When HPE’s acquisition of BlueData was first announced in late November 2018, our co-founder and CEO Kumar Sreekanti outlined the synergies with HPE in his blog post here. Now we’re very excited to announce the next phase of the BlueData journey: BlueData’s software is generally available from HPE and integrated into HPE’s go-to-market strategy. Internally within HPE it’s referred to as our “new product introduction” and “business day one”. It’s a major milestone for our team and the integration.
In planning for this new milestone, we’ve spent a lot of time over the past several months listening to our customers and partners on a wide range of topics including AI / ML, Big Data Analytics, Edge Computing, Cloud, and Kubernetes. Admittedly, it’s been a whirlwind of activity – both as we combine with a much larger organization and as the overall ecosystem continues to evolve and change rapidly.
In those conversations, three common themes emerged:
- The importance of Choice: the flexibility to deploy any application or tool, whether open source or commercial, on any infrastructure (including multi-vendor and multi-cloud)
- The need for Speed: providing rapid response and on-demand capability to meet the requirements of data science teams, helping them to deliver faster time-to-insight and faster time-to-value
- The imperative of Innovation: enabling new business outcomes and driving compelling business value, leveraging the power of AI / ML and advanced analytics
Today, on behalf of the entire HPE and BlueData team, I’m thrilled to share some of the details of our strategy and vision to help accelerate AI-enabled business innovation and data-driven digital transformation without compromising on customer choice or the need for speed. Here’s how it aligns with each of the three themes:
BlueData will retain the ability to run on any infrastructure. The BlueData EPIC software platform is built on container technology, enabling infrastructure portability across on-premises, hybrid cloud, and multi-cloud environments.
Now that BlueData is part of HPE, customers can continue to purchase the container-based BlueData software platform standalone – and they can continue to install it on servers from other hardware vendors, tap into data from other vendors’ storage systems, and run it on public cloud compute and storage environments including Amazon Web Services, Microsoft Azure, and Google Cloud.
With the BlueData software platform, our customers and partners can also continue to onboard commercial or open source distributed data platforms of their choice. BlueData already provides pre-tested application images of popular distributed platforms and AI / ML tools such as Cloudera, Spark, Kafka, H2O, and TensorFlow through our App Store. With HPE, our vision is to build partnerships with the broad ecosystem of AI / ML and Big Data / Fast Data applications so that our customers can get faster, streamlined access to best-of-breed tools for their deployments. And we will continue to provide the ability to add their own preferred frameworks and applications to the App Store, offering the ultimate in flexibility.
BlueData pioneered the “as-a-service” delivery model for on-premises and hybrid cloud deployments of AI / ML and Big Data Analytics. Fortune 500 and Global 2000 financial institutions, healthcare organizations, retailers, manufacturers, and other industry leaders leverage BlueData as their platform to deliver self-service and on-demand environments for AI and Analytics. Data science teams can build and iterate on their models more quickly and deliver greater business value and faster time-to-market for new innovations.
Together with our colleagues at HPE, our strategy goes well beyond these product innovations to deliver even greater “speed” for our customers. Enterprise IT organizations can’t keep up with the fast-paced innovations in the open source and commercial ecosystem of AI / ML, Data Science, and Big Data Analytics tools. Going forward, HPE will be providing pre-integrated and ready-to-run solutions for different use cases and configurations – combining our software with HPE Apollo Systems to accelerate deployments, reduce management complexity, lower cost, ensure greater efficiency, and future proof their investments.
Another challenge for many organizations is how to automate their “Day 2” operations for any deployment. We plan to integrate BlueData with HPE’s AI for Operations (AIOps) platform, HPE InfoSight – enabling predictive support automation analytics and intelligent AI-powered infrastructure solutions that can adapt and self-adjust in real time.
Finally, HPE Pointnext will offer new advisory services for solution implementations and ongoing support operations, ensuring success and faster time-to-value for our customers’ AI and data-driven initiatives.
AI / ML and data analytics are transforming every industry. Data scientists are creating new game-changing innovations, delivering competitive advantage, and disrupting business models.
In particular, enterprise adoption of AI is accelerating rapidly: the number of enterprises implementing AI grew 270% in the past four years, according to Gartner’s recent 2019 CIO Survey. And when Gartner asked CIOs which technologies are game changers for their organization, AI and Machine learning are at the very top of the list; Data Analytics (including Predictive Analytics) aren’t far behind, representing the second spot on the list.
Through the lens of our customers and partners, we see a convergence of trends in AI / ML, Big Data / Fast Data, and Containerization / Kubernetes to deliver next generation AI-injected applications that span from the edge to the core to the cloud.
To this end, we’ve embarked on a differentiated Hybrid IT product strategy and vision to help HPE BlueData customers accelerate their innovation using AI / ML and Analytics. I’ve outlined some of the key aspects of that strategy and vision here:
- AI / ML Pipeline Operationalization – The true north in realizing value from AI / ML is the ability to deploy, manage and inspect ML models in production for successful delivery of AI-based systems. Thus far, the emphasis has been on model development using a variety of different tools and libraries. Enterprise IT teams now face major pain points around not only managing the massive influx of models but also these production deployments. The BlueData product development team is leaning into this area to provide an AI / ML infrastructure software platform to store, manage, deploy, and operationalize these models.
- AI-Ready, Invisible Kubernetes – The AI / ML ecosystem is exploding with new open source projects and products that are being written from the ground up to leverage containers using the Kubernetes API. Data workers want to harvest these new projects without being exposed to the details of the underlying infrastructure APIs. BlueData has been at the forefront of simplifying the deployment and delivery of complex, stateful applications such as Hadoop, Kafka, and Cassandra using the power of Docker containers under the hood. More recently, our engineers started the KubeDirector open source project, an open source custom controller for Kubernetes (K8s). Over the next several quarters, we will extend the BlueData platform to offer differentiated and managed Kubernetes features that focus on AI / ML operationalization, secure high performance data access to existing data lakes, and extensibility to leverage cloud-based Kubernetes services such as GKE, EKS, and AKS.
- Consumption-Based IT Models – Our customers have been loud and clear: they love the cloud consumption model and want a cloud-like experience regardless of the underlying infrastructure. Together with HPE’s portfolio of differentiated hybrid IT offerings and HPE GreenLake consumption-based IT models, we at BlueData want to deliver a managed software-as-a-service experience to simplify the deployment and operation of AI / ML and Big Data Analytics in a hybrid cloud architecture. As such, customers should be able to come to a single portal, choose the AI and Analytics products and tools they want to use and specify where to use them – whether in their own data center or in a public cloud – and ultimately pay for these services to a single entity.
As we start this new chapter in our journey as part of HPE, I’m very proud of our team and grateful to our customers for keeping us focused on the mission at hand: to drive greater business value with AI / ML and Analytics in the enterprise.
To learn more, I’d encourage you to check out our online digital event and interactive discussion: “Deploying AI in the Enterprise” (now available on-demand). And if you’re not familiar with BlueData, this brief demo video provides a good overview and drills down into some of the themes I outlined above: