For Part 2, we’re going to focus on the practical benefits that your organization can attain by integrating SDN into your network architecture.

What are the most common advantages of using SDN?

In their eponymous article “7 Advantages of Software Defined Networking,” the author notes that SDN’s biggest promise is to “centralize and simplify control of enterprise network management”. Other advantages that SDN offers include the following examples:

• Ability to program traffic
• Increased agility
• Ability to create policy driven network supervision
• Ability to implement network automation
• Ability for network to scale as needed

The article goes on to note that SDN “creates a framework to support more data-intensive applications like big data and virtualization”. SDN helps organizations use virtual machines (VMs) and direct network traffic, which is one of the factors driving virtualization adoption in today’s organizations.

In addition to the aforementioned advantages, here are several of the advantages that SDN has over other types of networking:

Unifying cloud resources and shaping and controlling data traffic

By using SDN to abstract cloud resources, SDN helps simplify the process of unifying cloud resources. This process also helps SDN controllers to manage the networking components that make up the vast data centre platforms.

One of the primary advantages of SDN is being able to manipulate data traffic. The ability to direct and automate this traffic allows for easier implementation of quality of services (QoS) for multimedia transmissions and Voice over Internet Protocol (VoIP or Voice over IP). This ability allows SDN tends to produce better user experiences with benefits like improved network responsiveness and the ability to stream higher quality videos.

Centralized network provisioning

SDN offers the ability to program traffic and lets you provision resources from a centralized, software-based control plane. This centralized view helps administrators monitor the entire network and direct enterprise management. It helps accelerate service delivery and provides greater provisioning agility for physical network devices and VMs.

Scalable network management

In an effort to meet the growing needs of today’s organizations, today’s networks must establish new applications and virtual machines as needed. SDN supports both physical and virtual switches and network devices and provides application programming interfaces (API) for enterprises looking to create their own single, central management console for managing physical and virtual devices.

Network security

Centralized security is one of the biggest advantages that SDN offers. Virtual machines entering and leaving a network as components of physical systems creates a network security challenge: how can SDNs continue to use virtual machines as a part of their systems along with employees’ BYOD while applying firewall, content filtering and other similar cybersecurity policies and practices?

The SDN Controller helps answer this question by providing a centralized control point for continuously distributing information to your organization. By consolidating the centralized security control into the SDN Controller or a similar encapsulation, it increases the network’s cyber resilience, helping the SDN to better manage the organization’s security.

Cost-saving

There are a number of benefits that SDN offers which can help your organization reduce their operational expenses. These benefits include the following examples:

• increasing administrative efficiency
• streamlining server utilization
• improving virtualization control

SDN can also help your organization save on administrative costs because it helps centralize and automate routine network administrative functions that would otherwise require network administrators to perform.

SDN also makes optimizing commoditized hardware easier, allowing hardware to be repurposed by the SDN controller. “Less expensive hardware can be deployed to greater effect since new devices essentially become “white box” switches with all the intelligence centered at the SDN controller”.

Ready to take the next step? Schedule a consultation with an Software-defined networking (SDN) expert.

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

The post Network Services SDN Part 2: What are the benefits of software-defined networking? appeared first on IT Biz Advisor.

Techopedia defines SDN as a “computer network architecture [with] its main distinguishing factor [being] the separation of the data plane from the control plane in routers and switches”. For SDN, the control is incorporated into the software and decoupled from the hardware. In terms of OpenFlow, one of the most popular specifications for SDN, or similar SDN architecture, the control plane is incorporated using software from the servers and is incorporated separately from networking equipment. Opposite the control plane, the data plane is incorporated within the network hardware.

SDN uses open application programming interfaces (APIs) to support “programmatic management, control, and optimization of network resources”. When SDN decouples the network configuration and traffic and separates them from their hardware infrastructure, the decoupling creates network control. OpenFlow and other open protocols can “apply globally aware software control at the edge of the network to access network switches and routers that typically use closed and proprietary firmware”.

SDN versus traditional networking

Techopedia argues that SDN is best understood when compared with traditional networking and how traditional networking uses data packets. For traditional networking, data packets are directed from a switch or router by firmware that instructs the hardware on where the traffic loads need to go and on what path the traffic must travel to get there. Although advanced smart switches with application-specific integrated circuits (ASIC) can recognize different data packet types and treat them differently, with traditional networking most packets are treated identically.

Alternatively, SDN “decouples the control from the networking hardware’s firmware and puts it in the hands of the network administrator”. The network admin uses a central control console to direct the network traffic without altering the switches’ settings. Network admins have the flexibility to alter a network’s rules or prioritization, or even block specific packets. Techopedia notes that “SDN [is] very important for cloud computing [because it uses] multi-tenant architecture [and] allows for a more efficient and flexible control of traffic loads”.

