by Mitesh Shah
Data warehousing architectures have evolved considerably over recent years. As businesses try to derive insight as the basis of value creation, ALL roles must participate by leveraging new insights. As a result, analytics needs are expanding, markets are transforming and new business models are being created. This ushers in increased requirements for self-service analytics and alternative infrastructure solutions. Read on to learn how the “software-defined environment” (SDE) that utilizes container technology can help you meet expanded analytics needs.
Adaptability delivered through software-defined environments
From an avalanche of new data, to mobile computing and cloud-based platforms, new technologies must move into the IT infrastructure very quickly. Traditional IT systems—hampered by labor-intensive management and high costs—are struggling to keep up. IT organizations are caught between complex security requirements, extreme data volumes and the need for rapid deployment of new services. A simpler, more adaptive and more responsive IT infrastructure is required.
One of the key solutions on the horizon is the SDE which optimizes the entire computing infrastructure – compute, storage and network resources – so that IT staff can adapt to different types of workloads very quickly. For example, without an SDE, resources are assigned manually to workloads; the same assignments happens automatically within an SDE.
Now, dashDB Local (via Docker container) is available as an early access client preview. I hope you will test this new technology and provide us valuable feedback. Learn more, then request access: ibm.biz/dashDBLocal
By dynamically assigning workloads to IT resources based on a variety of factors, including the characteristics of specific applications, the best-available resources, and service-level policies, a software-defined environment can deliver continuous, dynamic optimization and reconfiguration to address infrastructure issues.
Software-defined environment benefits
A software defined environment framework can help to:
- Simplify operations with automated infrastructure tuning and configuration
- Reduce time to value with a simple, pluggable and rich API-supported architectures
- Sense and respond to workload demands automatically
- Optimize resources by assigning assets without manual intervention
- Maintain security and manage privacy through a common platform
- Facilitate better business outcomes through advanced analytics and cognitive capabilities
A software-defined environment fits well into the private cloud ecosystem so that IT staff can deliver flexibility and ease of consumption, as well as maximize the use of commodity or virtualized hardware. An SDE is now easily achievable by leveraging container technology, where Docker is one of the leaders.
Docker containers provide application portability
Docker containers “wrap up” a piece of software in a complete file system that contains everything the software needs to run: code, run-times, system tools, system libraries and other components that can be installed on a server. This guarantees that the software will always run the same, regardless of the environment in which it is running.
Docker provides true application portability and ease of consumption by alleviating the complex process of software setup and installation that often can require multiple skills across multiple hours or days. It provides OS-level abstraction without disrupting the standards on the host operating system, which makes it even more attractive.
One key point to keep in mind is that Docker is not the same as VMware. Docker provides process isolation at the operating system level, whereas VMware provides a hardware abstraction layer. Unlike VMware, Docker does not create an entire virtual operating system. Instead, the host operating system kernel can be shared across multiple Docker containers. This makes it very lightweight to deploy and faster to start than a virtual machine. There is no looking back, as container technology is being very quickly embraced as part of a hybrid solution that meets business user needs-fast!
dashDB Local: data warehousing delivered via Docker container
Coming full circle, the data warehouse is the foundation of all analytics and must be fast and agile to serve new analytics needs. Software defined environments make this easy to do – enabling key deployment of the warehousing engine in minutes as compared to hours or days.
IBM dashDB is the data warehousing technology that delivers high speed insights through in-memory computing and in-database analytics at massively parallel processing (MPP) scale. It has been available as a fully managed services on the IBM cloud. Now, dashDB Local as a is available as an early access client preview for private clouds and other software-defined infrastructures. I hope you will test this new technology and provide us valuable feedback. Learn more, then request access: ibm.biz/dashDBLocal
Mitesh Shah is the product manager for the new dashDB data warehousing solution as a software-defined environment (SDE) that can be used on private clouds and other implementations that support Docker container technology. He has broad experience around various facets of software development revolving around database and data warehousing technologies. Throughout his career, Mitesh has enjoyed a focus on helping clients address their data management and solution architecture needs.