Managing the cost of observability
BMC Observability and AIOps offers multiple methods to understand platform usage across teams, empowering IT to manage service health while maintaining control over observability costs. To effectively optimize observability expenses, organizations require clear insights into cost drivers across their resources.
Evaluate and forecast platform cost and usage across teams and services
As an administrator, leverage the Platform Observability dashboard to gain actionable insights into telemetry usage, and collaborate with business owners and teams to optimize observability costs. This dashboard offers detailed visibility into telemetry consumption by service, highlighting the top ingesting services and identifying unused telemetry that can be reconfigured to enhance efficiency and maximize value.
Additionally, the dashboard provides insights into telemetry data that is not linked to a business service, helping to identify and address potential blind spots. You can also configure thresholds on this data to trigger proactive notifications for administrators, business owners, and teams, ensuring timely action and improved cost control. For details, see Observability Platform Efficiency.
Control collection, granularity, or retention of ingested data
Optimize observability costs by managing the collection, granularity, and retention of ingested data. To ensure accurate and data-driven decisions, it is essential to collect events, metrics, logs, and topology data from various third-party products into a central data lake.
All BMC Helix Collectors offer configurable settings, such as filters, intervals, and polling, tailored to the data source, ensuring flexible data collection and filtering. For example, you can use the BMC Helix Intelligent Integrations collector for AWS CloudWatch to collect events and metrics from AWS CloudWatch. Various parameters such as Collection Schedule, Data Collection Window, and Max Batching Size allow you to control data collection and distribution. In addition, you can use various filters to collect data for a particular region and namespace. For more information, see Integrating by using BMC Helix Intelligent Integrations.
BMC Helix Observability and AIOps support direct ingestion of OpenTelemetry (OTel) data with built-in filtering and sampling controls to manage data granularity. OTel traces and logs are retained for 8 days, while OTel metrics are stored for 90 days. For more information about data ingestion by using OTel, see Enabling BMC Helix applications to collect service traces from OpenTelemetry.
For log management, use BMC Helix Log Analytics to ingest and process log data. Learn more about it at BMC Helix Log Analytics. Additionally, BMC Helix also leverages Agentic AI for just-in-time log analysis at the source, reducing unnecessary data ingestion and storage costs. Using Agentic AI, BMC HelixGPT Log Analyzer performs just-in-time analysis of related log data, providing in-context summaries for operators. This game-changing approach allows log source data to remain at the source, eliminating the need for ingestion and local storage. For more information, see Investigating ML-based situations.
What-if scenario planning
A well-balanced resource management system is critical for any IT organization to support business in a cost-effective manner. It is important to estimate whether your existing infrastructure is able to accommodate additional projects to support an ever-changing business model. You can use a What-if simulation capability in BMC Helix Continuous Optimization to evaluate historical data, predict future behavior, simulate scenarios, and therefore, prevent any potential issues.
For details, see Creating a What if simulation for business services and viewing the simulation results.
Conclusion
By integrating AI-driven analytics, real-time insights, and proactive resource management, BMC Observability and AIOps help organizations streamline operations, improve cost efficiency, and maintain optimal performance.