Because it can use cheaper commodity switches and continue to provide better traffic control than traditional networking, SDN is often considered a less costly alternative to traditional networking. Network administrators and engineers “can support switching fabrics across hardware from different vendors and models [and] integrate switches with ASICs and those without”.

Ready to take the next step? Schedule a consultation with an Software-defined networking (SDN) expert.

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

The post Network Services SDN Part 1: What is software-defined networking? appeared first on IT Biz Advisor.

While the headlines have been alarming, overall industry trends are mixed. According to a recent report by the Ponemon Institute, the average cost of a data breach dropped by about 10 percent to $3.62 million in 2017. This is most likely tied to a reduction in the cost per record stolen, which declined from $158 in 2016 to $141 in 2017. However, the average size of data breaches rose 1.8 percent to more than 24,000 records.

Clearly, this is not the time for enterprises to neglect network security. With the rapid expansion of the cloud, followed by what is likely to be an equally rapid move to the Internet of Things, wide-area infrastructure is in need of more flexible and robust protection. One of the most significant enhancements in this field is the advent of the software-defined wide-area network (SD-WAN). By abstracting regional connectivity on top of underlying hardware, enterprises can experience a number of benefits over traditional hardware-centric architectures. SD-WAN equips enterprises to:

1. Centralize network security

SD-WAN gives enterprises a single control plane to oversee all networks, including data center, multiprotocol label switching and WAN. This strategy will be crucial as data migrates to multiple clouds and becomes subject to multiple security regimes. With a single view of all network operations, the enterprise can ensure that security is fully orchestrated across the entire distributed data ecosystem.

2. Reduce attack vectors

By establishing a single cohesive security environment, businesses can prevent any holes in the distributed network infrastructure from being exploited. As infrastructure becomes more diverse, the chance of key vulnerabilities falling through the cracks increases. Enterprises can improve performance and bolster security confidence by establishing the control hub as the only available attack point.

Simplify and automate your network with managed services that enhance availability and optimize cost

3. Streamline upgrades

But is the control hub inherently more secure than a distributed architecture? It is if security features like malware protection, antivirus and identity management are managed as services. Organizations can receive automated updates and patching, which can then be pushed over the entire network environment without complex manual integration procedures. This enables the rapid deployment of cutting-edge technologies like artificial intelligence and machine learning, which are becoming vital tools in the fight against increasingly sophisticated attacks.

4. Reduce provider dependencies

The SD-WAN puts the enterprise back in control of its network infrastructure. Relying on third-party vendor solutions has traditionally posed a challenge for businesses, but this is nothing compared to coordinating security among various resource providers, network carriers and related suppliers. Most organizations build security to protect their own assets, which in turn extends protection to their customers.

5. Optimize network security

By investing in SD-WAN, enterprises can optimize security for a wide variety of applications, data sets and use cases. Web applications may require different protections than a back-office function. With an abstract network architecture, enterprises can apply security and other policies individually, ensuring optimal performance regardless of where data travels.

By combining SD-WAN technology with a network peering architecture, the enterprise can essentially construct a wide-area intranet for itself. Although security will remain an ongoing challenge, a single overarching network is much easier to manage than dozens — or even hundreds — of smaller ones. This holds true even as the scale of the data environment increases in both size and complexity.

At the end of the day, the most valuable commodity that the enterprise can offer to customers is trust. In a world of increasing security threats, that trust will belong to organizations that can effectively protect data while still providing top-notch access to the applications and network services that users find invaluable.

Ready to take the next step? Visit IBM Network Consulting Services

Related topic: Software-Defined Networking (SDN)

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

The post Five ways SD-WAN equips enterprises to improve network security appeared first on IT Biz Advisor.

Software-defined networking (SDN) is characterized as “the decoupling of control and packet forwarding planes in the network”. SDN allows networks to connect to apps using application programming interfaces (APIs). This relationship between SDN and APIs supports application performance and security and helps create scalable, dynamic network architecture.

SDN is frequently used for application deployment by enterprises globally and helps these organizations to quickly deploy their applications while simultaneously reducing the costs for deployment and operating. SDN helps IT administrators provision and manage their network services from a centralized point.

Yielding network resource optimization, programmatic management and control, SDN uses open APIs to support and maintain network control. This network control is created when SDN decouples the network configuration and traffic engineering, severing them from their fundamental hardware infrastructure. This separating action allows for OpenFlow use and the use of more open protocols, which can access network switches and routers that frequently use proprietary and closed firmware. These open protocols often use these types of firmware by leveraging globally aware software control from the end of the network

What is a traditional network?

