Today’s complex and dynamic architecture makes it increasingly difficult to trace an error back to the root cause of the problem. This results in slow incident response time, which can lead to service degradation and expensive downtime. We’re excited to announce new capabilities in the BMC Helix observability and AIOps solution portfolio that help teams improve service reliability and mean time to repair (MTTR) while streamlining incident management.

The BMC Helix ITOM 24.2 release introduces OpenTelemetry support for distributed tracing, BMC HelixGPT-powered log insights in the context of a situation, new service blueprints, and enhanced integration for correlation of incidents to situations. Other enhancements include expanded BMC Helix Discovery Technology Knowledge Updates (TKUs) and improved usability through advanced event filtering.

These key enhancements make cloud-native application data collection easier for IT operations and site reliability engineering (SRE) teams and reduce the time teams must spend manually troubleshooting problems or poring over complicated information.

Troubleshoot more efficiently with OpenTelemetry tracing

OpenTelemetry (OTel) is the open-source standard for instrumenting, generating, collecting, and exporting telemetry data to gain observability over microservices. Through the OTel collector, IT teams that include DevOps, IT operations (ITOps), SRE, and platform engineering, can get traces into BMC Helix ITOM, our observability and AIOps solution, without needing to use a third-party monitoring tool.

Our solution derives the rate, errors, and duration (RED) metrics from all the spans ingested to provide a highly accurate picture of an application’s behavior and give users a standardized starting point for troubleshooting microservices or any request-driven applications. By viewing a trace, you can track the complete flow of a request from one service to another and identify which part of the application is causing issues such as errors or latency concerns.

Figure 1. Visualizing a trace.

BMC Helix ITOM enriches OpenTelemetry trace data with a powerful topology mapping and visualization that gives IT teams a better understanding of the overall service and its dependencies and isolates root causes by correlating traces with topology, metrics, and events in the context of the problem. If an application issue occurs, you can identify the impacted application quickly. From that impacted node, you can launch the dashboard that shows the problem’s contextual RED metrics. Clicking on any error status will direct you to the relevant traces to pinpoint the issue.

In addition, the topology derived from those traces get reconciled and added to the solution’s network infrastructure topology mapping and visualization, giving IT teams end-to-end service visibility. This helps identify issues that stem from errors within the microservices or changes to the infrastructure or network.

Resolve incidents faster with AI-powered log insights

BMC Helix ITOM continues to invest in artificial intelligence and machine learning (AI/ML) capabilities to improve MTTR and team productivity. In January, we introduced the Best Action Recommendation (BAR) feature to help IT practitioners resolve issues and eliminate days of troubleshooting. Trained on past incidents, situations, and remediation actions, BAR uses generative AI to recommend potential solutions to resolve problems. IT administrators, network operations center (NOC) operators and SREs can use the “Ask BMC HelixGPT” tool to ask questions and get more details to questions such as, “What’s the impact of the issue?” and “Has this situation happened in the past?”

Figure 2. Log insights leveraging BMC HelixGPT.

Now, with log insights for situations, teams gain additional insights with important trends and patterns found in the context of the problem. Using generative AI for log data further enhances the functionality of BAR by reducing the noise and the time it takes to identify unusual behaviors in log data. Log insights provides a summary of the issue and a breakdown of the different occurrences so teams can make informed decisions with a clear explanation of the problem.

Automate incident management through a single interface

When you’re under pressure to respond to production incidents, nothing kills productivity more than context switching. The BMC Helix observability and AIOps solution portfolio eliminates context switching by enabling cross-launching between the situation view (where a generative AI-based summary and the root cause of the issue is shown) to your IT service management (ITSM) tool. By creating a single incident for many correlated events along with the impacted service and configuration item (CI) details, the solution significantly reduces the number of tickets created, as well as their corresponding costs and incident noise. ITSM and ITOps teams can now focus and collaborate more efficiently on solving critical issues.

Get better control of events

The new advanced event filter capability helps users view only the events they want to focus on to prioritize critical issues and diagnose them early by:

• Creating new filters and viewing events that match the specified priorities.
• Saving hundreds of filters and switching between them within the intuitive user interface (UI).
• Grouping devices and services based on technology, role, and geography.

Figure 3. Advanced event filter in BMC Helix Operations Management.

Other enhancements

New service blueprints for service modeling 

Speed the time to value (TTV) for customers creating service models with new out-of-the-box service blueprints for application performance monitoring, networks, cloud infrastructure, and mainframe that reduce contextual noise and enable root cause analysis.

New BMC Helix Discovery TKUs

Get expanded BMC Helix Discovery TKU content with new cloud, Kubernetes, storage, and network coverage that improves visibility into your IT environment. For the full list, see our documentation.

Want to see it working together? We’ll be happy to show you the latest features; request a demo today.

In today’s continuously evolving IT environment, staying ahead sometimes means embracing both the tried and true and the cutting cutting-edge For organizations deeply invested in TrueSight Operations Management, the prospect of integrating advanced artificial intelligence (AI) capabilities might seem like a leap into the unknown. However, the future of operational excellence lies in blending existing strengths with the latest innovations. This is where BMC Helix AIOps and observability come into play, offering a bridge to the future. BMC Helix AIOPs is called as BMC Helix Service Monitoring Tile in the Helix Portal Landing Page.

I have had several inquiries regarding the feasibility of using existing TrueSight Operations Management and connecting it to the award-winning functionality of BMC Helix AIOps and observability. Customers are asking if they can adopt the latest BMC Helix AIOps and observability tools without replacing TrueSight Operations Management with BMC Helix Operations Management.

This blog previews the best practice steps  and use cases for customers to connect TrueSight Operations Management to BMC Helix AIOps using BMC Helix Intelligent Integrations, and guidance to helpcustomers using TrueSight Operations Management who want to adopt both BMC Helix Operations Management and BMC Helix AIOps and observability to improve operational efficiency, reduce costs, and yield the benefits of a modern, highly available, cloud-native platform.

Working with available use cases

Use case 1— TrueSight Operations Management and BMC Helix Operations Management event data workflow using BMC Helix Intelligent Integrations

• Download, install, and configure the TrueSight Operations Management connector.
• Once the connection and integration are successful, send events to it.
• Through the connector, the events are propagated to BMC Helix Operations Management.

