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Aziro (formerly MSys Technologies) 2019 Tech Predictions: Smart Storage, Cloud’s Bull Run, Ubiquitous DevOps, and Glass-Box AI

2019 brings us to the second-last leg of this decade. From the last few years, IT professionals have been propagating rhetoric. They state that the technology landscape is seeing a revolutionary change. But, most of the “REVOLUTIONARY” changes, has, over the time lost their gullibility. Thanks to the awe-inspiring technologies like AI, Robotics, and upcoming 5G networks most tech pundits consider this decade to be a game changer in the technology sector.As we make headway into 2019, the internet is bombarded with numerous tech prophecies. Aziro (formerly MSys Technologies) presents to you the 2019 tech predictions based on our Storage, Cloud, DevOps and digital transformation expertise.1. Software Defined Storage (SDS)Definitely, 2019 looks promising for Software Defined Storage. It’ll be driven by changes in Autonomous Storage, Object Storage, Self-Managed DRaaS and NVMes. But, SDS will also be required to push the envelope to acclimatize and evolve. Let’s understand why so.1.1 Autonomous Storage to Garner MomentumBacked by users’ demand, we’ll witness the growth of self-healing storage in 2019. Here, Artificial Intelligence powered by intelligent algorithms will play a pivotal role. Consequently, companies will strive to ensure uninterrupted application performance, round the clock.1.2 Self-Managed Disaster Recovery as a Service (DRaaS) will be ProminentSelf-Managed DRaaS reduces human interference and proactively recovers business-critical data. It then duplicates the data in the Cloud. This brings relief during an unforeseen event. Ultimately, it cuts costs. In 2019, this’ll strike chords with enterprises, globally, and we’ll witness DRaaS gaining prominence.1.3 The Pendulum will Swing Back to Object Storage as a Service (STaaS)Object Storage makes a perfect case for cost-effective storage. Its flat structure creates a scale-out architecture and induces Cloud compatibility. It also assigns unique Metadata and ID for each object within storage. This accelerates the data retrieval and recovery process. Thus, in 2019, we expect companies to embrace Object Storage to support their Big data needs.1.4 NMVes Adoption to Register TractionIn 2019, Software Defined Storage will accelerate the adoption rate of NVMes. It rubs off glitches associated with traditional storage to ensure smooth data migration while adopting NVMes. With SDS, enterprises need not worry about the ‘Rip and Replace’ hardware procedure. We’ll see vendors design storage platforms that append to NVMes protocol. For 2019, NMVes growth will mostly be led by FC-NVME and NVMe-oF.2. Hyperconverged Infrastructure (HCI)In 2019, HCI will remain the trump card to create a multi-layer infrastructure with centralized management. We’ll see more companies utilize HCI to deploy applications quickly. This’ll circle around a policy-based and data-centric architecture.3. Hybridconverged Infrastructure will Mark its FootprintHybridconverged Infrastructure (HCI.2) comes with all the features of its big brother – Hyperconverged Infrastructure (HCI.1). But, one extended functionality makes the latter smarter. Unlike HCI.1, it allows connecting with an external host. This’ll help HCI.2 mark its footprint in 2019.4. VirtualizationIn 2019, Virtualization’s growth will be centered around Software Defined Data Centers and Containers.4.1 ContainersContainer technology is ace in the hole to deliver promises of multi-cloud – cost efficacy, operational simplicity, and team productivity. Per IDC, 76 percent of users’ leverage containers for mission-critical applications.4.1.1 Persistent Storage will be a Key ConcernIn 2019, Containers’ users will envision a cloud-ready persistent storage platform with flash arrays. They’ll expect their storage service providers to implement synchronous mirroring, CDP – continuous data protection and auto-tiering.4.1.2 Kubernetes Explosion is ImminentThe upcoming Kubernetes version is rumored to include a pre-defined configuration template. If true, it’ll enable an easier Kubernetes deployment and use. This year, we are also expecting a higher number of Kubernetes and containers synchronization. This’ll make Kubernetes’ security a burgeoning concern. So, in 2019, we should expect stringent security protocols around Kubernetes deployment. It can be multi-step authentication or encryption at the cluster level.4.1.3 Istio to Ease Kubernetes Deployment HeadacheIstio is an open source service mesh. It addresses the Microservices’ application deployment challenges like failure recovery, load balancing, rate limiting, A/B testing, and canary testing. In 2019, companies might combine Istio and Kubernetes. This can facilitate a smooth Container orchestration, resulting in an effortless application and data