The most common way of networking, traditional networking uses fixe-function and dedicated hardware and network devices, including switches and routers, to control network traffic.2 These devices have individual functions that work well together and help to support the network.

The ability to scale is a frequent problem for traditional networks. Most switching hardware and software is proprietary and it’s uncommon for APIs to be exposed for provisioning.

Traditional networks tend to synergize well with proprietary provisioning software. Unfortunately for traditional networks, this software is unable to be modified as needed and hardware-centric networking can be very limiting in what it’s able to use.

Traditional networking’s functions and functionality are implemented the following ways:

1. The functions are implemented from dedicated devices that use switches, routers and application delivery controls.

2. The functionality is primarily implemented in application-specific integrated circuits (ASIC) and other dedicated hardware.

How are SDN and traditional networking different ?

The biggest different between SDN and traditional networking is simply that SDN is software-based and traditional networking is usually hardware-based. Being software-based helps SDN with scalability and flexibility, and helps it provide its users with more control and easier resource management, allowing users to virtually manage resources with the control plane.

Unlike SDN, traditional networks use routers, switches and other hardware and physical infrastructure to generate connections and run the networks.

SDN controllers use a northbound interface that communicates with APIs, allowing application developers to program the network. The opposite of this interaction is application developers using traditional networking protocols to program the network.

When compared with traditional networking, SDN can better communicate with hardware that’s using the network. Instead of using physical infrastructure, SDN allows users to apply software for provisioning new devices and allows IT administrators to direct network paths and direct network services.

The biggest difference between SDN and traditional networking is showcased because of virtualization. SDN generates an abstract copy of your network when it virtualizes your network. This virtualization allows you to provision your resources from a centralized location.

For a traditional network, the physical location of the control plane hinders an IT administrator’s ability to direct the flow of traffic.

For SDN, virtualization transforms the control plane from being physical hardware to being software-based. Virtualization allows the control plane to be accessed through a connected device and gives IT administrators more control with directing the flow of traffic using a centralized user interface (UI). This centralized UI allows users more control over how their networks are configured and how they function. Users can quickly process different network configurations from the centralized UI, an ability that is particularly beneficial for network segmentation.

Because SDN allows IT administrators to provision resources and bandwidths, allowing admins to scale them as needed without requiring an investment of more physical infrastructure, SDN has become a popular alternative to traditional networking. Traditional networking needs new hardware to increase its network capacity. The concept of SDN versus traditional could be summed up by the following phrase: one needs more equipment for expansion and other needs more keystrokes.

Ready to take the next step? Visit IBM Network Consulting Services

Related topic: Software-Defined Networking (SDN)

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

The post SDN versus traditional networking: what’s the difference? appeared first on IT Biz Advisor.

Traditional network architectures that are too old, too rigid and too expensive to scale are out of alignment with today’s hybrid cloud and IT-as-a-service (ITaaS) deployments. Whether organizations are actively pursuing growth opportunities through innovation or reductions in cost and complexity, they need a network that is automated, intelligent and optimized for seamless operation within an increasingly virtualized and hybrid IT environment.

A different approach

Take, for example, a major international airline that needed to reinvent its global network to improve reliability, cost and service to customers. As the airline network expanded, so did cost and complexity. Additionally, the enterprise was dealing with the challenge of internet services that varied significantly in reliability and cost across many of the countries they served.

A multi-provider approach, which combined capacities from different carriers, enabled the airline to take advantage of individual providers’ local strengths and make up for the shortfall in certain regions. It provided customers with powerful and secure links to the enterprise network and major reservation systems through a virtual private network.

Highly interactive cloud-based applications and volatile traffic patterns demand a network infrastructure that is more agile, more adaptable and more in sync with the business it supports. The need for instantaneous, elastic connectivity across the enterprise is no longer just an option — it’s essential for a successful business. Additionally, the network needs to be managed as a programmable service providing enterprises a single management pane to view and program their network securely. This drives greater transparency, ensures resiliency, integrates security, and enables agility to scale quickly.

Redefine your cloud journey by infusing a software-defined approach to your networks

What’s required for transformation

Networking, IT and business requirements demand solutions that work holistically within an enterprise. These solutions require input from a broad spectrum of domains and stakeholders throughout the enterprise. Thus, network consulting projects are often complex, transformative and differentiated. To maximize value and minimize disruption as an enterprise moves through a network transformation project, enterprise decision-makers must:

• Ensure a services firm can strategically prioritize networking, operational and business requirements.
• Bring together disparate stakeholders and influencers to ensure a linkage between the business and the technology.
• Deliver the project in a globally consistent manner in a variety of consumption and payment models.
• Define and deliver repeatable methodologies for technology, operational and business change.
• Articulate investments in new technologies, processes, and tools for efficient, secure and intelligent service delivery.