• As a next step, when we do any event operation like a closing event in TrueSight Operations Management, we will see the corresponding event closing in the BMC Helix Operations Management
• Please note there is no back propagation, as of now, of event status from BMC Helix Operations Management to TrueSight Operations Management.

Figure 1. Use case 1 flow (TSPS is TrueSight Presentation Server, a component of TrueSight Operations Management).

Figure 2. Use case 1 flow with pros and cons.

Use case 2—TrueSight Operations Management and BMC Helix Operations Management event data topology using BMC Helix Intelligent Integrations.

• Download, install, and configure the TrueSight Operation Management connector.
• Configuration Items (CIs) created manually in TrueSight Operation Management will get ingested into BMC Helix Operations Management.
• In BMC Helix Operations Management, we will observe the CIs getting ingested. In BMC Helix Discovery, we will see these CIs as generic elements.
• In BMC Helix Service Monitoring, we will not see these CIs as these are created manually in TrueSight Operations Management.
• Please note there is no back propagation, as of now, of event status from BMC Helix Operations Management to TrueSight Operations Management.

Figure 3: Use case 2 flow.

Use case 3—TrueSight Operations Management with a configuration management database (CMDB) and service models integrated into BMC Helix Operations Management topology using BMC Helix Intelligent Integrations

• Download, install, and configure the TrueSight Operation Management connector.
• This is like use case 2, the only difference here is the service models are created in the CMDB and published from the CMDB to TrueSight Operations Management.
• BMC Helix Discovery will show the same topology.
• In BMC Helix Service Monitoring (BMC Helix AIOps), we will see the business service models.

Figure 4. Use case 3 flow.

Use case 4—TrueSight Operations Management monitoring vCenter

• Add monitoring policy for vCenter KM in TrueSight Operations Management.
• vCenter hierarchy builds up in TrueSight Operations Management.
• We can see the vCenter CI in BMC Helix Discovery.
• We observe that the hierarchy does not have multilevel topology as in TrueSight Operations Management.

There is no use case diagram for this.

This completes the best practice steps you can use when trying to integrate TrueSight Operations Management with BMC Helix Service Monitoring (AIOps) using BMC Helix Intelligent Integrations.

For each of the four use cases, we have recorded a five-minute video demonstration, which can be obtained by request by emailing sayan_banerjee@bmc.com

Conclusion

These use cases help IT teams that want to stay with TrueSight Operations Management while adopting BMC Helix Operations Management with AIOps and using BMC Helix Service Monitoring.

Organizations often struggle to maintain seamless functionality and uninterrupted service delivery due to the overwhelming amount of data and events they face. This can lead to operational inefficiencies, prolonged downtime, and fragmented insights. Without a clear understanding of their IT infrastructure, businesses find themselves in a cycle of reactive firefighting. This lack of visibility not only hampers agility and innovation, but also leaves organizations vulnerable to costly disruptions and reputational damage.

In this type of landscape, the need for a comprehensive solution that ingests data while also synthesizing it into actionable intelligence becomes increasingly apparent. I would like to tell you about BMC Helix IT Operations Management (ITOM), a suite of software that goes beyond telemetry and event data to address your pain points head-on, empowering your IT to prevent incidents and delivering composite artificial intelligence (AI)-powered services (predictive, causal, and generative AI) for fast innovation.

Observability—Your key to reliable service delivery across complex IT systems

In a recent customer briefing, the topic of observability was discussed, along with the question of how BMC helps organizations solve the overwhelming amount of data and events. We shared a few key differentiators that demonstrate how BMC goes beyond processing telemetry and a short explanatory video.

There are many key features that BMC offers as part of BMC Helix ITOM, but I will highlight three here:

1. The FIRST key feature we’ll explore is dynamic service modeling (DSM), which revolutionizes how IT teams discover and manage services within their infrastructure. Through automated, real-time service modeling, BMC Helix ITOM ingests topology from BMC and third-party sources, identifying dependencies and relationships across the IT landscape, including infrastructure, applications, and software, to provide crucial visibility and context. By ensuring accuracy and consistency through automated reconciliation, this approach transforms the traditional methods, offering a comprehensive and dynamic understanding of the IT environment.

2. The SECOND key feature I’d like to highlight is root cause isolation. The business service is a complex and ephemeral graph of configuration items (CIs) and their relationships. Without the connected topology you get with DSM, and a business service to provide context for the domain, root cause isolation would not be possible.

Telemetry, events, and change requests are automatically mapped to the business service and impacted CIs. Causal AI is used to identify the root cause CI and correlate any impactful change requests. This eliminates the blame game when dealing with thousands of changes in the system.

3. The THIRD key feature I’ll highlight today is the BMC HelixGPT-powered best action recommendation (BAR) capability. BMC ITOM ingests textual data from telemetry, service management, and vulnerability systems, and ships a pre-trained large language model (LLM) with domain expertise.

The composite AI pipeline, based on predictions, impact, and root cause isolation, can then contextually ask BMC HelixGPT to summarize problem scenarios, surface log insights, and provide a BAR based on historical data.

As an example, imagine that you performed a code update, which resulted in increased CPU utilization that significantly strained host resources. A BAR can provide tailored recommendations by leveraging its pre-trained domain expertise and optionally fine-tuning it with customer data to address resource-related issues efficiently.

Achieving seamless functionality and uninterrupted service delivery is paramount. However, overwhelming data and events can lead to operational inefficiencies and prolonged downtime. With features like dynamic service modeling, root cause isolation, and best action recommendation, BMC Helix ITOM is the only fully integrated, open observability and AIOps solution with AI/ML-powered discovery, monitoring, optimization, automation, self-healing, and remediation of services, empowering IT to prevent incidents and innovate quickly. Click here to discover how BMC Helix ITOM can help you revolutionize your IT operations.

BMC Helix AIOps and observability has been recognized as “Cross Infrastructure Analytics Solution of the Year” in the 5^th annual Data Breakthrough Awards program conducted by Data Breakthrough, an independent market intelligence organization that recognizes the top companies, technologies and products in the global data technology market today.

