
Display of the Standard Time label to indicate time zones not affected by DST
While selecting the time zone in an analysis, you can check whether the time zone follows the Daylight Saving Time (DST) or not by using the Standard Time label. For details, see Editing-general-properties-for-an-analysis.
Support for Ubuntu 22.04 LTS
Ubuntu 22.04 LTS is supported for the Continuous Optimization Agents. For a complete list of supported operating systems, see System-requirements-for-the-Continuous-Optimization-Agent.
ETL module enhancements
ETL module | Enhancement |
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DB_AVG_USER_CPU_USED metric to calculate the average instance CPU in percentage for the database instance. | |
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