BMC has announced an expanded Big Data strategy to automate, accelerate and secure enterprise-class Hadoop environments, enabling operational excellence and a competitive edge in the digital age. Adding to its Big Data strategy, BMC also announced Control-M Automation API, designed to improve Hadoop application deployment agility.
The digital universe is doubling every two years, and by 2020 about 1.7 MB of new information will be created every second for every human on the planet, according to IDC. The challenge that businesses face is that the more volume, velocity, and variety of data that is introduced into the organization the more the need for a sophisticated and scalable approach to managing the big data environment. Mastering this data is fundamental to every organization’s successful digital transformation – and failure to leverage the data and analytics will cripple an organization’s ability to meet customer expectations and competitive pressures.
“Many companies are rushing to deploy Big Data projects as part of their digital transformation to create new business models, accelerate growth, and radically reduce cost structures,” said Robin Purohit, group president, Enterprise Solutions Organization at BMC. “However, implementing a Big Data initiative can be challenging, and once you move from the sandbox to production it’s important to integrate with existing enterprise applications and optimize the costs of underlying infrastructure. BMC’s Big Data solutions provide the right tools to make production Hadoop environments successful in the enterprise.”
Automation of workflows and integration of Hadoop with the technology stack is key to delivering big data projects faster and ensuring reliability and scalability. BMC’s Control-M solution accelerates the delivery of big data projects and allows seamless integration of Hadoop workflows with other applications in the datacenter and cloud.
Big data initiatives running at scale involve huge volumes of data that need the infrastructure resources to scale up quickly. With seemingly unlimited possibilities for data to increase, it is important to operationalize the infrastructure to ensure it is running at peak performance. BMC’s TrueSight Capacity Optimization solution helps to plan and rightsize Hadoop environments – including compute, storage and network resources, ensuring control over infrastructure costs, while the TrueSight Operations Management helps IT deliver uninterrupted service.
Protecting applications and the data they use is essential, and to accomplish this, you must first know all the assets you have, how the assets depend on each other and most importantly, how they support the business. The BMC Discovery enterprise management solution provides a dynamic, holistic view of big data infrastructures including Hadoop, storage, analytics and consuming processes, giving IT crucial visibility across the entire organization. Proper discovery and dependency mapping ensures that IT avoids siloed big data initiatives, ensures compliance, and secures the environment.
"As big data becomes more and more central to enterprises strategic planning, the ability to effectively and efficiently manage production Hadoop deployments at scale becomes increasingly important," said Stephen O'Grady, principal analyst, RedMonk. "BMC's focus is in building on its long history of enterprise management to bring those capabilities to the Big Data space generally and to Hadoop specifically."
"Control-M for Hadoop is uniquely positioned to centrally to automate workloads inside and outside of Hadoop, giving us total control and visibility to our entire Big Data ecosystem,” said Darren Chinen, senior director of Data Science and Engineering at Malwarebytes. “In the modern enterprise, cloud infrastructure has allowed us to scale elastically and manage compute costs by workload hour. Control-M is enabling Malwarebytes to manage cloud infrastructure, Hadoop applications, ETL jobs, and dashboard refreshes in a way that takes advantage of the cloud billing model."
BMC is also announcing the expansion of its industry-leading Control-M for Hadoop solution with the release of the Control-M Automation API. The Control-M Automation API is a set of programmatic interfaces for Hadoop architects, engineers, and developers to use Control-M in a self-service manner within the agile application release process.
Using JSON notation for job definitions, GIT and RESTful APIs for validation, configuration, and deployment, workflow-scheduling artifacts are seamlessly integrated with preferred tools used to automate the Hadoop application release and deployment process. This allows Hadoop program teams to shrink the development-to-production cycle, delivering new capabilities to the business faster and increasing the value of their big data initiatives.