“BMC Helix AIOps harnesses the latest innovations in AI to revolutionize cloud service delivery and operational visibility to generate insights across the entire application structure. Complex IT environments are challenging I&O teams to balance stability with speed and agility,” said Steve Johansson, Managing Director, Data Breakthrough. “BMC Helix AIOps has everything enterprises need for excellence in operations allowing users to understand system health, diagnose and fix problems faster and even predict and prevent potential issues before they occur. It truly transforms IT from reactive to proactive. Congratulations to the entire BMC team for their well-deserved 2024 Data Breakthrough Award win.”

The significance of this award, and what that means for your operations

As you know, your IT Operations teams face a difficult balancing act. With AI and ML at the forefront of driving efficiency and innovation, we designed the BMC Helix AIOps and observability to effectively utilize AI to increase the reliability of IT services and make IT more efficient. Our solution helps IT teams move out of firefighting mode, and we believe process-centric AIOps and observability represents the future of IT operations management, where traditional approaches are enhanced and augmented with AI-driven intelligence.

I’ll share with you the key features and benefits of BMC’s Helix AIOps and observability platform:

1. Automation across Multi-Cloud and Hybrid Environments: These solutions automate operations processes and build accurate inventories of configuration items (CIs), aiding in efficiently managing IT resources.
2. Dynamic Service Modeling: BMC Helix uses dynamic service models to integrate and normalize data, offering rich visualizations and a unified topology view across the entire underlying virtual and physical infrastructure, from application to network and cloud to mainframe.
3. Service Blueprints: BMC Helix provides customizable service blueprints for defining and maintaining services, allowing organizations to model their IT services efficiently.
4. AI and ML Application for Pattern Detection and Noise Reduction: By applying AI and ML, these solutions identify patterns, reduce operational noise, save time, and labor, and decrease the mean time to repair (MTTR).
5. Predictive Analytics for Future Outcomes: The solutions predict future outcomes using historical data, aiding in strategic decision-making.
6. Finding and Fixing Issues in Seconds: Our patented causal and generative AI algorithms rapidly diagnose and resolve issues using NLP and AI clustering. It streamlines incident management, enhancing IT efficiency and shifting focus from troubleshooting to strategic innovation.
7. Proactive Issue Remediation and SLA Optimization: These technologies preemptively address issues, thus maintaining service level agreements, enhancing the customer experience, and reducing incident generation.
8. Service-Centric Noise Reduction and Root Cause Analysis: The solutions effectively differentiate between critical and non-critical events, focusing on root cause analysis for efficient problem resolution.
9. Advanced Anomaly Detection: Both univariate and multivariate anomaly detection services are provided, enabling early identification and remediation of potential issues.
10. Service Outage Prediction: Utilizing ML techniques, these solutions predict service outages, allowing for proactive measures to maintain service quality.
11. Real-Time Incident Correlation: Using advanced ML algorithms like BERT, the system automatically correlates incidents, enhancing the speed and accuracy of major incident management.
12. Proactive Problem Management: The application of Kubernetes means clustering helps identify recurring incidents and streamline problem management.

Winning the prestigious title of “Cross Infrastructure Analytics Solution of the Year” in the Data Breakthrough Awards signifies more than just industry recognition. For you, it means entrusting your IT operations to a proven leader in the field, ensuring reliability, efficiency, and innovation at every step. With BMC Helix AIOps and observability, you can rest assured that you’re investing in a solution that has been rigorously evaluated and acknowledged for its excellence, ultimately translating into tangible benefits for your organization’s IT infrastructure.

The BMC Helix AIOps and observability platform represents a transformative approach to IT operations. Unlock your potential with our award-winning BMC Helix AIOps and observability platform today.

Learn more about our solution on our website.

Proactively addressing potential situations before they become outages is highly important for site reliability engineers (SREs) and DevOps teams. In this blog, I cover how BMC’s SRE and DevOps teams use artificial intelligence for IT operations (AIOps) to resolve issues before they become problems. I spoke with BMC Senior Director of DevOps Jason Rush and BMC SRE Manager Jason Ferens about it. Their organization supports all BMC SaaS customers, monitoring the reliability of their services and infrastructure. Their charter is to prevent and mitigate customer outages. Since introducing the BMC Helix AIOps solution, this organization has seen a dramatic increase in the prevention of outages and faster resolution of incidents.

Navigating heavy alert load and short response times

Before deploying BMC Helix AIOps, BMC SREs dealt with high alert noise. Customers’ issues would sometimes auto close, leaving the engineers without a way to track the issue down. Overall, there needed to be a more efficient way to proactively deal with the issues that would otherwise become service quality risks in the long run. Enter BMC Helix.

Service reliability improved with AI and observability

The DevOps and SRE teams implemented the solution about a year ago and use it as part of their daily operations. They built custom dashboards to get detailed insight into the performance of all customer environments and critical trends. The impact was an overall reduction in alert noise, shorter mean time to resolution (MTTR), and better health of customers’ environments.

BMC Helix AI-powered Situations enable engineers to understand what’s happening in customer environments, where the root cause is, and what was impacted. This insight shifts them from being reactive, chasing incident after incident, to being proactive. Now, because the IT teams know the health of the services, they can proactively address emerging issues and prevent outages.

Every second counts when troubleshooting an issue, and the BMC DevOps and SRE teams automatically pinpoint the incident’s root cause through automation. SREs can remediate incidents more precisely and improve and optimize customer environments. Here are the results these teams have achieved since they deployed the BMC Helix AIOps solution:

• 76 percent improvement in service health
• 60 percent MTTR reduction (under 30 minutes resolution time)
• 64 percent of outages prevented
• 1,034 successful remediations from three intelligent automations in one month

Running health checks to prevent incidents

BMC DevOps and SRE teams also track how often outages are avoided, called health checks. Health checks are performed when no alerts are open, but based on trend analyses by BMC Helix AIOps, identify when an issue will become an incident if the trend continues. As a result, engineers can remediate the customer issue, averting the problem altogether.

Here is an example of how a potential incident was resolved in a preventative way. Using BMC Helix Service Monitoring and BMC HelixGPT, the configuration item (CI) topology and analysis pointed to a root cause indicating critical status at the customer’s platform.

Figure 1: BMC Service Monitoring and BMC HelixGPT.

