5 Storage and Data Management Trends to Watch
Like nearly every area of technology, storage and data management are evolving at lightning speed. New developments in machine learning, NVMe, containerization, and more are poised to transform the way enterprises interact with data.
The following are five new trends in data storage and management, including challenges and opportunities to watch in the coming months:
1. AI and machine learning to power storage analytics. Artificial intelligence (AI) and machine learning (ML) are already commonly used to detect malicious software that may be lurking in storage. But now new use cases are emerging, such as using AI analytics to optimize storage tiers, optimize backup schedules, predict future demand storage, or to flag potential compliance threats.
2. Edging toward even more efficient flash arrays: The fast, efficient capabilities of non-volatile memory express (NVMe) gained traction in 2018, accelerating data transfers between enterprise and client systems, and solid-state drives (SSDs) over a computer's high-speed peripheral component interconnect express (PCIe) bus. Now, storage technology experts are looking to leverage NVMe over Fabrics (NVMe-oF) technology to connect to storage over network ‘fabrics’ like ethernet, fibre channel, and infiniband to enable faster transfers of data in shared storage.
3. The advent of composable infrastructure. Converged and hyper-converged infrastructure remain invaluable for many organizations seeking agility and efficiency. Composable infrastructure is an emerging convergence architecture that eliminates the need for workload‐specific environments and provides resources that can be dynamically combined to meet the unique needs of any application. Compute, storage, and networking resources are abstracted from their physical locations and managed by software through a web-based application. That fluidity makes provisioning even more rapid, ultimately optimizing application performance across the business. A trusted consultant can help you determine if this is a worthy pursuit for your enterprise.
4. Data mobility in the hybrid cloud will remain a challenge. While cloud vendors like Google, Azure, and Amazon don’t charge you for uploading data into the cloud, they do charge for data downloads. Thus, every gigabyte of data you store in the cloud can potentially become costly. That’s why organizations leverage cloud services for application development, but keep the application data on-premise. The key to overcoming this bulky, often pricey process, is understanding where each type of your enterprise data should live. A cloud assessment can help you understand the larger cost structure of moving apps, images, and other data to and from the cloud.
5. Revamping networking and security to support containers. Containerization is becoming foundational for standardizing software deployments across multiple machines and platforms. Once in place, containers can be simpler to manage than virtual machines. But, just as configuring networking for virtual machines is a challenge, it takes careful planning and deep understanding of products and your own data usage to replace traditional infrastructure with containers. CIOs and IT leaders are also pursuing new methods of securing cloud-deployed containers that will enable organizations to more effectively track and manage security policies on each container. One key way forward: educate yourself on the opportunity, and the challenges—Burwood offers virtual workshops on containers and Kubernetes.
Keeping an eye on the data storage technology landscape can help your enterprise stay ahead, but it’s also a complicated story with many changing parts. It’s wise to consult with expert service providers before investing in any promising new solution.
Stay tuned for the next topic in this series: a deeper dive into the great world of AI and machine learning in storage analytics.
* This post was developed with funding from Hewlett Packard Enterprise (HPE).