Industry Solutions and Trends
Technology is more than just networking and Juniper experts share their views on all the trends affecting IT
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In today’s evolving business climate, companies of all types—service providers, cloud providers, and enterprises—are building more than just a network.  In fact, the network itself is merely a means to an end—an enabler for network services and a conduit through which applications pass.  In other words, the network is a platform that drives the business.

 

Clouds Begin with Platforms 

Let’s extrapolate this concept out further.  I look at every element within the network as if it is a platform, too:  hardware is a platform for software; software is a platform for network functions; the network is a platform for the cloud; and the cloud is a platform for applications that are the backbone of the cloud economic model. 

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Blockchain: Pardon the Disruption

by Juniper Employee ‎07-31-2017 03:04 PM - edited ‎08-14-2017 01:58 PM

 

Brooklyn Microgrid.png   .

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You have probably heard about “cognitive computing,” a methodology that simulates human intelligence through the application of machine-based cognitive models.  A subset of artificial intelligence (AI), cognitive computing mimics the cognitive behaviors of human “thinking” in order to achieve human-like insights within the machine world—in other words, making machines think like humans.

“Cognitive cloud infrastructurCognitive Cloud.jpge” follows a similar path, applying cognitive computing techniques to cloud infrastructure, enabling it to “think like humans” and become essentially self-driving.

 

As thinking humans, before we can apply intuitive reasoning to a given situation, we must build “perceptions” in order to develop awareness based on our experiences. I believe we are currently at the “perception stage” with machine learning techniques - building awareness using telemetry sensors at every layer within the cloud infrastructure. This is the first step towards achieving the cognitive “thinking stage” as technology progresses.

 

As cloud infrastructures are built to differentiate themselves in a hypercompetitive world, many innovative Web 2.0 companies are positioning their own migration to cognitive cloud infrastructure. In these cloud infrastructure environments, analytics controllers collect not only structured data but also dark, unstructured operational data.  When this unstructured data is combined with policy and baselined data, new insights can be gained using machine learning techniques. Patterns and relationships can be developed from the multi-layer infrastructure data with contextual associations; this awareness is critical to the “perception” stage.  As we move from the “perception” to the “thinking” stage, cognitive controllers can progress from perception to reasoning to driving the cloud infrastructure, learning in real-time to continue honing reasoning ability.

 

Data is plentiful in cloud infrastructures, and most modern cloud platforms support streaming telemetry at every layer.  However, most of this data is not utilized to form insights that provide the contextual awareness required to make actionable decisions.

 

So, what are the characteristics of cognitive cloud infrastructure? 

 

Intent-Based Global Policy

A model-driven policy that defines all of the multi-layer cloud resources is key to achieving intent-based global policy.  In order for this policy framework to scale, the policy attachments and enforcement should be distributed as close to resources as possible.

 

This distributed approach reduces the big data noise and only sends the relevant signals and data to the centralized cognitive controller, enabling higher-frequency collection for better learning, and scale to achieve the cognitive cloud.

 

Multi-Cloud Monitoring

Contextual monitoring of related workloads and resources, regardless of their location, is critical for dynamic cloud environments. Also, distributed collection points with a centralized aggregation point can bring increased scale to hyper-scale cloud environments. As multi-cloud environments take shape, global multi-cloud monitoring is critical to achieving a seamless cognitive cloud.

 

Predictive Analytics

Once you have an intent-based policy with multi-cloud monitoring in place, baselining with machine learning enables cognitive controllers to start building awareness and perceptions that allow predictive insights. These predictive models exploit patterns in contextual historical data, moving from the “perception” to the “thinking” stage as cognitive models and sensors evolve. These sensors can feed resource-related behavior data, policy-related descriptive data, and contextual resource interaction data that enable the cognitive models to learn from experience and employ reasoning and logic to create better cognitive clouds.

 

As Intent Based Global Policy, Multi-Cloud Monitoring and Predictive Analytics integrate with SDN Controllers, we start to move towards the Self-Driving Cloud by triggering a closed-loop of control.

 

Juniper Networks, with programmable infrastructure platforms like Contrail Networking, and intelligent analytics platforms like AppFormix, is well-positioned to lead the journey to the cognitive cloud. As we move from automation to actionable insights based on awareness and reasoning, the cognitive cloud moves within our reach, driving real business outcomes in agility, operational simplicity, and an improved user experience.  