migration.4.2 Software Defined Data CentersMore companies will embark on their journey to Multi-Cloud and Hybrid-Cloud. They’ll expect a seamless migration of existing applications to a heterogeneous Cloud environment. As a result, SDDC will undergo a strategic bent to accommodate the new Cloud requirements.In 2019, companies will start cobbling DevOps and SDDC. The pursuit of DevOps in SDDC will be to instigate a revamp of COBIT and ITIL practice. Frankly, without wielding DevOps, cloud-based SDDC will remain in a vacuum.5. DevOpsIn 2019, companies will implement a programmatic DevOps approach to accelerate the development and deployment of software products. Per this survey, DevOps enabled 46x code deployment. It also skyrocketed the deploy lead time by 2556x. This year, AI/ML, Automation, and FaaS will orchestrate changes to DevOps.5.1 DevOps Practice Will Experience a Spur with AI/MLIn 2019, AI/ML centric applications will experience an upsurge. Data science teams will leverage DevOps to unify complex operations across the application lifecycle. They’ll also look to automate the workflow pipeline – to rebuild, retest and redeploy, concurrently.5.2 DevOps will Add Value to Functions as a Service (FaaS)Functions as a Service aims to achieve serverless architecture. It leads to a hassle-free application development without perturbing companies to handle the monolithic REST server. It is like a panacea moment for developers.Hitherto, FaaS hasn’t achieved a full-fledged status. Although FaaS is inherently scalable, selecting wrong user cases will increase the bills. Thus, in 2019, we’ll see companies leveraging DevOps to fathom productive user cases and bring down costs drastically.5.3 Automation will be the Mainstream in DevOpsManual DevOps is time-consuming, less efficient, and error-prone. As a result, in 2019, CI/CD automation will become central in the DevOps practice. Consequently, Infrastructure as a Code to be in the driving seat.6. Cloud’s Bull Run to ContinueIn 2019, organizations will reimagine the use of Cloud. There will be a new class of ‘born-in-cloud’ start-ups, that will extract more value by intelligent Cloud operations. This will be centered around Multi-Cloud, Cloud Interoperability, and High Performance Computing. More companies will look to establish a Cloud Center of Excellence (CoE). Per RightScale survey, 57 percent of enterprises already have a Cloud Center of Excellence.6.1 Companies will Drift from “One-Cloud Approach.”In 2018, companies realized that having a ‘One-Cloud Approach’ encumbers their competitiveness. In 2019, Cloud leadership teams will bask upon the Hybrid-Cloud Architecture. Hybrid-Cloud will be the new normal within Cloud Computing in 2019.6.2 Cloud Interoperability will be a Major ConcernIn 2019, companies will start addressing the issues of interoperability by standardizing Cloud architecture. The use of the Application Programming Interface (APIs) will also accelerate. APIs will be the key to instill the capability of language neutrality, which augments system portability.6.3 High Performance Computing (HPC) will Get its Place on CloudIndustries such as Finance, Deep Learning, Semiconductors or Genomics are facing the brunt of competition. They’ll envision to deliver high-end compute-intensive applications with high performance. To entice such industries, Cloud providers will start imparting HPC capabilities in their platform. We’ll also witness large scale automation in Cloud.7. Artificial IntelligenceFor 2019 AI/ML will come out of the research and development model to be widely implemented in organizations. Customer engagements, infrastructure optimization, and Glass-Box AI, will be in the forefront.7.1 AI to Revive Customer EngagementsBusinesses (startups or enterprise) will leverage AI/ML to enable a rich end-user experience. Per Adobe, enterprises using AI will more than double in 2019. Tech and non-tech companies, alike, will strive to offer personalized services leveraging Natural Language Processing. The focus will remain to create a cognitive customer persona to generate tangible business impacts.7.2 AI for Infrastructure OptimizationIn 2019, there will a spur in the development of AI embedded monitoring tools. This’ll help companies to create a nimble infrastructure to respond to the changing workload. With such AI-driven machines, they’ll aim to cut down the infrastructure latency, infuse robustness in applications, enhance performances, and amplify outputs.7.3 Glass-Box AI will be crucial in Retail, Finance, and HealthcareThis is where Explainable AI will play its role. Glass-Box AI will create key customers’ insights with underlying methods, errors or biases. In this way, retailers don’t necessarily follow every suggestion. They can sort out responses that fit rights in that present scenario. The bottom-line will be to avoid customer altercations and bring out fairness in the process.

