BMC Software’s recent acquisition of StreamWeaver reflects how BMC plans to meet its customers’ DataOps and AIOps needs, as those customers work in increasingly data-centric and distributed environments.

Statements by BMC representatives reflect how StreamWeaver, which offers data-streaming integration and management tools and platforms, will enhance BMC’s Helix service- and operations-management platform, offering improved observability and cloud migration across distributed environments, achieved largely through AIOps.

StreamWeaver has rich capabilities to integrate cloud environments that will further accelerate the Helix AIOps roadmap “to enable data-driven businesses and great customer experience,” said Ali Siddiqui, BMC’s chief product officer, during a keynote address at BMC’s user conference BMC Exchange 2021  in late October.

AIOps Integration

As part of BMC’s “doubling down on Helix,” StreamWeaver will also offer BMC AIOps integration, such as improved discovery for mainframe servers, application mapping and data-driven business insights, Siddiqui said during the keynote.

These capabilities include integrations with distributed microservices-based architectures, automated remediation and increased support for DevOps and ServiceOps overall. BMC is also hoping StreamWeaver, as well as further product and services innovations, will help it better support customers by applying AI and machine learning (ML) analytics capabilities to meet business goals.

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BMC President and CEO Ayman Sayed on what is required for the “autonomous digital enterprise.”

On a higher level, BMC, as a legacy player that has offered IT services and tools for decades, is also seeking to attune itself to the modern IT and business needs of its customers that seek to become “autonomous digital enterprises,” said BMC President and CEO Ayman Sayed during his keynote.

“An autonomous digital enterprise is the model by which a company, through the use of technology, enables key traits to win and expand in the industry,” Sayed said. “Starting by focusing on the customer and customer centricity, the ability to take the data and translate it into actionable insights involves the business offering and agility, which is the ability to run business initiatives quickly, and to be able to respond rapidly to all the changes that happen around us all the time.”

This, he said represents a change in mindset and a shift from the traditional model of a five-year strategy in which every step is planned out far in advance. In this new approach, Sayed said, “it doesn’t matter what gets thrown at us, since we’ll be agile, and then we’ll be able to pivot and evolve our offering, all while focusing on customers and leveraging that data that’s coming in.”

Indeed, tools and processes that StreamWeaver — and likely other acquisitions in the future — will provide, along with continued product development, should further support BMC’s mission to help its customers improve business inferences and decision-making processes that are very much AIOps- and data-driven.

In other words, collecting data from distributed data sources and pooling it together in a data lake is just a starting point, while the ability to analyze and apply data-centric inferences to improve customer experiences is key.

“Organizations are realizing that simply putting lots of diverse data into the cloud or a data lake won’t magically create meaningful insights — not without further integration, transformation, enrichment and orchestration,” Noel Yuhanna, a Forrester analyst, wrote earlier this year in the report, “Enterprise Data Fabric Enables DataOps.”

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“Delivering connected data across hybrid and multicloud sources isn’t trivial, especially with growing data volumes, complexity and the need for rapid ingestion,” Yuhanna wrote. “Organizations want to democratize data to allow business users to access  and leverage all data themselves to support faster and more accurate business decisions.”

Enhancing Decision-Making Processes

For a legacy player like BMC, StreamWeaver reflects how its new owner is seeking to modernize its Helix and other platforms by infusing them with artificial intelligence and machine learning capabilities, Torsten Volk, an analyst at Enterprise Management Associates (EMA), told InApps Technology.

The ability to discover and ingest operations data from distributed microservices applications within the context of DevOps and IT operations data is vital to help users make the most of AI/ML capabilities to minimize operations cost while maximizing agility, Volk said.

Achieving the vision of a data-driven enterprise is “the most critical goal in enterprise computing today,” Volk said. “Any tool that can help in creating and continuously enhancing the data model that is required to connect all relevant data sources in DevOps directly contributes to increasing  the impact of AI/ML and therefore enabling the overall organization to solve short-, mid- and long-term issues in a business KPI-driven manner.”