The business advantages of a dynamic, programmable and virtualized network environment are significant and include more innovation, faster time to market and better security. It’s imperative when it comes to successful deployment of hybrid cloud and ITaaS. The transition to software-defined networking requires thoughtful strategy and design to prepare the organization and the infrastructure.

Ready to take the next step? Visit IBM Network Consulting Services

Related topic: Software-Defined Networking (SDN)

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

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And IT is certainly feeling the pressure: In the same survey, 47 percent of IT teams voiced the business demand for more IT agility and speed, while about 44 percent cited modernization and re-platforming, and 39 percent referenced the requirement for a data center upgrade, expansion or replacement.

As businesses hurtle toward the cloud, it’s critical to consider whether or not current enterprise networks will be able to handle the transformation.

Programmable networking for a multicloud world

Network modernization is absolutely essential to digital transformation. Your enterprise network is the IT backbone of your business. With increasing complexity, aging networks, the accelerating need for network agility and an evolving application landscape, IT leaders are turning to programmable, agile and software-driven enterprise networking solutions.

Software-defined networking (SDN) has emerged as an architectural approach to data center networking in the cloud era, bringing the flexibility and economy of software to data center hardware. SDN helps align enterprise network infrastructure with the needs of application workloads by providing:

• Automated orchestration and agile provisioning
• Programmatic network management
• Application-oriented, network-wide visibility
• Direct integration with cloud orchestration platforms

This transformation goes beyond the data center. Digital transformation and increasing hybrid IT and multicloud adoption are also redrawing the boundaries of remote and cloud locations, redefining what’s required of both data center local area networks and enterprise wide-area networks (WANs). Fortunately, that same SDN technology can be applied to connect enterprise networks, including branch offices and data centers, over large geographic distances. A software-defined approach to WAN (SD-WAN) makes it possible for IT to provide reliable access to business applications across the entire enterprise.

Orchestrate and automate

To maximize the value of a virtualized network, it’s critical to implement a strategy for orchestration and automation. These things work in tandem to help you reap the full benefits of network virtualization:

• Enable self-service functions for development teams
• Reduce risk through integrated governance and management
• Prevent vendor lock-in on hardware-based platforms
• Save time by orchestrating and automating integration complexities
• Boost overall quality through intelligent and aware operations like self-healing

Complexity hinders agility, but an intelligent, self-driving network that harnesses the power of AI can help minimize complexity and further optimize performance, application availability and overall user experience, helping you drive even more value from network virtualization.

Network modernization may seem like an overwhelming challenge. It can be a struggle to get a clear picture of the evolving application environment, let alone how it maps to changing requirements for network infrastructure and network operations. If yours is like many organizations that don’t know where to begin, you may benefit from a consultative approach.

A network modernization partner can help you identify gaps that might hinder SDN deployment, determine automation needs, define an orchestration strategy and develop a roadmap. Because one thing’s for sure: Technology is always moving forward. Whatever comes next, network agility is prized as a strong foundation for any innovation.

Ready to take the next step? Visit IBM Network Consulting Services

Related topic: Software-Defined Networking (SDN)

In depth: IBM Network Services topics:

Network Services

Network Consulting Services

Software Defined Networking (SDN)

Managed Network Services

Hybrid SD-WAN Services

What is Software-defined wide area network (SD-WAN)?

What is a software-defined data center and how it can help your business?

SDN vs Traditional Networking Explained

What is network function virtualization (NFV)

The post Network modernization is essential for digital transformation appeared first on IT Biz Advisor.

Enterprise the back-end network, to provide uninterrupted connectivity to a dispersed workforce. In many cases, network infrastructure at enterprises around the world has exceeded expectations in delivering a seamless experience. This success has been made possible by global telecommunications service provider networks supported by technologies such as software-defined networking (SDN) and network function virtualization (NFV) delivered by services integrators — as well as the relentless efforts of millions of network engineers.

As we navigate the pandemic and learn to live with it, enterprises are shifting focus from initial response and damage control to reopening and emerging stronger from disruption. The return to work initiative is gaining traction as companies start thinking about their long-term, strategic response. These critical moves require a strong foundation: Your network must be modern, agile and efficient enough to adapt to change and support ongoing cloud transformation.

IDC whitepaper: Network modernization – Essential for digital transformation and multicloud

Modernize your network to adapt to change

The application landscape has been redefined by cloud and multicloud, and your network must adapt, both architecturally and operationally. Enterprises need network transformation to accelerate agility and efficiency in the cloud, optimize costs and deliver applications with security and resiliency.

