As this year takes hold, we are beginning to see some interesting trends developing in the data centre sector. Paul Speciale, Chief Product Officer, Scality, predicts the evolutions he expects to take place in storage at the Edge, multi-cloud, Digital Transformation, data breaches and sustainability.
Object storage at the Edge will be on flash
Object storage will move into the Edge, for applications that capture large data streams from a wide variety of mobile, IoT and other connected devices. This will include event streams and logs, sensor and device data, vehicle drive data, image and video media data and more, with high data rates and high concurrency from thousands or more simultaneous data streams. These applications will be developed for cloud-native deployment and will therefore naturally embrace RESTful object style storage protocols – making object storage on flash media an optimal choice on the Edge to support this emerging class of data-centric applications.
Data storage will become massively decentralised as enterprises leverage a combination of on-premises and public cloud IT resources. This will create a need for a unified namespace and control plane to simplify data visibility and access. Moreover, corporations will use a variety of public clouds, each one selected to help solve specific business problems, thereby creating a multi-cloud data management problem. In addition, the emergence of Edge Computing will further drive decentralisation as corporations choose to deploy IT resources ‘near’ the Edge devices they manage. These trends all help to create a new and extreme ‘cloud data silos’ scenario, that can only be addressed by solutions that provide global data visibility across these distributed clouds and data centres.
Digital Transformation and multi-protocol
Multi-protocol systems will be embraced during Digital Transformation: customers transforming from legacy applications to cloud-native applications will continue to embrace RESTful protocols as their standard mechanism for accessing data storage services and systems. Systems that are multi-protocol (legacy protocols such as NFS and SMB for file access plus new RESTful APIs such as AWS S3 and Azure Blob Storage for object style access) will be adopted to help companies transition during this phase. Moreover, object storage services and systems will become a standard solution for stateful container storage.
Infrastructure application will be deployed on Kubernetes, including storage
Kubernetes will be the default platform for infrastructure deployment in the data centre. As enterprises transform and adopt cloud-native applications, the need for a standard deployment and orchestration framework for containers will increase, just as it did during the Virtual Machine (VM) wave over the course of the last two decades. Kubernetes will be that standard orchestration platform, not only for applications deployed in containers, but also for infrastructure elements built as services and microservices. This will extend to data storage and data management infrastructure deployed on Kubernetes.
Monopolies and the cloud
This year, IT teams will make the move from ‘all-cloud’ initiatives to hybrid- and multi-cloud data management solutions as they continue to recognise that to depend 100% on a single cloud provider is to empower a monopoly. Cloud providers have capitalised on lock-in and their customers see it. And this is a key reason why 53% of enterprises that had moved everything to public cloud are already repatriating some of their data (IDC). Storing data in one cloud and on-premises, (hybrid cloud infrastructure) or in multiple clouds (multi-cloud infrastructure) are both sensible, proven approaches to ensure organisations can remain in control and beat the monopoly.
Monopolies and AI
AI will compete more strenuously against….AI, fuelling monopolistic practices and reducing competitive situations (a key early example of this includes the homogenisation of air travel pricing). To be ready for what the fourth (and fifth) industrial revolution brings, the division between what requires ‘humans’ and what does not will accelerate, so we will continue to see the divvying-up of those tasks and functions that require humans, and those that AI does well. As time goes on, humans will do what requires care, creativity and artisanship; and everything else will be automated. This year will see this division of ‘labour’ accelerate.
Hackers and data breaches
New ways of identifying patients, customers and depositors will be developed this year, as the already accelerating pace of hacking and data breaches continues. There’s huge value in stored data. Until they make these changes, hospitals and medical providers, for example, will remain strong targets due to the value of the data they store: not just patient health information, but also the patient identification that goes along with it (government ID, birth date, address, etc.).
Organisations will stop unnecessary ‘rip and replace’ to reduce waste this year. When technology refresh cycles come around, many organisations are compelled by their vendors to take on full replacement of both hardware and software. This results of course, in a large amount of technology waste that gets processed, or ‘demanufactured’, (using energy and human resources) for recycling and disposal. Servers, which can contain toxic chemicals like Beryllium, Cadmium, Chromium Hexavalent, Lead, Mercury, BFRs and more should be used until they ‘break’, not just until a vendor wants to sell its customers a new round. It’s time for that ‘rip and replace’ culture to reform.
Storage is a great example of a place where that reform can happen. Software-defined storage, with ultra-strong data resiliency schemes, is a great way to take data servers to their true end-of-life, rather than replacing at refresh time. Adopting a robust software-defined storage solution that can scale infinitely using standard servers – and that is ‘generation-agnostic’ so it can accommodate the steady evolution of hardware over time – is a good way to reduce waste.
What is ultra-strong data resiliency in storage? When storage is spread across a collection of storage servers, those nodes can share a highly parallel distributed logic that has no single point of failure – it doesn’t not depend on any single component. This kind of system is resilient, self-healing, adaptive, location aware and constantly renewing. In that kind of scenario, you can wait for hardware to fail before you replace it, because it won’t affect data availability – server outages are not a problem. Even better, some resiliency models can lose a full data centre – or a data centre plus a server. Eventually, servers will fail. When that happens, their metal, plastics and glass can be recycled; and toxic components disposed of safely. Why accelerate and increase the processing, waste and energy when using the systems until they must be replaced is a solid option?