Cisco MDS 9000 and IBM FICON: Just Got Married Again

We know humans like to celebrate. The wedding date represents a significant one for many couples and there is a tradition to celebrate again, even if with less fanfare, upon reaching a specific amount of years together. Apparently originated from an ancient German tradition, there is also a symbolic name to represent how long ago the wedding occurred. For example, the golden wedding indicates 50 years of marriage.

Cisco MDS 9000 series and IBM mainframe FICON have not reached that level yet. The original wedding date was in 2004, and 2020 marks 16 years, assuming my math is not wrong. There is a name for this, despite not popularly used. It is called ivy wedding….but don’t ask me why.

IBM originally announced FICON channels for the S/390 system in May of 1998. Since then, FICON has evolved from 1 Gbit to the 16 Gbit FICON Express16S channels, announced in January 2015 in conjunction with the IBM Systems z13. Each generation of FICON channels offered increased performance and capacity. Initially, the FC-SB-2 Fibre Channel upper-level protocol (ULP) was used by FICON. As the name implies, a single byte (SB) link address was used to specify the switch port on the director, out of a range of 00-255. It supported key features like native FICON storage devices, channel-to-channel connections, FICON directors (or switches), and more. But it did not allow for switched paths over multiple directors. In 2003, with the introduction of a new and enhanced ULP, this limitation was removed. In fact, FC-SB-3 employs a dual byte address.

Funny enough, rather than changing the name from SB to DB, it was decided to change the version instead, increasing its number from 2 to 3. This was the beginning of cascaded FICON. Two directors per fabric, also known as single-hop cascading, became possible since then. Recently multi-hop cascading has been qualified and has opened up new deployment options. Fibre Channel Single-Byte-4 (FC-SB-4) standard followed in 2008 and accounted for a big step forward in terms of performance, by reducing FICON channel overhead with the introduction of the high-performance FICON for System Z (zHPF).

A few years later, FC-SB-5 was standardized and in 2020 work is still in progress for the FC-SB-6 standard and new improvements are expected. Meanwhile, new routing schemas have come along, specifically FICON Dynamic Routing (FIDR), creating an exchange-based routing model (OXID-based routing). Meanwhile, the mainframe gained enhanced monitoring capabilities for switching devices with a revamped version of the CUP protocol.

Just as the protocol and the topologies have evolved over time, the same is true for requirements, expectations, and underlying hardware products. Cisco MDS 9000 series has just completed the most stringent testing and validation exercise, successfully receiving its latest FICON certification letter and can be found on the IBM resource link page (registration is needed to access this website).

With software version, NX OS 8.4(2b), Cisco MDS 9710, MDS 9706, and MDS 9250i and their IBM c-type counterpart have renewed their approval for use within mainframe environments with the full feature set. It is a great achievement, putting Cisco MDS 9000 series at the center of customers’ preferences when it comes to both FICON and Fibre Channel switching. Specifically, the new certification adds support for:

◉ IBM Fiber Channel Endpoint Security

◉ CUP Diagnostics

◉ Support for z/OS health checker

◉ 16G and 32G ELW optics for extended reach on dark fiber

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Cisco CCNP Collaboration 350-801 Certification Practice Test

 

Cisco CLCOR Exam Description:

This exam tests a candidate's knowledge of implementing core collaboration technologies including infrastructure and design, protocols, codecs, and endpoints, Cisco IOS XE gateway and media resources, Call Control, QoS, and collaboration applications. The course, Implementing Cisco Collaboration Core Technologies, helps candidates to prepare for this exam.