 

Are you ready for the journey?

The Service Provider Cloud

by Juniper Employee ‎07-19-2017 06:56 AM - edited ‎07-31-2017 01:11 AM

ServiceProviderCloud.png

Software-defined networking (SDN) and Network Functions Virtualization (NFV) have revolutionized the traditional communication network architectures and have transformed the way communication service providers (CSPs) design their network infrastructure and services. The implementation of the Service Provider Cloud (Telco Cloud, Cable Cloud or Mobile Cloud architecture) is a strategic step for SPs to become competitive in the Digital Cohesion era.

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How will Digital Cohesion impact the Service Provider space?

by Juniper Employee ‎07-13-2017 08:13 AM - edited ‎07-31-2017 01:27 AM

In a Digital Cohesion world dominated by mega-services, what will be the role of Communication Service Providers?

And ultimatelly, how will they compte?

 

                                       SP Digital Cohesion.png

Juniper Cloud-Grade Networks provides the architecture framework for Service Providers to compete in the Digital Cohesion era.

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Everywhere Networking

On June 20th, Juniper announced the concept or “Cloud-Grade Networking,” which builds on carrier-grade reach and reliability and enterprise-grade control and usability to bring cloud-level agility and operational scale to networks everywhere.

 

One of the tenets of Cloud-Grade Networking is the ability to run anywhere and everywhere—on any software, on any hardware, in any cloud. Juniper calls this requirement Everywhere Networking, and it refers specifically to the disaggregation of the networking technology stack so that applications can run in any cloud, cloud workloads can run on any device, and software can run on any hardware.

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The Connected Campus Powers Digital Learning (Part 1)

by Juniper Employee ‎06-30-2017 11:33 AM - edited ‎07-11-2017 02:48 PM

We recently held our annual higher education advisory board meeting at one of our global Openlab facilities in New Jersey.  We had CIO’s and IT leaders from several leading institutions.  Rutgers, Virginia Tech, University of Nevada – Reno, Kent State, DePaul, Cornell, Stevens Institute of Technology and Olin College of Engineering were members that attended and shared their top of mind issues in front of them, including:

  • Establishing a “cloud appropriate’ strategy
  • Balancing security / risk across academia and research – cybersecurity was the top issue and aligns with the 2017 Educause top IT issues list.
  • Staffing – attracting and retaining with an eye on the skills gap that exists with pace of technology advancements in automation, analytics, and machine learning.
  • Analytics for better-informed decision making across the institution’s lines of business. Bill Dillon of NACUBO facilitated a great session on actionable intelligence. 
  • Increasing student outcomes (retention and graduation rates) while also establishing new sustainable funding models.

In this five part series, I will overview what we call the “Connected Campus here at Juniper.  What it is and how it can address the issues raised above.  To truly empower and engage students' success, colleges and universities must transform their legacy networks into agile, predictive service platforms that are accessible by students, faculty, and staff - anywhere, anytime. 

 

The Connected Campus is our blueprint for building a more secure, automated, and simplified campus network to enable digital transformation.  With the Connected Campus, college and universities will:

  • Connect students, faculty, and staff with always-on access to digital learning and research environments.
  • Protect student and institutional privacy by building a more secure network.
  • Automate and reduce the operating costs to deliver digital learning through a simplified campus network.

The Challenging Journey Toward Network Transformation

by Juniper Employee ‎06-08-2017 07:54 AM - edited ‎06-08-2017 11:10 AM

At Juniper Networks, we see customers across all industries seeking to modernize their legacy networks through massive digital transformations. Each customer is different, but most share similar goals. They want to be able to increase the speed of application and services deployment, decrease production times through automation, enhance security and business continuity, and achieve greater flexibility while lowering operational costs.

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Multi Cloud.jpgEnterprises have moved beyond the “Private vs. Public vs. Hybrid Cloud” debate, embracing a “Multi-Cloud” strategy that offers unprecedented flexibility for matching workloads to best-in-class technologies, adopting various price-points, and choosing geographical locations.