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Why Hyper-Converged is best solution for Storage, Networking, Virtualization?

The storage industry is evolving, albeit with an increasing need of ease of managing datacentres. With the advent of hyper-converged solutions, there has been a significant advantage in running datacentres. In this article, we will discuss datacentre related scenarios which can be circumvented with a hyper-converged solution. Scenario 1: The need to build a data centre which requires storage, networking and virtualization. Scenario 2: System failures in the storage system; considering that for the storage industry, triaging with failures is very tedious process. Solution The efficient solution to the above problem is to have a hyper-converged solution which can be useful to provide a one stop resolution to your storage, networking and virtualization requirements. Let’s discuss this in detail. Hyper-converged solutions are sold as a single deck box having in-built storage, networking and virtualization solutions. So considering the first scenario, where you want to build a datacentre automation system, you need to rely on other vendors for solutions. Hyper-converged is a highly scalable platform that gives you everything in a single deck which seamlessly integrates your SAN, servers and virtualization software. Considering the second scenario of system failure, you may not necessarily be aware of the root cause, and triaging failure usually needs the involvement of vendors. Instead, if you opt for a hyper-converged solution, you get to know about the root-cause of any failure, as hyper-converged infrastructures provide single page application that offer easy fault detection. Cost optimization, data optimization, data rebalancing and high availability are also some key features which are provided by Hyper-Converged Solutions. Most hyper-converged solutions provide 24*7 data availability, greatly reducing downtime and data-loss possibilities. Hence most hyper-converged solutions provide zero RPO (Recovery Point Objective) which corresponds to no data loss and zero RTO (Recovery Time Objective) which corresponds to no downtime. In the storage industry, data protection is very crucial, and hyper converged solutions provide efficient answers for them. Also disaster recovery and data protection is a very important aspect for storage systems. With the help of hyper-converged solutions, disaster recovery and data protection are managed very well. Hyper-converged solutions come with bare metal along with pre-installed operating systems which provide ease of management and avoid any compatibility issues. Aziro (formerly MSys Technologies) specializes in Storage, Networking, Virtualization and Networking and is a global leader in providing services to build hyper converged solutions. Aziro (formerly MSys Technologies) can play an important role in providing the best in class solutions to builds hyper-converged solution for your organisation.

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How to do Rapid VM Backup and Clone by Using Native Storage APIs?