Cisco 350-801 Exam Overview:

• Exam Name:- Implementing Cisco Collaboration Core Technologies
• Exam Number:- 350-801 CLCOR
• Exam Price:- $400 USD
• Duration:- 120 minutes
• Number of Questions:- 90-110
• Passing Score:- Variable (750-850 / 1000 Approx.)
• Recommended Training:- Implementing Cisco Collaboration Core Technologies (CLCOR)
• Exam Registration:- PEARSON VUE
• Sample Questions:- Cisco 350-801 Sample Questions
• Practice Exam:- Cisco Certified Network Professional Collaboration Practice Test

Related Articles:-

1. Pass CCNP 350-801 CLCOR Exam and Enjoy Benefits It Draws
2. It’s High Time to Take Cisco 350-801 Certification Exam
3. Your Journey to Being CCNP Collaboration 350-801 Certified Made Easier

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Cisco DNA Spaces helps businesses weather the pandemic

As we wrap 2020, I want to reflect on the year gone by and what it meant for us folks at Cisco DNA Spaces. I think we can all agree that 2020 was a year like no other. It was a time of crisis, it was a period of upheaval; but it was also a period of innovation and transformation for location analytics products.

DNA Spaces is Cisco’s indoor location and IoT services cloud platform.  It enables Cisco Catalyst and Meraki wireless customers to use their existing network to drive digitization within their buildings.

In a world where our websites and mobile apps are becoming smarter by the day, DNA Spaces was launched with the vision to make buildings smarter, for our customers to drive seamless Wi-Fi onboarding for people and IoT devices, for loyalty based differentiated experiences and for behavioral analytics across your business locations.

Prior to Covid-19, we fulfilled our industry’s need for location analytics, behavioral insights, engagement and onboarding tools. In the two years since launch we are the most deployed indoor location services platform in the world, with over 120,000 global business locations on the platform at present. Most customers used the platform to set up Wi-Fi onboarding, engagement rules, locate assets or collect monthly analytics reports and stats on how their locations were performing. Setup DNA Spaces one time and you are all set from an indoor location services perspective.

And then the pandemic hit.

New circumstances require new solutions

Schools and universities closed without notice. Companies went remote overnight. Stores had to close for in-person shopping. Venues had to cancel their events. The Covid-19 crisis was turning out to be most difficult for our customers that operated out of physical locations.

As the state and federal governments started imposing restrictions and social distancing became a survival tactic, everyone woke up to the importance of understanding how people move and interact within buildings—not just in retrospect but in real time. Navigating the global pandemic required enterprises, policymakers and health officials to understand indoor location behavior trends intimately and use those insights to drive safety and compliance.

The product team at Cisco DNA Spaces saw this as an opportunity to help the community adapt for long-term business resiliency. For a product whose mission is to digitize physical spaces, it was clear that if there was ever a moment we could make an impact, it was now.

Pivoting to meet immediate demands

Our team decided to quickly pivot and reprioritize our product roadmap to include apps that would help customers respond to the pandemic and prepare them to safely get back to business. At the heart of our product pivot strategy were our users. We engaged in conversation with them at every step – acknowledged their needs, collected their feedback, understood their point of view.

Any product team will tell you that taking new features to market with a very short runway isn’t exactly an ideal scenario. But we learnt that if your purpose is clear, if your whole team is onboard and if executed well, the experience can be extremely gratifying.

We tapped into some of our core features and repurposed them to build apps more relevant to the new needs created by the pandemic. This resulted in a suite of apps that facilitate a safe return to work in a suite of Back to Business apps and features, including:

◉ Proximity Reporting App for contact tracing based on wi-fi presence

◉ Right Now App for real-time people count and behavioral monitoring on a single pane across your business locations

◉ Density threshold-based triggers for safe capacities and social distancing

◉ Instant Captive Portals for contact-less customer experiences

Smoothing the path to adoption

We built and shipped these apps in the shortest time possible. But our work was far from over. How could we scale adoption at a time when customers were working from home and short on both time and money?

Our adoption strategy was based on two key principles:

1. We ensured that all new features would work with zero support– no training, no long customer meetings and no demo. We wanted it to be possible for customers to sign-up, activate and deploy the new Covid-19 apps in 30 minutes or less. This required heavy focus on simplifying and scaling onboarding, providing in-product guidance and proactively addressing support issues with 24/7 service-level agreements (SLAs).