 

Enterprises still prefer private clouds to support their predictable and sensitive workloads, and they value the elastic nature of public clouds and the inherent benefits of pay-as-you-go economics and bursty dynamic workloads when scaling the business to meet demand growth. The multi-cloud approach offers the best of both worlds, allowing users to easily move workloads from private to various public clouds without getting locked into a particular provider.

 

The 1H 2017 OpenStack Summit, held in Boston May 8-11, saw a majority of sessions devoted to Mutli Cloud strategy and Kubernetes.  Many other sessions focused on the operational challenges of large-scale deployments.  Telco presenters emphasized the need for VMs and containers to co-exist for years to come, warning the community to plan for such a mixed environment.

 

Why Kubernetes Invaded the Sessions at OpenStack Summit

OpenStack has long been a platform that uses VMs as the computing units for cloud workloads. As the adoption of containers takes off, however, thanks to their low footprint and faster bring-up times, Kubernetes is also taking off as the top container management framework. This has created concerns about whether this trend will lead to the end of OpenStack. It is promising to see how the OpenStack community is embracing Kubernetes as a complementary technology for accelerating multi-cloud adoption.  The two sides have agreed not to duplicate efforts and instead focus on the right things at each layer:  OpenStack will remain a programmable platform for the cloud infrastructure, while Kubernetes will manage container clusters.

 

Apart from hyper-scale cloud providers such as Amazon Web Services (AWS), Google Compute Platform (GCP), and Microsoft Azure, who build their clouds based on their own proprietary platforms, there are more public cloud operators building their solutions on OpenStack.  Operators such as Rackspace, Internap, China Telecom’s CT Cloud Platform, Telefonica Open Cloud, and DT’s Open Telekom Cloud are building their clouds on OpenStack while promising their enterprise customers they will seamlessly enable multi cloud on the same platform.  These OpenStack-based public cloud providers are betting that these enterprises will lean heavily on their familiarity with OpenStack when developing their multi-cloud strategy to gain market share.

 

What are the Near-Term Challenges to Multi-Cloud Adoption?

The multi-cloud strategy elevates the complexity of enterprise IT operations, driving customers to seek out vendors and operators who can help them manage that complexity and reap the benefits of multi cloud.  A trusted partner can mitigate the operational risks and accelerate the adoption of multi-cloud technology.

 

Multi-Cloud Management Challenge

As enterprises adopt more micro-service architectures to build hyperscale applications, the challenge of interconnecting these decomposed workloads and monitoring them for auto-healing and auto-scaling reasons amplifies their role in the multi-cloud strategy.

 

Many vendors have started introducing platforms and tools to cope with this workload management challenge. Juniper Networks, with its widely adopted OpenContrail SDN platform and recently acquired AppFormix multi-cloud analytics and monitoring platform, is spearheading a solution to this operational challenge. As platforms that hide the complexity of multi-cloud architectures, it is essential for OpenContrail and AppFormix to support various computing units such as bare metal servers, VMs, and containers, providing predictive analytics across multiple clouds.  By integrating Kubernetes and AppFormix, which Juniper demonstrated at the OpenStack Summit in Boston, OpenContrail seamlessly and intelligently manages all three computing units.

 

Multi-Cloud Skill Challenge

Over the years, many businesses have trained their IT staff to manage their IT infrastructure using well-established, high-performance methods and tools.  As the adoption of multi-cloud technology grows, the skill gaps between the cloud technologies can stymie IT staff, preventing them from successfully managing and operating the multi-cloud environment unless they can bring some of the familiar tools with them.

 

Many vendors now offer both physical and virtual components of their infrastructure to seamlessly leverage acquired skills and experience across multiple cloud environments. Juniper Networks, with virtualized routing and security products such as the vMX virtual router and vSRX virtual firewall, enables enterprises to apply common routing and security experience to multiple cloud environments.  This “carry forward” strategy also applies to common feature sets, networking stacks, and networking OS shared by both physical and virtual solutions, allowing users to streamline the deployment and use of these networking components across multiple cloud environments.

 

As multi-cloud deployments accelerate, OpenStack, Kubernetes, and OpenContrail with AppFormix take on an increasingly important role in not only efficiently building private clouds, but also seamlessly enabling workloads across multiple cloud environments.

 

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