Based on the details of the associated incident, a third-party tool increased logging, resulting in high file system utilization. The team implemented BMC Helix Intelligent Automation, which ran when the alert fired, allowing the deletion of excessive logs to be performed before the file system utilization affected the customer.

By using BMC Helix AIOps, the Situation was cleared, and the performance of other tools was continuously monitored, allowing for self-healing operations, a nirvana for SREs.

Preventing outages with ServiceOps insights

The SRE team shares a commonality with BMC customers since many of them use BMC Helix AIOps and ServiceOps solutions to manage their day-to-day operations, including alerts and incidents. For instance, SREs developed a custom dashboard that pools data from BMC Helix ITSM and BMC Helix AIOps. This combined visibility allows the SRE team to address open incidents in their full context and accelerate decision-making. “Using BMC Helix AIOps and ServiceOps gives us a much better ability to prevent incidents.” – Jason Rush, Senior Director, DevOps, BMC

Engineers can easily track the number of incidents per customer and address them accordingly. As a result, the SRE team is more proactive, preventing outages with much higher precision.

An SRE’s 360-degree view of customers’ services and operations

As I mentioned previously, engineering teams can use BMC Helix to see the health of a customer’s environment. At BMC, the SRE team uses another BMC Helix dashboard, “BMC 360 Customer View,” to track the health of all our customer environments. SREs can see the health of all applications, infrastructure, resource utilization (such as CPU and historical ITSM tickets), and everything they need to know about each customer’s environment. Based on the overview dashboard, the SRE team knows where the issues are, and as a result, can dive into the incidents and services that require their attention.

How SREs remediate Kubernetes issues with BMC Helix

Let’s examine two examples of how AIOps and observability help the BMC SRE team solve common operational issues. The first example is an out-of-memory issue that was restarting a customer’s Kubernetes pods regularly. While the customer was not affected by this issue, it needed to be resolved to prevent it from progressing. Using the BMC Helix AIOps solution, SREs knew that adding more memory to the configuration would resolve all related alerts in the future. This represents an example of a situation that can be further automated with BMC Helix Intelligent Automation.

The other issue is filling out the logs on the user Kubernetes pods, which causes what is known as “pod evictions.” A Kubernetes pod eviction occurs when a pod running on a node is terminated and rescheduled on another node, resulting in instability when memory in the pod fills up, causing the pod to shut down and restart. The solution for this issue is upgrading the environment.

The SREs use BMC Helix AIOps to see when alerts related to this issue arise and remediate the threat before the pod is forced into the eviction. The proactive work done by the SRE team prevents the degradation of customers’ service health.

Achieving self-healing operations with ServiceOps, AIOps, and observability

It has been a remarkable journey for this BMC department as they embrace the power of ServiceOps. They’ve evolved from a constant firefighting mode to achieving self-healing operations thanks to the BMC Helix AIOps solution. What’s even more exciting is how the combination of AIOps and observability is ushering a new era of predictive solutions into the hands of DevOps and SRE teams.

“My day starts with AIOps.” – Jason Ferens, Senior SRE Manager, BMC

If you’d like your day to start smoothly, try BMC Helix solutions and follow this link.

Modern enterprise applications are deployed in hybrid multi-cloud environments. The system of engagement for end users is supported by modern, cloud-scale architectures deployed as containerized microservices. The system of record requires hybrid architectures spanning cloud to mainframe for seamless integration between modern and legacy systems.

For end users—global customers, partners, or employees who interface with mission-critical business services for financial transactions or administrative tasks—business services are synonymous with the brand. Bad service quality or outages can have a negative impact, resulting in financial penalties and brand damage. The attention span of a mobile end user is measured in seconds; a bad mobile experience in any industry can result in subscriber churn. App stores place the power of switching loyalties in the hands of the end user, who can download, install, and delete applications at will in seconds. This is why it is critical to measure end user experience in the context of end-to-end business service performance and availability.

Organizations are constantly looking to improve operational efficiencies, reduce errors, and optimize productivity; however, these same organizations are also challenged with the burden of manual toil. The goal is to achieve zero-touch operations, where processes and operations require little to no manual intervention during unexpected disruptions to business services that span a multi-layered public and private IT landscape.

For zero-touch operations, the solution—in addition to ingesting observability artifacts and integrating with service management solutions for incident and change—will apply correlation, predictive, causal, and generative artificial intelligence, and machine learning (AI/ML) algorithms to recommend and automate actions to remove manual steps. Additionally, a conversational AI-based experience enriches and personalizes the user experience.

In this blog post, I would like to highlight seven core AIOps capabilities that are required by organizations to successfully achieve zero-touch operations (see Figure 1):

Figure 1. Seven core AIOps capabilities for managing complex and constantly changing hybrid cloud environments.

These seven core AIOps capabilities are used to apply domain context, derive actionable insights from data, and, finally, automate the best action with confidence.

Apply domain context and derive actionable insights

The criticality for an impacted business service is measured by the service impact. Figure 2 below overlays the hybrid multi-cloud deployment with the first four AIOps capabilities that model the service and build Situation awareness to identify root cause and assess service impact.

Figure 2. Model a dynamic service (1), build Situation awareness based on alertevent fatigue (2), perform root cause isolation (3), and assess service impact (4).

1. Dynamic service model

Dynamic service models are used to represent a business service (e.g., mobile banking, voicemail, etc.). The business service adds domain-specific knowledge, which in turn adds context and improves decision-making.

A business service is modeled from topology ingested by discovery and monitoring tools. The goal is to eliminate any manual tasks and automatically reconcile and dynamically update the end-to-end topology that spans application to network and cloud to mainframe. In Figure 2 above, the grey oval shape (1) encapsulates all the configuration items (CIs) and their relationships that represent a business service.

The dynamic service model provides the underlying connected topology as a foundation to apply AI/ML algorithms. The model represents domain-specific knowledge of the business service. Putting a boundary around the impactful CIs helps make informed predictions, root cause determination, and recommendations.

Business services are built automatically starting with a CI that represents a service (e.g., application name, database cluster name, VMware cluster name, Kubernetes name space, or network switch). Based on the starting point CI, related CIs are pattern-matched to automatically build and update the service model. This removes the need to manually build or maintain service models. You can refer to my previous blog post for additional details on service modeling and blueprints.