Global IT decision-makers often experience cloud-related network issues caused by legacy infrastructure. Traditional networks struggle to support the distributed nature of cloud services, resulting in a degraded user experience. The network and interconnectivity across physical infrastructure, virtual infrastructure and as-a-service consumption hinder broad cloud adoption across the enterprise.

Successful network transformation challenges us to think about the network in new ways and requires commitment from business, development and operational leaders across the enterprise. You need to define the right modernization and network orchestration approach for your particular organization. For faster time to market and network resiliency, your network also needs to be programmable.

A programmable network is achieved when SDN decouples network service control and data planes from the switches, routers and other network appliances. Once they’re abstracted from the underlying infrastructure, these controls become directly programmable and management can be centralized. This enables the network to automatically request and have services provisioned as needed through application programming interfaces (APIs).

Many organizations don’t know where to begin as they seek to modernize their networks for digital transformation and cloud and find themselves daunted by the breadth and depth of the challenge. Engagement with a trusted partner can help you make sense of how your networks can be modernized, as well as how such modernization can be achieved within the bounds of your existing technology investments, and the skill sets and comfort levels of IT and network personnel.

SDN has revolutionized the way networks are conceptualized, designed, deployed and managed. The enterprise network of the future will drive virtualization across existing infrastructure with SDN, which will enable wide-area networking at scale.

As workloads shift to cloud and applications are modernized for cloud infrastructure, the next step is service chaining the virtualized network functions and platforms that reside in your data center and cloud environments. To succeed here, you will need orchestration, automation and a DevOps mindset to drive consistency across these diverse environments.

Webcast: Network transformation – Enabling your journey to cloud

Emerge smarter

Beyond modernizing your network infrastructure, here are six key areas where technology can help your enterprise emerge smarter from this disruption, stronger and better prepared for disruptions in the future.

1. Work safe and work smart to safeguard the health, safety and productivity of your people in a changing workplace. Explore technologies to help with workplace re-entry planning, facilities management, workplace safety, contact tracing, care management and customer and employee care.
2. Engage customers anywhere by deploying features like chat and virtual agents to increase productivity and provide timely responses to your customers and employees.
3. Enhance IT resiliency and business continuity with end-to-end data protection management to address your unique backup, retention and retrieval needs.
4. Accelerate agility and efficiency with cloud to operate your business anywhere and adapt to changes without compromise.
5. Address new cybersecurity risks, uncover hidden threats and make more informed risk-based decisions.
6. Reduce operational cost and ensure supply chain resiliency with actionable AI-based insights, real-time insights and automated decision-making where it makes sense.

Now is the time for enterprises to dig deep and rethink how business works. We’ve all been given a mandate for change, to challenge our beliefs about what matters most to the viability, competitiveness and health of our organizations and workforces. Together, we can make lasting changes that will help us become stronger as individuals, as businesses and as a society. The actions we take right now can help us grow smarter, more resilient and agile using technology—not just to survive today, but to thrive for years to come.

So, let’s get to it.

Prepare for the next wave of cloud with 5G-enabled edge and software-defined networking

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RPO and RTO establish the foundation for determining and discerning strong inclusion strategies for the business continuity plan (BCP). These strategies should allow for the speedy resumption of business continuity processes within a time frame equal to or close to the RPO and RTO.

Although they’re both tied into determining disaster recovery, an RPO must remain independent of an RTO or the minimum estimated time needed to restore regular operations following a system or network failure.

Like RTO’s, RPO’s help determine disaster recovery policies and procedures. The RPO helps administrators choose the best backup and recovery technologies to use, depending on the overall design strategy that data loss shouldn’t delay the RTO.

How’s an RPO different from an RTO?

Both RPOs and RTOs are concepts used for supporting business continuity. They also work as business metrics and can help you calculate how often your business should perform data backups.

RPOs and RTOs are instrumental to a business’ disaster recovery plan or data protection plan. They’re both linked to business impact analysis, a systematic process that can help separate critical and urgent organization-specific functions and activities from non-critical and non-urgent ones. Functions can be considered critical if specified by law.

RPO and RTO are the two values that are assigned for each function. Whereas RPO determines how much data will or will not be recovered after a disruption, RTO determines how much time it takes for a system to transition from disruption and to regular operations functioning normally.

How’s a RPO calculated?

RPOs go backwards in time, stretching back from the instance of disruption to the last backup point where the data is usable. They can also measure how often you should regularly backup your data.

In terms of calculation, RPOs are usually calculated in minutes or hours but, depending on the urgency or lack thereof, they can also be calculated in seconds or days. An RPO determines how far back into the data’s history you need to go for backup storage to resume normal operations after a computer, system or network experiences disruption from a hardware, program or communications failure.