IntroductionVMware supports native snapshot and clone technology at VM level where users can take snapshots or clones for a VM backup and fast VM provisioning by using the clone. In the vSphere UI, user can right click on VM and initiate a snapshot or clone operations.There are also command line options available to initiate the snapshot of a VM. VMware provides option to revert to given snapshot through “Snapshot Manager” in case of any data corruption at VM level or if the user intentionally wants to revert VM to particular snapshot.However, considering the technologies stack, this is the best offering by VMware, though performance degrades as we increase the size of VMs which eventually happens in enterprise DC, caveats, it can longer be instantaneous. How do we make VM backup or clone even faster in enterprise Datacenter deployment?It is a well-known fact that snapshot and clone features are also offered by storage vendors though the granularity is at block or at file level depending on type of storage solution offerings. By leveraging the storage snapshot and clone technologies for a VM backup, it is possible to increase the VM backup and clone performance.Please refer to the “VMware Infrastructure” diagram below:Some limitations of existing snapshot or clone offerings are:Hypervisor LayerEnterprise Server LayerEnterprise Network LayerEnterprise Storage LayerAny snapshot or clone offering by hypervisors is at top of the technological stack, i.e. at Hypervisor Layer. This reduces the performance since each i/o needs to traverse the technology stack before committing to disk. What if we could bypass some layers of the stack or minimize the above technological stack? This could be achieved by taking advantage of the storage vendor’s snapshot and clone technologies.DetailsStorage vendors offer their snapshot and clone technologies solution and they are made available to end user via REST/SOAP SDKs. On leveraging the storage APIs, it is possible to take the snapshot/clone of a volume. Since it is volume level backup, the respective VMware APIs and Storage APIs could be used to amalgamate the VM, datastore and its associated volume, in order to achieve VM level backup or clone.If we consider VMware technologies, VMs are made up of files *.vmdk,*.vmx , *.vswap etc and gets stored in data stores. Datastore is directly mapped to a Volume.Using VMware APIs, you can get the file structure of VMs and its storage details like volume properties, host properties, storage details etc. Once this information is available, invoke native Storage APIs and initiate a snapshot of a volume. You then need to maintain the relationship between VM and volume snapshot and present this association to user.Similarly, for clone, take the clone of a volume and present its VM clone to vSphere.The above solution could be offered as:Command line interface (CLI)VMware UI PluginDesignVMware exposes a vSphere API as a web service, running on VMware vSphere server systems. The API provides access to vSphere management components that can be used to manage and control life-cycle operations of virtual machines. The APIs are made available via VMware vSphere Web Services SDK.Storage vendors also expose their APIs for snapshot and clone operations and could be used for building any integration solutions. Thus by leveraging the VMware APIs and storage vendor’s APIs, the following solution is developed:Plugin UIThis is a user visible component and sits inside the vSphere GUI from where user can list all the VMs and also request any snapshot or clone. Any user driven request comes to Plugin Server via REST APIs. It offers the following features to end user:List view of VMsDrop down menu option for snapshot and clone of a VM.List view of snapshots of a VMPlugin ServerThis is a REST based server application which acts as client as well as server. It takes request from Plugin UI and acts as client for VMware vCenter Server and Storage Arrays. Primary responsibilities of this application is to process the Plugin UI request and invoke VMware vCenter Server APIs to get the necessary VM details, if the plugin server requests to take snapshot or clone, it further invokes Storage APIs and take snapshot or clone at volume level. The relationship between storage volumes, snapshot and VM is locally stored.ConclusionThe performance of a snapshot or a clone of a VM is significantly increased due to the fact that it has not only minimized the technological stack but also by using the best native snapshot or clone technology offered by storage vendors. The intention here is to give fair perspective of various redundancy features and technology solutions available which could be used in a manner to achieve desired end user performance results.