2. Situation awareness

A Situation represents awareness around an active issue that is impacting or has the potential to impact a business service (e.g., network switch issues could potentially impact mobile banking users if not triaged and fixed in a timely manner).

Alert/event fatigue is a common problem for the service desk that is compounded by the complex and distributed nature of modern applications. For example, a network problem can trigger an alert/event storm that impacts every layer of the business service, from application to network and everything in between.

Deciphering the signal from the noise is beyond human cognitive abilities and requires an AI/ML-based approach to build Situation awareness of the problem. Correlation AI/ML algorithms are used to group alerts/events across the dimensions of time and text using clustering and natural language processing (NLP) algorithms. The resulting noise reduction draws focus to the problematic cluster(s).

The Situation clusters alerts/events in relation to the impacted CIs and is represented as a slice of the dynamic service model, as shown above in the blue oval shape (2) in Figure 2. While this Situation puts a lens on the brewing problem, at this stage, there is no root cause isolation or indication of current or future service impact. Noise reduction based on event/alert clustering is not enough to determine root cause.

3. Root cause isolation

Root cause isolation is required to identify the culprit in an active Situation, and then engage and/or automate best actions to restore an impacted business service.

Correlation AI/ML algorithms do a good job of noise reduction; however, they lack causation, which is required for root cause isolation. By the same token, algorithmic root cause isolation is required to eliminate the blame game that takes place in a typical war room. The ultimate goal is to minimize the impact of an outage and restore service.

To be deterministic and explainable, root cause isolation requires domain-specific knowledge. To achieve this, dynamic service models provide a third dimension of topology. Causal AI/ML algorithms are used to build a causal graph for the active Situation, perform graph traversal in the context of the alerts/events, and identify the root cause CI(s). In our example, the root cause CI is the network switch, represented by a green circle (3) in Figure 2 above.

The active Situation is automatically updated with the root cause CI. However, at this stage, the impact and urgency of the Situation is unknown. This can be determined by predicting the service impact.

4. Service impact predictions

Service impact analysis is required during an active Situation to assess the current or potential future impact to a business service. This helps identify the criticality to determine the best action needed to engage with ticketing and automation systems.

Service impact to a mission-critical business service can result in brand damage and financial penalties for an organization. Proactively assessing service impact is critical to prioritize the criticality of the active Situation, as shown in the red circle (4) in Figure 2 above.

Service impact is linked to the key performance indicators (KPIs) that are used to measure and assess the health and performance of a business service. KPI examples are service- and industry-specific (e.g., end user response time for a mobile banking application, voice quality for a voicemail application, user sentiment from social media feeds, number of transactions processed to measure revenue, or saturation events for infrastructure resources).

Predictive AI/ML algorithms are used to assess current or future KPI impact to the business service. They are applied against historical and current data to identify patterns and predict future outcomes. Common proactive approaches include:

• Predictions are used to report near-future deviations from threshold and/or normal behavior. This helps fix issues before users are impacted.
• Forecasting is used to assess and report on resource saturation. Proactively fixing resource saturation helps with planning and avoids potential outages.
• Univariate anomaly detection is used to observe metrics over time to find and report on outliers. This helps identify the needle(s) in the haystack, especially when looking across thousands of metrics.
• Multivariate anomaly detection is used to compare multiple metrics to find and report deviations from normal metric patterns. This helps find abnormal trends in data patterns across multiple dimensions.

With the Situation in place, the AIOps solution has successfully modeled the business service, reduced noise, identified the root cause, and assessed the service impact to establish criticality. The Situation also provides contextual input (prompts) for generative AI algorithms to accurately build a human-readable summary as shown in Figure 3 below. Note how context is captured based on the root cause, service impact, and causal chain of alerts/events to write an accurate problem summary based on event/alert data.

Figure 3. Human-readable generative AI problem summary identifying root cause CI and its impact.

Automate with confidence

Once the Situation has matured, the next step is recommending and automating the best action to take based on past Situations and historical ticket resolutions. The last three AIOps capabilities (5-7 below) help you make an informed decision and automate with confidence.

5. Best action recommendation

Best action recommendation is based on the analysis of past Situations represented in a knowledge graph and the processing of historical ticket data using generative AI.

Knowledge graph and past Situations

The knowledge graph is a graph-based reasoning framework used to represent past Situations. The Situation captures the causal chain of alerts/events across the different layers (cloud to mainframe), isolates the root cause CI, and identifies the end user impact.

The Situation enriches the knowledge graph with a semantic meaning that represents real-world knowledge, allowing for intelligent reasoning and inference. A good example is the generative AI Situation summary described in the previous section, which summarizes the problem across text, time, and topology for event/alert data. The knowledge graph also pattern-matches similar Situations from the past, as shown in Figure 4 below.

Figure 4. Similar Situation aggregated view for the past four months.

The knowledge graph learns and grows over time, recommending the best action based on past behavior. Past similar Situations in the knowledge graph are clustered and pattern-matched to provide automation recommendations based on the success or failure of past actions, as shown in Figure 5 below.

Figure 5. Automation recommendation based on past Situations.

Historical ticket and large language models

Additionally, historical ticket data (incident, change, defect) is used to train a large language model (LLM) that provides a best action recommendation based on historical resolutions. Figure 6 below shows a generative AI-based Situation event summary, along with two recommended actions based on the processing of historical ticket data. Using generative AI, the trained model is asked, for example, how to fix, a storage issue. Based on the results, the user can automate or manually run a recommended automation, ask the LLM to generate an automation script using the code wizard, and/or chat with the model to get more information. In the example below, we click on “Ask BMC HelixGPT” to ask questions and better understand the issue’s impact and which team has solved the issue in the past.

Figure 6. Generative AI problem summary and best action recommendation with actionable insight and conversational UI.

The Situation at this stage has enough context to confidently engage with other solutions to create incident(s) and change request(s), and then act by running automation tasks using automation tools. Based on root cause isolation, service impact prediction, and recommended best action, the system can automate with confidence.

6. Automatic ticket management

With the root cause and service impact identified, we can now automate the creation, prioritization, and routing of a ticket.

Create a single incident ticket for the Situation (not per each individual event) and target the right support group based on the CI(s) identified as the root cause. This eliminates the need for the first level of support to triage the Situation, and a second level of noise reduction is applied to reduce help desk incident fatigue. This also bypasses the need for a war room and eliminates the back and forth between different monitoring teams to establish root cause and ownership to fix the issue.