2. We opened up our tier offerings for everyone as a free trial so customers who hadn’t yet adopted DNA Spaces could get started and do contact tracing, monitor real time occupancy within their buildings and deliver contactless experiences. Every Cisco wireless customer deserved to make their buildings safe for business.

Build it and they will come

Over 300 Cisco enterprise customers deployed the new features across 50,000 business locations in the first 60 days after release, leading to improved management of social distancing in places like retail stores, workspaces, hospitals, universities, malls across the world.

The positive response and validation motivated us to stretch ourselves even further and make our apps ready for Meraki as well.

Countless hours and many sleepless nights went into building and shipping these features but all of our efforts were rewarded when we received the ‘Customer Choice’ recognition on Gartner Peer Insights. To be recognized for the value that DNA Spaces continues to deliver was the icing on the cake. The real reward has been the opportunity to share the journey with our customers and be part of their commitments to caring for their employees, customers and communities.

Looking back, but actually looking ahead

As I look back on 2020 one last time, I see what a tough year it has been for all of us. But I also realize that if we broaden our perspective just a little, life becomes that much easier. That said, I believe that for the product and engineering team at Cisco DNA Spaces, 2020 was a year of courage and shared responsibility. But most of all, 2020 was the year of indoor location services – a year when our product found its true relevance and meaning. We will go into 2021 with all our learnings and I believe, we will all be better for it.

Source: cisco.com

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Enabling Innovation in Customer Experience while Optimizing the Multi-Cloud: Part Two

As you read in part one of this blog, due to the pandemic and the resultant exponential increase in digital transactions, Customer Experience is far more paramount than ever before, across all demographics. It is imperative that as financial institutions embrace multi-cloud, the impact of how services are consumed from different clouds but presented in a consistent manner for the desired Customer Experience is vital.

Impact of the Multi-cloud environment on CX

As institutions go Cloud-All-In to enable this digital transformation, an application customer transaction will bounce across multiple clouds before reaching the end goal. In the recent State of the Cloud 2020 Report by Flexera, customers indicated that their #1 initiative is to reduce cloud bills, but their #2 is go move more workloads to the cloud. This is mainly due to the fact that existing individual cloud-provided tools are not integrated and create data silos. Also, most companies are unable to connect the dots between poor digital performance and the cost to the business. Most importantly, executives want — but don’t have — real-time performance metrics of their applications. There were consistent patterns found when CXO’s were asked how they assure application performance, namely:

◉ They over-provision – on an average 20% more, which is expensive.

◉ They monitor for alerts, which doesn’t always prevent the problems in the first place. In fact, people tell us that they ignore most of the alerts.

◉ They troubleshoot issues with people, which no longer scales given the volume and complexity of workloads.

◉ And they suffer with slow applications. Few companies tell us that they can “assure performance”.

When application workloads get the resources they need, when they need them:

◉ Your applications would perform as designed – no more resource contention.

◉ You’d be able to get the most out of your data center infrastructure.

◉ Sticker shock would be a thing of the past for your cloud projects.

◉ With the infrastructure constraints gone, you would not have to relax your policies.

◉ And best of all, your developers would have time and flexibility to innovate instead of chasing alerts.

The issue is around providing that flexibility for the DevOps teams to experiment at scale  as costs are kept in control, ensuring compliance is maintained and operationally the services are manageable, while assuring application performance is above par. As you constantly aim to find that equilibrium, there are 5 key areas one must keep in mind:

1. Assuring your applications: Do you understand your application portfolio ‘beyond the CMDB’ ? How will you be prioritizing your application migration? What KPIs will you use to baseline and measure success?

2. Streamline your operations: Will you be enabling developers to deploy infrastructure on demand? On multiple clouds? How do you plan to cost-optimize your infra?

3. Multi-cloud & cloud hosting: How will you develop the right level of abstraction across multiple clouds? How will developers manage container platforms across multiple clouds? How will you host legacy workloads?

4. Multi-cloud Optimized Networks: How will you achieve common operations, policy, visibility, and performance across multiple clouds? How will you assure and secure user experience to any cloud from anywhere?