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Federated Data Services through Storage Virtualization

When one talks about virtualization, the immediate thought that comes to mind is about server/ host virtualization otherwise understood from the virtualization offerings from the likes of VMware, Citrix, Microsoft, etc. However, there is a not-so-explored & not much known data center technology that can contribute significantly to a modern (future) data center. When we talk of real time cloud application deployment (access anywhere) with enterprise workloads, there should be something more that the Infrastructure should support, to enable effective consolidation and management of storage/ host infrastructure across a data center.This article aims to introduce Storage Virtualization (SV) as a technology and the role this can play in enabling federated data services use cases. Aziro (formerly MSys Technologies) also has been a leading virtualization services provider working on the same technology.The Need for Storage VirtualizationTraditional data centers are largely FC-SAN based, where monoliths of huge enterprise storage arrays are hosted, deployed, configured, and managed but with niche expertise. Most of mission critical applications of the world run on such data centers (DC). EMC (Dell EMC), NetApp, IBM, HP (HPE), etc. are a few major players in this arena. The appliances these companies have built are tested and proven on the field for the reliability, efficiency and availability across various workloads.However, the major constraint of an IT investor of the modern times is related to the DC/ DR manageability and upgradability, more in the context of upcoming products with alternate technologies such as hyper converged storage; than defy the storage array based implementations. With vendor lock-in’s, rigid & propriety storage management API’s/ UI’s, it is a cumbersome process to think of an idea of having heterogeneous storage arrays with various vendors in a DC. Also, it poses the challenge of having skilled administrators who are well-versed on all different product implementations and management.Before it was a hyper-converged storage, the storage majors ventured to innovate an idea that could possibly solve this problem. This is how Storage Virtualization was born – where a way was envisaged to have heterogeneous storage arrays in a DC but still could seamlessly migrate data/ applications between them through a unified management interface. Not just that, the thrust was to see a bigger picture of application continuity to data center business continuity scaling up the scope of the high availability picture.What is Storage Virtualization?Storage virtualization (SV) is the pooling of physical storage from multiple storage arrays or appliances into what appears to be a single storage appliance that can be managed from a central console/ unified storage management application. Storage Virtualization could be an appliance hosted between the host and the target storage or could be just a software VM.Some popular SV SAN solutions available in the market are IBM SVC, EMC VPlex, NetApp V-series, etc.Use case & Implementation – How does it work?Let’s look at a practical data center use case of a heterogeneous data center, where there are 9 enterprise storage arrays, say 2 nos. of Dell EMC VMAX, 1 nos. of HPE 3PAR, 1 nos. of IBM V7000 & 5 nos. of EMC Clariion CX300. Consider that all legacy applications are currently hosted in EMC Clariion array and all the mission critical applications are hosted independently in EMC/ HPE/ IBM arrays. Let’s assume that the total data center storage requirements are already met and with the current infrastructure, it can easily support the requirement for the next 5 years. Consider, just between HPE, EMC and IBM arrays, we have sufficient storage space to accommodate the legacy applications as well. However, there isn’t a way yet to manage such a migration or a consolidated management of all different storage devices.Now, let’s look at some of the use case requirements/ consolidation challenges that a storage consultant should solve:Fully phase out Legacy CX300 Arrays and migrate all the legacy applications to one of enterprise arrays say, IBM V7000, but with minimum down time.Setting up a new data center, DC2 about 15 miles away and moving 2 of the enterprise arrays, say 2* EMC VMAX arrays to the new site and host this as an active-active data center/ disaster recovery site for former DC (DC1).The current site, DC1 should become DR site for the new DC, DC2 however should actively engage I/O and business should continue. (Synchronous use case)Management overhead of using products from 3 different vendors should reduce and should be simplified.The entire cycle of change should happen with minimum downtime except for the case of physical movement/ configuration of VMAX arrays to the new site.The architecture should be scalable for data requirements of next 5 years in such a way that new storage arrays from existing or new vendors can be added with no downtime/ disruption.The DC & DR sites are mutually responsive to each other during an unforeseen disaster and are highly available.Solution IllustrationThis is a classic case for Storage Virtualization Solution. An SV solution is typically an appliance with software & intelligence that is sandwiched between the initiator (hosts) and the target (heterogeneous storage arrays). For the initiator, the SV is the target and for the target, the SV becomes the initiator. All the storage disks from the target (with/ without data) appear as a bunch of unclaimed volumes in the SV. As far as hosts are concerned, they appear to the SV as unmapped initiators unregistered. Storage- Initiator