Assign ticket severity based on the current or predicted service impact. This helps prioritize the Situation so that support staff can focus and work on the most critical business-impacting issues.

7. Intelligent automation

Run the recommended automation based on resolution insights from similar Situations and past tickets. The recommended action(s) is based on the success of past actions and ticket resolutions, eliminating the need for support teams to manually process historical Situations and tickets. Change request approvals can also be automated depending on the change request risk assessment (e.g., restarting pods or scaling out virtual machines may be considered low risk, allowing for automated approvals).

To summarize, zero-touch operations can help revolutionize how organizations minimize customer outages and improve the end user experience. Adoption of AI/ML and automation with the seven core AIOps capabilities discussed in this blog provide the foundation to apply domain-centric service context, derive actionable insights from monitoring data that spans a complex multi-cloud IT landscape, and, finally, automate a best action recommendation based on historical success with confidence.

The AIOps capabilities in our BMC Helix Operations Management and BMC Helix Discovery solutions provide the foundation, and BMC HelixGPT brings the domain knowledge—typically held by subject matter experts—to apply correlation, predictive, causal, and generative AI/ML algorithms to solve complex IT operational issues.

In today’s dynamic, cloud environments, IT teams that include DevOps, IT operations, site reliability engineering (SRE), and platform engineering need a way to get accurate and easy-to-setup insights from large volumes of observability data. Without proper tooling to glean comprehensive insight across thousands of key performance indicators (KPIs), IT teams face slow reaction times, which can lead to service degradation. Manual analyses are no longer enough. The 24.1 release of the BMC Helix IT Operations Management portfolio demonstrates our investment in applying more practical use cases for causal, generative, and predictive AI.

Figure 1: Best Action Recommendation Example

We have enhanced our solutions with that include Advanced Anomaly Detection and a patented BMC HelixGPT-Powered Best Action Recommendation (BAR) for AIOps using BMC HelixGPT. We also added updates of our observability solution, described in further detail below. With these key enhancements, modern IT teams can:

Improve service reliability with Advanced Anomaly Detection

• Autodetect all anomalies using one-click configuration across your cloud services and infrastructure
• Fine-tune anomaly detection to unique environments with adjustable sensitivity
• Combine static thresholds and machine learning (ML) to identify both the known unknowns and unknown unknowns

Resolve incidents quickly and easily with generative AI

• Utilize knowledge from past incidents, situations, and remediation actions to reduce mean time to repair (MTTR)
• Use patented BAR insights to accelerate your response
• Get a sample code recommendation using BAR

Optimize performance and resource utilization

• Understand and act on trends more quickly with a combination of Advanced Anomaly Detection and BAR
• Find anomalies instantly, without domain knowledge or the need for query language
• Detect performance or resource bottlenecks more quickly without tedious configuration steps

Improve service reliability with Advanced Anomaly Detection

Advanced Anomaly Detection improves identification of issues and helps IT teams proactively find both known and unknown unknowns. IT environments are unique and complex, which makes setting thresholds complicated and time-consuming. Advanced Anomaly Detection (univariate) adds an autoconfiguration option to existing BMC Helix ML-based anomaly detection. Now, all KPIs are automatically analyzed and alerted on when the anomaly matches user-defined sensitivity settings. A single click enables anomaly detection for the entire environment, helping IT teams find previously unknown problems and saving time by eliminating tedious parameter configuration. Policies can still override the global settings across one time series (univariate anomaly detection), while also allowing for management of anomalies across multiple time series (multivariate anomaly detection).

Figure 2: Advanced Anomaly Detection Example

In combination with BMC Helix AIOps functionalities, Advanced Anomaly Detection events further enhance the Situations functionality, creating a powerful solution that allows IT teams to be proactive and find and fix issues faster.

BAR and BMC HelixGPT help IT remediate issues instantly

We are continuing to help IT teams be more productive with practical uses for our generative AI. Back in June, we announced BMC HelixGPT, embedded across the BMC Helix platform. BMC HelixGPT uses large language models (LLMs) trained on enterprise domain data. It becomes an expert in your IT environment. With the 24.1 release, we have added the BAR feature based on BMC HelixGPT to help IT practitioners resolve issues and eliminate days of troubleshooting.

Trained on past incidents, situations, and remediation actions, BAR uses generative AI algorithms to accelerate the time to resolution with actionable insights in a human-readable language—no need to learn another query language. Additionally, BAR can dramatically improve an IT team’s efficiency by using insights from similar correlated incidents to automatically generate code templates for the end user to fix an issue.

Figure 3: Best Action Recommendation with Ansible Code Snippet

Practical BAR examples

Let’s assume that your code update resulted in an increased CPU utilization that significantly strained host resources. To remediate the issue last time, an on-call SRE rolled back a code deploy, helping reduce CPU load. When a similar situation happens in the future, BAR will surface how the situation was resolved and help recommend a potential resolution with the steps provided to resolve the problem.

If you are experiencing longer than expected response times on your requests (slow queries or similar), it may be due to higher-than-expected resource utilization. BAR provides guidance on how to fix the issue. In this case, it recommends running the script to increase the storage space or other pegged resource and then restarting a Kubernetes pod.

Another practical use would be to help recommend patching. Let’s assume you missed patching a set of host instances with the latest security or operational updates. Based on past resolutions, BAR will be able to help you identify what was missed and recommend implementing the latest patch.

The applications of BAR are virtually limitless.

Observability enhancements bring more comprehensive visibility

New BMC Helix Intelligent Integrations enhance IT coverage

We have expanded BMC Helix Intelligent Integrations with Icinga, allowing our customers to get enhanced visibility into their tooling, as well as bring and correlate new data sources into BMC Helix. In this release, we also enhanced our existing connectors, including Entuity, Zabbix, Prometheus, SolarWinds, Datadog, VMware vRealize Operations (vROPS), Cisco AppDynamics, and CA UIM. With these updated connectors, BMC Helix IT Operations Management solutions provide better coverage and visibility into data from these tools, helping IT to quickly navigate to a specific issue.  For details, please refer to our documentation.