5. Zero Trust Security: How will you deliver a cloud-ready security policy across multiple clouds, without slowing developers down? How does your cloud security strategy fit with your overall security strategy?

Taking a holistic solution approach

The true value of the application is not just on the hosting but on the consumption. Providing end to end connectivity, security, assurance and visibility to consume the apps is the key, looking at it consistently is the right way to provide the desired outcomes.

Cloud Hosting: Create cloud-agnostic, cloud native software solutions to enable and optimize your multi-cloud. Cloud-agnosticism means different services consumed from different clouds but presented in a consistent manner across clouds.

Cloud Consumption: Providing end-to-end connectivity, security, assurance, and visibility to consume those services across all clouds.

All cloud providers within themselves have strong capabilities, but as you undoubtedly are embracing multi-cloud, it’s imperative to be able to create consistent services across multiple clouds or as some people like to say – keeping the cloud providers honest. Thereby giving your development teams the flexibility to meet and surpass business asks and expectations, when it comes to the digital experience from their applications, but do it while keeping costs in check, maintain compliance and operational teams happy too.

Thus, evolving your applications experience not just from a FUNCTIONAL one to a JOYFUL one, but further raising the entire digital experience to a MEANINGFUL one. Thereby increasing your brand value and in-turn your desired customer recall.

Realizing this vision, backed by a business case

Cisco has always been at the forefront of providing the underlying infrastructure in enabling the expected connected experience, enabling businesses to get the most out of their ever-changing foundational layer. Cisco’s Performance IT program takes a consultative approach to assessing how your current multi-cloud environment is set up to help achieve your expected application experience. Keeping business outcomes in mind, Performance IT takes a 360˚ view of architectural transition, operational efficiency, and financial oversight in one go. It provides organizations with an architectural blueprint and a target operating model to demonstrate how this architecture can be run effectively. The cherry on top is the financial benefit in making this possible and setting up your teams to assure application performance in a multi-cloud environment of the future.

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Enabling Innovation in Customer Experience while Optimizing the Multi-Cloud: Part One

Digital Experience is the Brand

We live in a world where customers expect a digital experience. That experience makes or breaks brands today. According to The App Attention Index, people today are far less tolerant of problems with digital services than they were just two years ago, and they’re now far more likely to take decisive action – deleting apps, turning to the competition, and sharing their negative experiences far and wide.

The index gives us some key insights into these changes in consumer behavior:

◉ An average person used 34 digital services every day

◉ 61% admit they reach for their mobile phone before talking to anyone else when they wake up

◉ 55% can only go without a mobile device for up to 4 hours before they find it difficult to manage tasks in their everyday life

◉ 71% admit that digital services are so intrinsic to their daily lives, they don’t realize how much they rely on them

It’s evident that the penalty for poor application experience is very high, with over 49% of surveyed users stating they have switched suppliers due to poor digital experience. Not to mention, a 100ms delay in load time resulted in a 7% drop in conversion, which when compounded, substantially impacts the bottom line.

The digital experience is not just scanning a document or having a video call with a regional manager; it means actually doing an end to end transaction completely digitally. Today, application loyalty is the new brand loyalty, meaning that consumers are loyal to the brands that deliver digital experience perfection. In the same report, 70% of consumers said they want digital experiences to be more personalized than those that happen face-to-face. Furthermore, 50% stated that they would be willing to pay more for an organization’s product or service if its digital services were better than a competitor’s.

The Pandemic’s effect on Customer Experience

As the pandemic has hit us, it pushed all age groups towards extreme digital adoption. This is no longer a gen x or gen y statement; it is true across all ages, making it far more important to act upon than ever before.