An RPO can also be considered the maximum acceptable amount of data loss that’s measured in time. In addition, it can describe how much time passes during a disruption before the amount of data lost during the period of disruption extends beyond the business continuity plan’s maximum allowable “tolerance” or threshold.

For example, if a computer system has an RPO of 30 minutes, that means that the maximum window for data loss following a disruption is 30 minutes. Therefore, a backup of the system must be performed every 30 minutes.

IBM disaster recovery as a service (DRaaS) helps enable rapid and reliable recovery

When should you schedule data backups for an RPO?

RPOs are often easier to perform than RTOs. The reason is because data use provides few variables and is generally consistent. However, the opposite can also be true since calculating restore times is usually based on your whole operation and not just your data.

When the disruption happens is also a factor in the restore time. When constructing your data backup schedule, consider what hours your business is the busiest and least busy. For example, if you have a disruption at 3 AM Eastern Standard Time and IT resolves the disruption by 5 AM, did you lose two hours’ worth of data? If this timeframe is a low-traffic period for your business, then probably not.

For another example, let’s say your business backs up its data every 10 hours. There’s a disruption at noon and it’s quickly resolved with your business back to normal by 12:30 PM. Because there was only a 30-minute window of data loss from 12 PM until 12:30 PM, you don’t need to restore all the data from the previous 10 hours. You only need to restore data from the lost 30 minutes.

Simplify your disaster recovery (DR) management with IBM Resiliency Orchestration

Disaster recovery and disaster recovery plans

Not to be confused with emergency management and disaster response, disaster recovery deals with IT infrastructure and systems in support of important business processes. Disaster recovery is a subset of business continuity, which works to maintain all vital aspects of a business despite any disruption.

Disaster recovery is the policies, tools and procedures that compose the eponymous restoration or continuation of critical technology infrastructure and systems after a natural or manmade disaster has occurred.

A disaster recovery plan (DRP) is the process or procedures used to perform a disaster recovery process, and recover and protect an organization’s IT infrastructure and systems following a disaster. This process can be expanded to take place before and during a disaster.

Ready to take the next step? Schedule a consultation with an IBM Business Continuity Services expert.

Related topic: Disaster recovery as a service (DRaaS)

IBM products related to business continuity plans

• IBM Resiliency Orchestration
• IBM Disaster Recovery as a Service (DRaaS)
• Cyber Resilience Services
• Data protection with Backup as a Service (BaaS)
• IBM Business Continuity Consulting Services
• IBM Data Center Services

Understand how to plan for and react when business disruptions are happening.

Adapt and respond to risks with a business continuity plan (BCP)

How to defend against cyber attacks

Do you have your disaster recovery plan (DRP)?

Defend against ransomware attacks?

What is data breach and how to defend against one?

What is a recovery time objective (RTO) and how does it affect disaster recovery for your enterprise?

What is an RPO (recovery point objectives)?

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AI and machine learning have their genesis in science fiction and a revered, colorful history that stretches back to antiquity and forward to the present day. They are used across countless areas to make our daily lives better. For many enterprises, AI and machine learning are quickly populating their data centers as tools to help solve complex issues including prediction and optimization.

What’s deep learning?

Techopedia defines deep learning as “a collection of algorithms [that are] used to model high-level abstractions in data [through] model architectures [composed] of multiple nonlinear transformations.” Deep learning is used by machine learning and is part of a group of methods that are based on learning representations of data. It’s a specific approach for constructing and training neural networks: decision-making nodes with a vast potential.

Algorithms are considered to be “deep” if that input data is siphoned through a series of nonlinearities or nonlinear transformations prior to the input becoming output. Inversely, the majority of today’s machine learning algorithms can be deemed “shallow” since their input can only reach the first few levels of subroutine calling.

Deep learning eliminates the manual identification of features in data and relies on its training process to discover the input example’s useful patterns. This feature makes the training process for neural networks easier and faster and helps produce better results, which advances the field of AI.

How do businesses use deep learning, AI and machine learning to boost efficiency and cut cost?

Deep learning, AI and machine learning are tools that can analyze a vast amount of data, then locate patterns within that data and determine when these patterns might repeat in the future. AI and machine learning can model alternate configurations, boosting uptime and resiliency, locating opportunities for preventative maintenance, and targeting potential cybersecurity risks.

Data centers usually feature a wealth of resources and sensory instruments, supplying their operations with real-time and historical data on their overall performance and their environment. Optimizing resources and predicting and preventing downtime are important functions for AI and machine learning in data centers. By monitoring real-time performance data that regulates power management and system cooling, not only can AI and machine learning conserve and otherwise optimize their resources, but also predict where failure might occur in the data center. If they can locate where a failure is likely to occur, then preventative maintenance can be performed, and system downtime or a system outage can be prevented.