groups are created (registered) in the SV which can be modified/ changed on the fly giving flexible host migration at the time of server disaster.There are different SV solutions available from vendors such as EMC VPlex that can help cases of local DC migration as well as migration between sites / DC’s. Let’s see how the solution unfolds to our use case requirements.Storage from both legacy array and the new array once configured to access the hosts through an SV solution, the storage disks/ LUNs appear as pool of storage at the DV interface. The SV solutions encapsulates the storage so that data migration between both the arrays can happen non-disruptively. Vendor1- Vendor2 replications are challenging and often disruptive.SV solutions are configured in a fully HA configuration providing fault tolerance at every level (device, storage, array, switch, etc.).Across site SV solution such as EMC VPlex Metro can perform a site-site data mirroring (synchronous) that too which both the sites are fully in active-active IO configuration.The entire configuration done through HA Switches provides option to scale to add existing/ new vendor storage arrays as well new Hosts/ Initiators with zero down time.The entire solution be it at local DC level or multi-site would be fully manageable through a common management UI/ Interface reducing the dependence on skilled storage administrators who are vendor specific.A SV solution consolidates the entire storage and host infrastructure to a common platform simplifying the deployment and management. Also, this sets a new dimension to hyper-converged storage infrastructure to be scaled across sites.A SV solution is agnostic, to the host and storage giving diversity of deployment options. For e.g. various host hardware, operating systems, etc.All the features of a storage array are complimented to its full potential along with superior consolidation across Storage/ sites with additional availability/ reliability features.Solutions like VMware vMotion does help in site- site migration, however, an SV solution provides the infrastructure support for that happen at the storage device level that too across sites.ConclusionIt’s just a matter of time, when we will see more efficiently packaged & effectively deployed SV solutions. Perhaps, it could be called software defined SV solution that can be hosted on a VM instead of an appliance. Storage consolidation is a persistent problem, more so in the modern days, due to the diversity of Sever Virtualization/ SDS Solutions, varieties of Backup and recovery applications/ options available to an IT Administrator. There should be a point where DC should become truly converged where best of every vendor can co-exist in its own space complimenting each other. However, there is a business problem to that wish. For now, we can only explore more on what SV can offer us.

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Serving the Modern-Day Data With Software-Defined Storage

Storage is Getting Smarter Our civilization’s been veering towards intelligence all this time. And our storage infrastructures are keeping up by developing intelligence of their own. The Dynamic RAMs, GPUs, Cloud Infrastructures, Data Warehouses, etc., are all working towards predicting failures, withstanding disasters, pushing performance barriers, and optimizing costs, instead of just storing huge chunks of data. Per Gartner, more than 33% of large organizations are set to allow their analysts to use decision modeling and other decision intelligence by 2023. Smartening our storage capacities opened up some unfathomable realms for our business landscapes. And it won’t be wise to stop now. We are evolving our storage infrastructures to meet the scalability, performance, and intelligence requirements of the modern world. The same is reflected by the report by technavio claiming 35% growth in the software-defined storage market in North America alone. Our storage needs to step up to identify meaningful patterns and eliminate road blocking anomalies. Therefore, it makes sense to zoom in into the world of software-defined storage and see how it is helping to optimize the system. This blog will take a better look at Software-Defined Storage (SDS) and its role in dealing with modern day data requirements like Automation, Virtualization, and Transparency. Software-Defined Storage: The functional ally to Clouds We want our data blocks to be squeezed down to the last bit of intelligence they can cough out and then a little more. The more intelligent our systems and processes will be lesser will be our operational costs, process latencies, and workload complexities. Our IoT systems will be more coherent, our customer experience innovations will be more methodical, and our DevOps pipelines will be more fuel-efficient. We need storage resources to proactively identify process bottlenecks, analyze data, minimize human intervention, and secure crucial data from external and internal anomalies. And this is where Software-Defined Storage (SDS) fits in the picture. The prime purpose of SDS, as a storage architecture, is to present a functional allyship with clouds infrastructure. By separating the storage software from hardware, software-defined storage allows the storage architecture to have just the flexibility that can help full exploitation of clouds. Moreover, factors like the uptake of 5G, rising CX complexities, and advanced technologies – all serve as the fuel to drive for SDS to be accepted more immediately and efficiently. Be it public, private, or even hybrid cloud architecture, SDS implementation comes really handy against the need for centralized management. The data objects and the storage resources