Better control and security with flexible log index management

With this release, BMC Helix AIOps capabilities, specifically those in BMC Helix Log Analytics, deliver enhanced security and allow better control over log data. Now, IT practitioners get flexible log management with multi-index support per tenant. With this flexible log segregation and archival duration, IT teams can better manage security and costs.

Enhanced BMC Helix Discovery Technology Knowledge Updates content

Now, BMC Helix Discovery Technology Knowledge Updates (TKU) content is expanded with new cloud, software, storage, and network solutions. BMC Helix Discovery continues to lead the industry with comprehensive, out-of-the-box discovery coverage, enabling IT teams to automatically discover and map their IT assets and dependencies with unparalleled accuracy. BMC Helix Discovery provides even more comprehensive visibility into complex IT landscapes, helping IT teams optimize operations, reduce risk, and accelerate digital transformation. For the full list, please see our documentation.

If you wish to check these out, please contact sales.

IT operations (ITOps) teams now more than ever need an IT operations management (ITOM) solution that is both highly observable and leverages the power of artificial intelligence for ITOps (AIOps) to drive more actionable insights. When you’re dealing with complex, dynamic IT environments, it can be tough to get the visibility you need to make informed decisions.

That’s where BMC Helix comes in, and we are delighted to announce our latest 23.4 Fall release for BMC Helix Operations Management. It’s packed full of new innovations that deliver unparalleled real-time visibility into your IT environment and the ability to analyze data across all underlying domains and services across the entire IT estate, from mainframe to on-premises to the edge.

BMC Helix Operations Management uses machine learning (ML) algorithms to analyze patterns and anomalies in real-time data, identifying potential issues before they impact end users. This enables IT teams to take proactive measures to prevent incidents and minimize downtime.

In this release, we’ve also rolled out several enhancements across our ITOM portfolio.

BMC Helix Operations Management

• Service Blueprints. New, out of the box for microservices, Kubernetes, cloud, and application program monitoring (APM), Service Blueprints provide users with the ability to define simple templates like microservices on Kubernetes, while improved auto-detection across different components enhances service modeling.
• Situation Explainability powered by causal AI provides a visual representation of root cause and now accepts user-driven Situation feedback, allowing additional Situation information to be added by a user for faster root cause isolation.

Figure 1. Situation Explainability.

• Situation Fingerprinting powered by AI, GPT, and natural language processing. Automatically identify whether a similar situation has previously occurred and eliminate the need to diagnose the same problem again.

Figure 2. Situation Fingerprinting.

BMC Helix Discovery

BMC Helix Discovery is our SaaS-based, cloud-native discovery and dependency modeling system that provides instant visibility into hardware, software, and service dependencies across multi-cloud, hybrid, and on-premises environments.

In this release, we’ve added Visual Query Builder, which allows customers to build complex queries using a simple drag-and-drop method for a faster and more intuitive and available experience that removes the need for specialist query scripting skills. BMC Helix Discovery is continually evolving, and we are working towards releasing a deep container discovery capability in a future release that which will enhance visibility into embedded containers for site reliability engineers (SREs) and end users.

Figure 3. BMC Helix Discovery.

BMC Helix Intelligent Integrations

BMC Helix Intelligent Integrations use REST APIs and Webhook mechanisms to communicate with a data source, providing an easy-to-use, click-and-connect capability to configure an integration and import resource information, topology, and services from third-party data sources for an end-to-end view of your environment. In this release, users will find new enhanced support for Datadog, Microsoft System Center Operations Manager (SCOM), Dynatrace, VMware vRealize Operations, SAP HANA^®, and ServiceNow.

The enhanced connectors make it faster and easier for customers to add their third-party monitoring data to BMC Helix Operations Management, delivering more data sources to strengthen the AIOps algorithms’ ability to isolate root cause and improve mean time to repair (MTTR).

Figure 4. Root cause isolation leveraging BMC Helix Intelligent Integrations.

Our development is highly dependent on the feedback we receive from our customers, partners, and the wider analyst communities. Thank you to all of you who contributed feedback to us. To continue the discussion, tell us how you’re using the new features and workflows and share suggestions to improve the product experience on the BMC Helix Operations Management community forum.

Additional Resources

• BMC Helix Named a Leader in the The Forrester Wave^™: Process-Centric AI For IT Operations (AIOps), Q2 2023
• BMC Helix Operation Management Release Notes
• BMC Helix AIOps Frequently Asked Questions (FAQs)

We are thrilled to share some exciting news from the recent TM Forum Digital Transformation World (DTW) 2023, hosted in Copenhagen. At this prestigious event, BMC was honored with the Outstanding Catalyst Showcase Award for its pivotal role in revolutionizing telco service assurance through artificial intelligence for IT operations (AIOps) with an innovative approach, attention to detail, and a commitment to pushing the boundaries of what’s possible in the telecom industry.

Every year, the event brings together communication service providers (CSPs), technology suppliers, and enterprises working globally, in the telecom industry, offering vendors an opportunity to showcase their latest innovations for the telecom industry and provide insights into groundbreaking software solutions that are shaping the future of communication technology.

The winning solution

BMC’s winning solution, titled “Revolutionizing service assurance through AI-powered, intent-based systems for continuity and customer satisfaction,” was made possible by our highly skilled technology partner, Telia, and our customer, Telecom Italia. The submission was focused on how customers can leverage BMC Helix AIOps and machine learning (ML) capabilities to help customers:

• Increase network availability to improve customer satisfaction
• Improve efficiency and simplify operations using AI/ML-based automation
• Achieve higher performance as result of predictive capabilities
• Reduce manual activities in the network operations center (NOC) and substantially reduce the corresponding operating expenditures (OpEx)

The BMC Helix platform promises to revolutionize the way telcos provide service assurance and will open possibilities for efficiency, reliability, and scalability in the telecom sector.

Acknowledging excellence

While BMC emerged as the winner in this category, it is important to recognize the remarkable achievements of all the participants and especially our technology-focused partner, Telia. The level of innovation and dedication displayed by each company in this event was truly awe-inspiring.

As we celebrate this award, BMC will continue to push the boundaries of what’s possible in the world of telecoms with our AIOps capabilities to shape a more connected, efficient, and innovative telco.

To learn more about BMC Helix Operations Management, click here.