How Google used DeepMind to optimize their data centers’ cooling ability

In the article Smartening up: How AI and machine learning can help data centers, Peter Judge notes that beginning in 2014, Google’s data center engineer Jim Gao began using DeepMind technology as a recommendation engine. By 2016, a couple of neural networks had learned to predict future temperatures and give suggestions on how to proactively respond. This use of AI allowed Google to optimize the cooling of their Singapore facility, reducing the cost of the site’s cooling by 40% and saving 15% of the facility’s power utilization effectiveness (PUE).

During 2018, Google applied the same approach used in their Singapore facility data center and created a self-driving data center cooling system where AI oversaw the data center’s operational settings alongside human oversight. With safety in mind, the bar was set for the automatic system to only reduce the cost of the cooling bill by 30 percent. Ultimately, the data center saw a “40% drop in the amount of energy needed to cool the facility [and achieved] the lowest [PUE] score in its history of 1.06.”

To predict how actions would affect energy consumption and determine the best choice for the future, the AI system used thousands of sensors and recorded snapshots every five minutes of the data center’s cooling system. The AI system then fed this information to a cloud-based AI system and selected what it believed was the best choice of action. This action was then forwarded to the data center where it was verified by that center’s human operators and, if the action was deemed safe, was performed.

Eventually, the AI learned to predict environmental changes and to take advantage of them. For example, the AI used chilly winter conditions to create colder water that reduced the energy needed for cooling the data center.

How can AI and machine learning help businesses to understand their customers?

Businesses are using AI and machine learning to analyze the vast amounts of customer information found throughout their business’ data centers. If the AI or machine learning software is connected with a customer relationship management (CRM) system, then they can locate and retrieve customer data that is otherwise not used by the CRM system. Ultimately, businesses could use AI and machine learning to create strategies for customer lead generation, boosting customer success and reducing customer churn.

How can AI and machine learning help businesses to use prediction?

When there is a big environmental change, people can overreact or just make the wrong decisions. In this area of response, AI can perform better here than people can, maintaining stability with logic-based predictive approaches for choosing the best actions.

Learn more about data center modernization

Temperature fluctuations among servers in data centers can waste lots of resources trying to get a server that is too hot back under control. If a server is temporarily taken offline, then it drastically reduces the data center’s productivity. Data center infrastructure management (DCIM) firms are working to remedy this quandary by integrating predictive analytics with AI and machine learning.

Raw data from sensors is processed and fed into predictive modeling engines. AI and machine learning use pattern matching to regulate temperature and locate signs of refrigerant leaks. Some systems analyze and discern areas for improvement within an AI system.

How Nlyte uses IBM Watson® to move beyond prediction

Peter Judge notes that in 2018 the DCIM vendor Nlyte integrated its tools with IBM Watson. The goals of this collaboration were to improve AI and machine learning-based preventative maintenance and to move “beyond predictive things [and] into workloads and managing workloads.”

Judge goes on to state that AI can help reduce workload size and the risk of workload failure. He cites the North American marketing lead for IBM Watson IoT Amy Bennett, who says AI is “a member of the data center team [who] never takes a vacation.”

What’s direction will AI and machine take in the future?

The ultimate challenge with using AI and machine learning to improve the power and efficiency of cooling data centers’ and container orchestration and move the IT loads themselves and reduce the IT energy cost.

Judge references Suvojit Ghosh, the head of Computing Infrastructure Research Centre (CIRC), who is using AI to analyze the sounds of a data center and their correlation with power consumption. Ghosh is working to create an AI that can predict when something needs to be repaired or replaced. This can be coupled with human operators and engineers who could receive the data center’s condition reports from the AI, and then respond accordingly with repairs or problem solving.

In the article How machine learning in data centers optimizes operations, Julia Borgini argues that machine learning software is predicting issues and resolving them faster than ever before. Machine learning is an extension of the hybrid data center environment and a burgeoning arm of data center infrastructure. Borgini states “IDC predicts that 50% of IT assets in data centers will run autonomously using embedded AI functionality by 2022”.

AI and machine learning could eventually reach the point where the system autonomously performs digital actions and assigning robots to perform physical actions, such as the day-to-day physical maintenance and operations of the data center. This futuristic ability for AI to run a data center without the need for human interaction would create a model for self-sustaining data centers.

Ready to take the next step? Schedule a consultation with an IBM Business Continuity Services expert.