trusted by the on-premises storage can be easily extended to the cloud using SDS. Not only does SDS ensure robust data management between on-premises and cloud storage, it also strengthens disaster recovery, data backup, DevOps environments, storage efficiency, and data migration processes. Tightening the corners for Automation Software-Defined Storage has its core utility vested in its independence to hardware. This is also one of the prime reasons that it is greatly compatible with the cloud. This builds the case for SDS to qualify for one of the prime motivators in the contemporary IT industry – Automation. Automation has become a prime sustainability factor. It can only be deemed unfortunate if an IT services organization doesn’t have an active DevOps pipeline (if not several) for their product and services development and deployment. To add to that, Gartner suggests that by 2023, 40% of product and platform teams will have employed AIOps to support their DevOps pipeline to reduce unplanned downtime by 20%. Storage Programmability Storage policies and resource management can be more readily programmed for SDS as opposed to hardware dependent architectures. Abstracted storage management, including request controls, storage distribution, etc., makes it easier for the storage request to be manipulated for storing data based on its utility, usage frequency, size, and other useful metrics. Moreover, SDS controls also dictate storage access and storage networks, making them crucial for automating security and access control policies. Therefore, with SDS in place, automation is smoother, faster, and more sensible for DevOps pipelines and business intelligence. Resource Flexibility The independence from underlying hardware allows SDS to be easily communicated with. APIs can be customized to manage, request, manipulate and maintain the data. Not only does it make the data provisioning more flexible, it also limits the need to access the storage directly. Moreover, SDS APIs make it easier for it to work with tools like Kubernetes to access the scope of resource management over the cloud environment. Thus, storage programmability and resource flexibility allow Software-defined storage to internalize automation within the storage architecture, as well as secure, provide data for external automation tools. Furthermore, workloads based out of Cloud Native are more adaptive and comfortable with SDS than other hardware specific storage software. This makes SDS more desirable for enterprise-level automation products and services. Virtualization: Replacing ‘where’ with ‘how’ Virtualization belongs to the ancestry that led to modern day cloud computing. It doesn’t come as a surprise when Global Industry Analysts (GIA) predict in their report that the global virtualization software market would exceed $149 billion by 2026. With the abstraction of hardware infrastructure, businesses across industries expect data to be more easily accessible as well. Therefore, Software Defined Storage needs to have an ace in the hole, and it does. Software defined storage doesn’t virtualize the storage infrastructure itself, rather the storage services. It provides a virtualized data path for data blocks, objects, and files. These virtual data paths provide the interface for the application expecting to access them. Therefore, the abstracted services are separated from the underlying hardware making the data transactions smoother in terms of speed, compliance, and also scalability. In fact, SDS can prepare the data for hyper scalable applications making it the best choice for cloud-native, AI-based solutions. Monitoring the Progress with Transparency What the pandemic did to the IT world wasn’t unforeseen, just really, really hurried. For the first time, modern businesses were actually pushed to test the feasibility of remote connectivity. As soon as that happened, the prime concern for – Data Monitoring. Studies show that the average cost for a data breach in the US itself is up to $7.9 million. Thus, it is important that there is transparency in data transactions and that the storage services are up for it. Data Transparency would ensure reliable monitoring curbing the major causes of data corruption. With Software-defined storage, it is easy to program logging and monitoring of data access and transaction through the interfaces and APIs. SDS allows uninterrupted monitoring of the storage resources and integrates with automated monitoring tools that can pick the metric you want to be monitored. SDS can also be programmed to extend logging to the server requests to help with access audits as and when required. Similarly, API calls are logged to keep track of the cloud storage APIs called. With the operational data being – automation compatible, scalable through virtualization, and transparent in its transactions – it would be all ready to serve the modern business ambitions of IoT projects, CX Research and Development, AI/ML Engines, and more. Therefore SDS has a lot of futuristic aspirations; let us take a look at some in the next section. Final Thoughts Modern-day data needs are governed by speed, ease of use, and proactive offerings. Responsible for storing and protecting data with their nuanced resource, storage infrastructure cannot bail out on these needs. Software-Defined storage emerges as a by-product from this sense of responsibility. It abstracts the services to make them independent of the underlying infrastructure. It is programmable, making storage automation friendly. And it is easy to monitor. For a civilization aspiring better intelligence, Software-defined storage seems like a step in the right direction.

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