In today’s technology-driven world, the role of IT operations management has evolved beyond ensuring smooth operations to also include some of the critical aspects of cybersecurity. Network blind spots, inadequately managed software licenses, outdated software, and other security vulnerabilities have become the Achilles’ heel of many organizations, and organizations need a powerful ally to tackle these security concerns. In this blog, I’ll compare these digital challenges to an urban landscape in the real world to demonstrate how an effective security solution creates a positive impact across the organization.

Security challenges faced by IT operations management teams

Managing a sprawling network is like overseeing a busy city with hidden alleyways and secret passages. Just as it can have blind spots with limited visibility, IT teams often encounter those same areas of limited visibility in their network infrastructure—exacerbated by modern networks, legacy systems, and rapid changes brought about by cloud adoption.

These concealed corners are easy for bad actors to exploit, taking advantage of gaps to infiltrate a network undetected. Without a clear understanding of an entire network’s layout, vulnerabilities can remain obscured, allowing cyber threats to proliferate undetected and ultimately put the entire network ecosystem at risk. Now imagine in that busy city, how its expansion can result in new neighborhoods and streets that make getting a holistic view even more challenging.

One pitfall of an organization’s infrastructure sprawl is effectively managing software licenses to ensure they are not underutilizing or over-purchasing. In an urban landscape, this would be the role of city planners who issue and oversee the commerce licenses and permits necessary for smooth operations.

In IT, license confusion creates avenues for bad actors to introduce unauthorized software applications into the mix, much like contraband goods flooding a city’s retail market. These rogue applications then introduce potential security vulnerabilities that can wait for the opportune moment to strike. Comprehensive license management maintains order and ensures that only authorized software is in place, much like law enforcement keeps track of and shuts down counterfeit goods.

A resilient infrastructure

Software, much like cities, follows a constant cycle of growth and evolution. Just as a city bolsters its infrastructure like utilities, roads, and bridges to ensure its resiliency, software relies on updates and patches to protect against vulnerabilities and exploits that threaten its integrity. An outdated software system is an easy target for cyberattacks, granting cyber intruders access to breach the system’s defenses. Neglecting software updates is akin to ignoring an aging and unprotected infrastructure, leaving both susceptible to threats.

In response to these challenges, organizations must adopt proactive measures to address vulnerabilities and fortify their cybersecurity defenses. Comprehensive discovery solutions offer holistic visibility into the software landscape, ensure meticulous license management, and facilitate strategic vulnerability assessments, providing a digital health check and reinforcing defenses against modern cyber threats. In this sense, these solutions mirror city planners who keep streets lit for maximum visibility and ensure that each building adheres to codes and regulations.

The consequences of ignoring IT security

Imagine the aftermath of a major disaster hitting a city—recovery efforts, rebuilding, and restoring normalcy all come at a staggering cost. Similarly, a security breach within an organization can be nothing short of catastrophic. Beyond the immediate expenses required to mitigate the breach, organizations also have direct costs, such as forensic investigations, legal consultations, and notification processes, as well as the hidden costs of diverting IT teams from their regular duties and innovation projects to remediate the breach. This is similar to diverting a city’s resources from development to disaster recovery—a setback that affects the community’s growth.

Think of an organization’s digital infrastructure as a vital part of a city’s utility network—power grids, water supply, and communication systems that underpin daily life. Now imagine this infrastructure falling into the wrong hands, orchestrated by individuals with malicious intent. A compromised infrastructure can be exploited for launching attacks on other organizations, distributing malware, and participating in illegal activities that threaten the integrity of the digital landscape and broader digital ecosystem. The same holds true for cities, where infrastructure weaknesses might lead to malicious blackouts or ransomware attacks on utilities.

The implications of these actions go beyond just financial losses; they draw the attention of law enforcement agencies, legal bodies, and regulatory authorities, yielding legal consequences, fines, and sanctions that further exacerbate the damage. Cities combat these challenges by collaborating on security protocols and information sharing to prevent infrastructure vulnerabilities and regional crime waves.

Guarding the IT security cityscape

Organizations can combat these issues by implementing a comprehensive discovery and security solution like BMC Helix Discovery, which safeguards infrastructures and contributes to the overall resilience of the digital landscape. Think of it as the digital landscape’s planner, providing a panoramic view of the entire IT landscape and eliminating any blind spots that might conceal potential threats. With real-time discovery and mapping capabilities, IT teams mirror the city planners who meticulously track every building, road, and intersection.

This comprehensive visibility extends to identifying all connected devices, much like surveillance cameras capturing movement across the city. In this digital metropolis, BMC Helix Discovery empowers IT teams to detect even the most inconspicuous devices, safeguarding against potential threats and enabling swift response to any suspicious or unauthorized activity.

In the area of managing software licenses, BMC Helix Discovery assumes the role of a diligent license registrar, meticulously maintaining an accurate inventory of software licenses and their usage across the organization, just as a city’s licensing department diligently tracks permits to prevent unauthorized activities, BMC Helix Discovery optimizes costs and mitigates legal risks by ensuring compliance with software licenses.

Within the digital landscape, software vulnerabilities mirror the cracks that can emerge in a city’s infrastructure, threatening its overall stability. Acting as a vigilant city inspector, BMC Helix Discovery supports vulnerability assessment by swiftly pinpointing outdated or unpatched software to prevent the vulnerability exploits we discussed earlier.

As organizations strive to secure their digital frontiers, they must heed the lessons of urban management—leveraging proactive planning and maintenance to creating a safe and thriving environment. The parallels between technology and a city in the real world underscore the importance of resilient systems to withstand threats while continuing to evolve and flourish.

Just as a city thrives when its governance is proactive, vigilant, and responsive to potential threats, an organization’s digital environment flourishes when equipped with comprehensive discovery solutions that proactively deliver network visibility, effective license management, and enhanced vulnerability assessment. BMC Helix Discovery ensures that blind spots are eradicated, licensing is meticulous, and vulnerabilities are promptly addressed. Just as a well-managed city thrives amid responsible governance, a digitally secure ecosystem ensures a safer and more resilient IT environment that fosters innovation, growth, and trust.

To learn more about BMC Helix Discovery capabilities, try the free self-guided demo visit our website: www.bmc.com/discovery, and subscribe to our YouTube channel.