Related topic: Disaster recovery as a service (DRaaS)

IBM products related to business continuity plans

• IBM Resiliency Orchestration
• IBM Disaster Recovery as a Service (DRaaS)
• Cyber Resilience Services
• Data protection with Backup as a Service (BaaS)
• IBM Business Continuity Consulting Services
• IBM Data Center Services

Understand how to plan for and react when business disruptions are happening.

Adapt and respond to risks with a business continuity plan (BCP)

How to defend against cyber attacks

Do you have your disaster recovery plan (DRP)?

Defend against ransomware attacks?

What is data breach and how to defend against one?

What is a recovery time objective (RTO) and how does it affect disaster recovery for your enterprise?

What is an RPO (recovery point objectives)?

The post How can AI and machine learning help data centers? appeared first on IT Biz Advisor.

Part 2 focused on how business continuity is used and its biggest threats.

Part 3 focuses on implementing business continuity management and planning.
These concepts were briefly referenced in Part 1.

What’s business continuity management (BCM)?

SearchCIO defines business continuity management BCM as “is a framework for identifying an organization’s risk of exposure to internal and external threats”. SearchCIO continues noting that the “goal of BCM is to provide the organization with the ability to effectively respond to threats [and] protect the business interests of the organization.

Techopedia notes that several “organizations and trade groups have participated in building [BCM] standards” and that different organizations “offer certifications for this type of role”.2 Alternatively, other organizations can congregate and discuss how best to generate BCP for different disastrous scenarios. This planning is often rooted in past disruptive events that occurred, the damage that was produced, and the best preventative measures and recovery strategies that were revealed following them.

How does BCM work best?

Business continuity management BCM works best if the infrastructure for good response systems has been established. These systems help minimize damage from potentially disruptive events and allow organizations to focus on scalable supply chains, the deployment of data safeguards and similar IT practices. At its core, BCM works on the principle that good response systems can help businesses avoid some damage from theoretical events.

What groups have developed BCM standards?

Techopedia notes that the British Standards Institute (BSI) and the International Organization for Standardization (ISO) created some BCM standards to help other businesses bolster themselves against potential disasters and emergencies.

What’s business continuity planning (BCP)?

Business continuity management BCM, like every other concept that involves risk, benefits from having information and strategies that bolster its success and minimize its risks. BCM uses resource management to fight against disruption causing threats like natural disasters, network failures, cyber attacks and human error. BCM provides your business with the tools to best prevent these threats and to minimize their impact if and when they occur. BCP, also referred to as a business continuity plan (BCP), functions similarly, and helps your business identify, assess and plan for a crisis, as well as practicing how to respond to them.

A BCP helps your business mitigate the disruptive effects of a disaster or emergency, allowing you to continue or resume general business operations. It behooves a business to have several different BCPs, bolstering the business’s cyber resilience and helping the business continue operating if one of the planned threats occurs.

What are the steps for developing a BCP?

Techopedia states that a BCP involves the following steps:

1. Analysis of organizational threats
2. A list of the primary tasks required to keep the organization’s operations flowing
3. Easily located management contact information
4. Explanation of where personnel should go if there’s a disastrous event
5. Information on data backups and the organization’s site backup
6. Collaboration among all facets of the organization
7. Buy-in from everyone in the organization

The first step for anyone developing a BCP is to determine every threat that could shut down your general business operations. The second step is to identify the critical tasks needed to resume your general business operations.

Several people should be involved in the creation of a BCP for your business. Every BCP should include the most recent list of your management staff and how they can be reached. This information should also be available to your management staff outside of the office, allowing them to reach one another if it’s impossible to get into the office. During an emergency like a natural disaster, this process helps your staff connect with each other and create plans for resuming business operations. Regularly training your staff on disaster recovery plans and frequently backing up your data helps increase the chances of your business quickly resuming general operations after a disaster or similar disruption.

Ready to take the next step? Schedule a consultation with an IBM Business Continuity Services expert.

Related topic: Disaster recovery as a service (DRaaS)

IBM products related to business continuity plans

• IBM Resiliency Orchestration
• IBM Disaster Recovery as a Service (DRaaS)
• Cyber Resilience Services
• Data protection with Backup as a Service (BaaS)
• IBM Business Continuity Consulting Services
• IBM Data Center Services

Understand how to plan for and react when business disruptions are happening.

Adapt and respond to risks with a business continuity plan (BCP)

How to defend against cyber attacks

Do you have your disaster recovery plan (DRP)?

Defend against ransomware attacks?

What is data breach and how to defend against one?

What is a recovery time objective (RTO) and how does it affect disaster recovery for your enterprise?

What is an RPO (recovery point objectives)?

The post Business continuity part 3: How is business continuity planned and managed? appeared first on IT Biz Advisor.