Managing the capacity of your GCP infrastructure
As a Capacity Planner or GCP Technology Specialist, you can use BMC Helix Continuous Optimization to configure, administer, and manage the capacity of your GCP infrastructure.
As the flow diagram illustrates, the data source (Google Cloud Platform - GCP API ETL) collects data from the GCP console. The collected data is transferred to Continuous Optimization where it is processed, and then displayed on the user interface. You can use the product features to review, analyze, and manage the capacity of your GCP infrastructure.
The following sections describe how you can achieve these goals:
Managing the capacity of GCP infrastructure
You can analyze and manage the capacity of your GCP infrastructure elements by using the GCP VM Instances view. For the GCP data to be available in the view, the Administrator must first set up the data sources to collect data.
Task 1. Collect data and install the views
As an Administrator, you can use the Google-Cloud-Platform-GCP-API-Extractor to collect data from the GCP VM instances.
- Configure and run this ETL to collect the required configuration and performance metrics from the VM instances.
- In addition to the required metrics collected by using the GCP API Extractor, you can create a Stackdriver account and install the Monitoring agent on each of your virtual machines to collect additional performance metrics from them. These metrics are useful for investigating the capacity-related issues that might occur in your Google Cloud environment. When you run the GCP API ETL, these metrics are imported into the Continuous Optimization database. For more information, see Collecting-additional-metrics-using-the-Stackdriver-monitoring.
After data collection starts, data is loaded daily and Indicators are available in the Workspace tab.
As an Administrator, you must install the GCP views and Business Services view and grant the necessary permissions to Capacity Planners and GCP Technology Specialists to access these views. While creating the service pools, ensure to select GCP domains to view GCP only data.
Task 2. Analyze the collected data
To get a high-level view of the GCP infrastructure usage and health at the business services and service pools level, use the Analyzing-business-services.
For detailed analysis, use the GCP-views.
The following common use cases are described here:
Understand the usage and health of your GCP VM instances
Review and analyze the GCP-Data-Explorer-view to determine the usage and health of your VM instances.
From the VM Instance filter, select the instance that you want to view data for detailed analysis.
Determine and analyze the available resources and their utilization per VM instance
Review and analyze the relevant metrics on the VM-Instances-page-in-the-GCP-VM-Instances-view to determine the available resources and their utilization per instance. For example, utilization metrics for CPU, Memory, and network.
Identify idle or unused VMs
Use the Recommendations-page-in-the-GCP-VM-Instances-view to identify VMs that are idle or the VMs that display a regular usage pattern with a significant idle time. The page also provides actionable recommendations to help you manage the VM and resolve the issue. For example, you can view the recommendations that suggest actions to power-off the VMs during their idle time and power-on them back during their functional time to achieve cost saving.
Performing advanced analysis
The earlier sections explained how you can use the out-of-the-box capacity views to manage your environment. These capacity views help you analyze your GCP infrastructure using a predefined set of metrics.
To perform advanced analysis on the imported GCP data, such as identifying specific performance issues, trends, and bottlenecks, you can use Analysis. For more information, see Analyzing-domain-data.
Managing future demand
By using the capacity views and analysis charts, you can analyze the data of your existing capacity. Use Models to predict service performance and obtain forecasts of historical series of metrics, including deep details on the modeling techniques used in forecasts and how to interpret the results of model runs. For more information, see Modeling-capacity-usage.