BMC announced new innovations for the BMC Helix SaaS solution that help businesses better manage and automate complex IT operations and orchestrate application and data workflows across any hybrid environment to deliver an improved employee and customer experience.
Understanding the frequent changes and shifting contexts of business services and supporting environments across the enterprise requires a solution like BMC Helix ServiceOps. It brings service and operations management together with differentiated capabilities that provide a deep level of context and insight through benefits like:
- Protecting the business from the risk of outages and slow performance: The BMC Helix solution highlights problems related to business services in their entirety and not just individual components. Incidents, alerts, and data from operations and service requests are correlated to help cross-functional teams pinpoint root causes faster.
- Scaling capacity with AI: BMC's enhanced AIOps capabilities identify performance and root cause outages by applying pre-trained AI and ML to observability data and dynamic service models to assess service health, look for future service impacts, and provide proactive responses. This ensures teams can better keep pace with the sheer volume of metrics, events, and alerts.
- Personalizing employee and customer experience: The BMC Helix solution delivers a consumer-like, personalized service experience across traditional IT and business functions such as HR and customer service management through virtual agents, knowledge bases, live chat, and tickets that make it easy for customers and employees to request and get help.
- Propelling innovation: With enriched ServiceOps data and connections via working teams' tools of choice, the BMC Helix platform enables operational excellence to support agile DevOps to create new apps and services that enhance the business.
BMC Helix Control-M—the application and data workflow orchestration SaaS platform—responds to the demand to produce more with capabilities that help IT operations eliminate redundant, time-consuming tasks and risks. IT organizations can support decentralized product teams to orchestrate complex application and data workflows across disparate technologies and securely build, manage, and monitor these services in production to ensure SLAs are met and business services are delivered on time, every time.
Updates to the BMC Helix Control-M solution simplify complexity with:
- Advanced functionality and self-service interfaces that improve collaboration between IT operations, developers, data engineers, and business users to deliver new products into production quickly, securely, and at scale with a self-service SaaS experience.
- Strategic integration with Apache Airflow and cloud data services including AWS Glue, Azure Data Factory, GCP Dataflow, Databricks, and more that orchestrate application and data workflows, whether the data is on-premises or in the cloud.
- Single unified user view for all workflows and interfaces that provides operational efficiencies for multiple roles throughout the organization.
"The complexity and scale of today's IT environments require businesses to seek the highest level of integration and automation from their cloud tools to receive the information needed to prevent and resolve issues quickly," stated Ali Siddiqui, chief product officer at BMC. "As silos come down to drive more collaboration, the tools IT professionals use need to work seamlessly across groups to enable the innovation needed to become an Autonomous Digital Enterprise."
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...