In a recent McKinsey & Company study, interesting demographics emerged during these pandemic times, which led to some key observations:

◉ Digital preferences of older Western European consumer cohorts (ages 51-64 and 65+) aligning for the first time with those of younger demographics for most banking services

◉ Declines across markets in consumers’ desire to visit branches for transactions—shifts that may stick for the long-term

◉ Digital is expected to become the default channel for most customers and the sole sales and service channel for many

Because of this scenario, users don’t just compare one bank’s app experience with another bank’s app experience, but as the apps on their phones sit next to the apps from other industries (Amazon, Facebook, Uber, etc.) subconsciously, the expectation is set in that the banking app should be as good in the experience as the others, if not a leap ahead: That is the bar we are measured against.

The good news is that the technology to not only meet the app experience bar set by these companies, but to surpass them is available, and our development teams are always keen to get their hands on them and embed them within our customers’ journeys towards making the app experience exceptional. But as the customer experience simplifies, there is a multifold explosion in application complexity:

◉ Businesses are investing in making things better, easier, and more engaging for their customers

◉ This innovation is driven by investments that only increase complexity

◉ Highly distributed, multi-cloud, micro-services, APIs, containers, IOT environments, and relentless code releases that introduce constant change

◉ And all of this is happening at a staggering scale

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Industrial IoT: Top 3 trends for 2021

After 2020’s twists and turns, here’s hoping that 2021 ushers in a restored sense of “normal.” In thinking about what the upcoming year might bring for industrial IoT, three key trends emerge.

Trend #1: Securing operational technology (OT)

IT will take a bolder posture to secure OT environments.

Cyber risks in industrial environments will continue to grow causing IT to take bolder steps to secure the OT network in 2021. The CISO and IT teams have accountability for cybersecurity across the enterprise. But often they do not have visibility into the OT network. Many OT networks use traditional measures like air gapping or an industrial demilitarized zone to protect against attacks. But these solutions are rife with backdoors. For example, third-party technicians and other vendors often have remote access to update systems, machines and devices. With increasing pressure from board members and government regulators to manage IoT/OT security risks, and to protect the business itself, the CISO and IT will need to do more.

Success requires OT’s help. IT cybersecurity practices that work in the enterprise are not always appropriate for industrial environments. What’s more, IT doesn’t have the expertise or insight into operational and process control technology. A simple patch could bring down production (and revenues).

Bottom line? Organizations will need solutions that strengthen cybersecurity while meeting IT and OT needs. For IT, that means visibility and control across their own environment to the OT network. For OT, it means security solutions that allow them respond to anomalies while keeping production humming.

Trend #2: Remote and autonomous operations

The need for operational resiliency will accelerate the deployment of remote and autonomous operations – driving a new class of networking.

The impact of changes brought on in 2020 is driving organizations to increasingly use IoT technologies for operational resiliency. After all, IoT helps keep a business up and running when people cannot be on the ground. It also helps improve safety and efficiencies by preventing unnecessary site visits and reducing employee movement throughout facilities.

In 2021, we will see more deployments aimed at sophisticated remote operations. These will go well beyond remote monitoring. They will include autonomous operational controls for select parts of a process and will be remotely enabled for other parts. Also, deployments will increasingly move toward full autonomy, eliminating the need for humans to be present locally or remotely. And more and more, AI will used for dynamic optimization and self-healing, in use cases such as:

◉ autonomous guided vehicles for picking and packing, material handling, and autonomous container applications across manufacturing, warehouses and ports

◉ increased automation of the distribution grid

◉ autonomous haul trucks for mining applications

◉ Computer-based train control for rail and mass transit

All these use cases require data instantly and in mass, demanding a network that can support that data plus deliver the speed required for analysis. This new class of industrial networking must provide the ability to handle more network bandwidth, offer zero latency data and support edge compute. It also needs security and scale to adapt quickly, ensuring the business is up and running – no matter what.

Trend #3: Managing multiple access technologies

Organizations will operate multiple-access technologies to achieve operational agility and flexibility.

While Ethernet has always been the foundation for connectivity in industrial IoT spaces, that connectivity is quickly expanding to wireless. Wireless helps reduce the pain of physical cabling and provides the flexibility and agility to upgrade, deploy and reconfigure the network with less operational downtime. Newer wireless technologies like Wi-Fi 6 and 5G also power use cases not possible in the past (or possible only with wired connectivity).

As organizations expand their IoT deployments, the need to manage multiple access technologies will grow. Successful deployments will require the right connectivity for the use case, otherwise, costs, complexity and security risks increase. With wireless choices including Wi-Fi, LoRaWAN, Wi-SUN, public or private cellular, Bluetooth and more, organizations will need to determine the best technology for each use case.

Cisco’s recommendation: Build an access strategy to optimize costs and resources while ensuring security. Interactions between access technologies should deliver a secured and automated end-to-end IP infrastructure – and must avoid a “mishmash” leading to complexity and failed objectives.

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The Why of AI and ML

In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have been in the spotlight. I think by now folks understand that neither are some strange form of technological magic, but rather a science and some working knowledge of the domain is now well understood. However, up to this point, the question has been “what are AI and ML?”  But what I want to take some time to ask, is why? Why do we need them? Why will they still be a part of products and services; not just in security but throughout our digital lives?

The short answer is because we can no longer operate at human-scale to be competitive. It is necessary that we operate to some degree at machine-scale and this is where advanced computer science techniques become valuable. AI and ML are just a few of these techniques and to maximize their benefits, we must know how to use them safely and effectively. Like any advanced technology, they can be used for good or for bad or maybe I should say that it could be used for your benefit or your demise.

There is a pattern that joins humans to machines, machines to machines, machines back to humans, and humans to humans. We have hundreds of years of social science that we can use when examining human to human patterns. Machine to machine includes a multitude of well-known patterns in computer science discussed on a daily basis. So for now, let’s concentrate on the patterns that integrate humans with machines and vice versa.

Human-to-machine communication is largely based on the human’s ability to communicate their “intent” to the machine. This is done via a model that the machine can process and that the human can express and understand. The precision of this model is critical to the overall success. A model that is too coarse limits the machine’s accuracy in its automation; while a model that is too precise may lead to humans making errors in their expression or just be too tedious to maintain. A great example of a model done well is cloud-native orchestration like Kubernetes. The admin can specify his/her intent for production in a model and Kubernetes orchestrates these microservices in an adaptive manner depending on future demand of the environment – scaling up and down depending on criteria.

One last thing to add about these models that sit in-between human-to-machine is that in the example above, the initial model may have been instantiated by the human, but over time, machines via their observations, can create their own models at scales well beyond human perception. You could say that these machine derived models are “machine-learned.”

The machine-to-human pattern is largely constrained by human cognition and human understanding. No matter how fancy your machine learning system may be, if the human cannot understand how the machine arrived at an answer, it cannot be trusted. Machines must “explain” their findings and analytical outcomes in a way that humans can understand. Failing to do so means that automation is not being safely managed and should not be coupled with actions that are critical to human life or to the business. To operate at machine-scale effectively and safely, machines must be able to communicate their operational integrity and analytical outcomes in ways that their human steward can comprehend. This is challenging because in some cases, machines are interfacing with experts and in some cases, non-experts. In the end, you must design systems that are observer-centric and accommodate for the different personas that use the system.

Getting this right means that we can leverage machines as tools that help us go beyond human perception and even what is humanly possible to build as a workforce. This would not have been such a useful capability if it were not for the Internet. Because of the Internet, businesses are asked to understand questions that are global in scale, that deal with petabytes of data, quantities of data processing that are just no longer at human-scale. Businesses are also having to operate with dynamic ranges never experienced in our recorded history: On Monday you may have to service 30,000 customers, on Tuesday THE ENTIRE INTERNET SHOWS UP, and on Wednesday 20,000 customers. Without the help of machines, we could not take advantage of these opportunities.

The term Machine Learning has been used synonymously with Artificial Intelligence when in reality, ML is a child of AI. So, if AI is the parent of ML, does ML have any brothers and sisters? The answer is yes and over the years, we will move beyond the data science-biased ML as we meet and get to know these new siblings that will help us humans operate safely and securely at machine-scale.

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