Software Defined Application Services (SDAS) are going hybrid. .

Organizations are turning to cloud not just as an option for applications but also for the network and application services that deliver applications to anyone, anywhere at any time. And not just "in" the cloud marketplace, available for immediate provisioning and deployment, but as part of the cloud itself; as a service.

One of the questions we asked of respondents in our survey this summer focused on the preferred deployment model across the breadth of application services. Security, I'm sure unsurprisingly, wound up with a significant number of services which organizations prefer to consume "as a service". Of those security services, the top three were SPAM filtering, DDoS protection and anti-fraud services.

The distinction between "cloud" as in marketplace and "cloud" as in a service is necessary for a number of reasons, not the least of which is that adoption of both can force organizations to deliver services across multiple architectures (with a variety of different management systems) if they want to preserve seamless application experiences for users.

For example, you might be able to subscribe to a DNS as a service (and many small and even medium businesses do), but it's management interface – whether API or service portal – are disconnected from everything else. Organizations might also choose to deploy apps in AWS or VMware vCloud Air and then choose to deploy application services to enhance security and improve performance from their respective marketplaces. But those, too, are likely to end up operationally disjoint from other, similar, services that may be delivered as a service or on-premise.

That disjointed operational state is double plus ungood. It inhibits visibility into the overall state of the business (applications) and the services upon which those applications rely. It can impede deployment, too, by introducing stops and starts in processes that might otherwise be orchestrated to improve time to market, because the tools and techniques used to provision and manage these other services are not well integrated with the rest of the IT toolbox.

That's why we continue to expand the ability of F5 Synthesis to deliver SDAS and have introduced yet another option for organizations seeking to ensure the security, performance and availability of applications across a growing portfolio of environments, architectures and business models.

F5 Synthesis: As a Service

F5's vision for application delivery is to enable organizations to take advantage of cloud and support a hybrid data center model without sacrificing the services applications need to stay secure, fast and available. That means not only expanding customer choices with respect to cloud environments and marketplaces, but making those application services available as a service and manageable as part of comprehensive, hybrid application service model spanning cloud, as a service and on-premise environments.

That's where F5 Silverline comes into play, extending F5 Synthesis ability to deliver SDAS on-premise and in the cloud with cloud-based services delivery platform. F5 Silverline will support enterprises by eliminating traditional constraints requiring an either on-premise or in-the-cloud deployment model for application services.

With an as-a-Service option to deliver F5 SDAS, customers gain the ability to shift the deployment of applications and adjacent services closer to the users and apps that benefit from them.

As a first step, building on our acquisition of Defense.Net, we've added a new security service option with F5 Silverline DDoS Protection. This new, hybrid offering combines on-premise DDoS protection capabilities with a high-capacity, cloud-based service that enables organizations to mitigate a complete spectrum of DDoS attacks. New data centers in Frankfurt and Singapore expand the global availability of this service.

F5 Silverline DDoS Protection

F5 Silverline DDoS Protection is a cloud-based traffic scrubbing service providing real-time, automated DDoS mitigation of volumetric attacks. Organizations benefit from cloud-based DDoS protection precisely because it's in the cloud, meaning attacks are scrubbed (stopped) before they ever get near the corporate network. That's important because the growing scale and volume of these attacks can overwhelm many organization's Internet links. While such attacks target services such as DNS and applications, simply oversubscribing the target's links has the same effect: the denial of service.

Scrubbing traffic external to those links, "in the cloud", provides ample reduction in traffic and effectively prevents services from becoming overwhelmed in the first place.

F5 Silverline DDoS protection offers three subscription models:

• Always On
  This offering is a first line of defense, continuously evaluating traffic to identify and eliminate bad traffic
• Always Available
  A first line of defense available on demand, this subscription enables organizations to turn on the service "on demand". This allows organizations to primarily rely on on-premise DDoS protection services but immediately react in the event of an attack.
• Ready Defense
  This is a "stand by", secondary protection option for organizations who are planning ahead and desire extra protection, just in case.

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Working with Big Data is challenging, especially when decision makers depend on market insights and intelligence from your data but don’t have quick access to it or find it unusable.
In their session at 6th Big Data Expo, Ian Khan, Global Strategic Positioning & Brand Manager at Solgenia; Zel Bianco, President, CEO and Co-Founder of Interactive Edge of Solgenia; and Ermanno Bonifazi, CEO & Founder at Solgenia, discussed how a revolutionary cloud-based BI along with mobile analytics is already changing the way organizations rely on data for decisions that affect operations as well as strategy. Also learn how combined predictive analytics, data modelling, mobile, and cloud BI are fast changing the key decision-making mechanisms in the enterprise.

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87% of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next three years. 89% believe that companies that do not adopt a Big Data analytics strategy in the next year risk losing market share and momentum.

These and other key findings are from a Accenture and General Electric study published this month on how the combination of Big Data analytics and the Internet of Things (IoT) are redefining the competitive landscape of entire industries. Accenture and GE define the Industrial Internet as the use of sensor, software, machine-to-machine learning and other technologies to gather and analyze data from physical objects or other large data streams, and then use those analyses to manage operations and in some cases to offer new, valued-added services.

Big data analytics now seen as essential for competitive growth

The Industrial Internet is projected to be worth $500bn in worldwide spending by 2020, taking into account hardware, software and services sales according to Wikibon and previously published research from General Electric. This finding and others can be found on the home page of the Accenture and GE study here: How the Industrial Internet is Changing the Competitive Landscape of Industries.

The study also shows that many enterprises are investing the majority of their time in analysis (36%) and just 13% are using Big Data analytics to predict outcomes, and only 16% using their analytics applications to optimize processes and strategies. Moving beyond analysis to predictive analytics and optimization is the upside potential the majority of the C-level respondents see as essential to staying competitive in their industries in the future.

A summary of results and the methodology used are downloadable in PDF form (free, no opt in) from this link: Industrial Internet Insights Report For 2015.

Key take-aways from the study include the following:

• 73% of companies are already investing more than 20% of their overall technology budget on big data analytics, and just over two in ten are investing more than 30%. 76% of executives expect spending levels to increase. The following graphic illustrates these results:

• Big data analytics has quickly become the highest priority for aviation (61%), wind (45%) and manufacturing (42%) companies.  The following graphic provides insights into the relative level of importance of big data analytics relative to other priorities in the enterprises interviewed in the study:

• 74% of enterprises say that their main competitors are already using big data analytics to successfully differentiate their competitive strengths with clients, the media, and investors. 93% of enterprises are seeing new competitors in their market using big data analytics as a key differentiation strategy.  The single greatest risk enterprises see from not implementing a big data strategy is that competitors will gain market share at their expense.  Please see the following graphic for a comparison of the risks of not implementing big data strategy.

• 65% of enterprises are focused on monitoring assets to identify operating issues for more proactive maintenance. 58% report having capabilities such as connecting equipment to collect operating data and analyzing the data to produce insights. The following graphic provides an overview of Big Data monitoring survey results:

• Increasing profitability (60%), gaining a competitive advantage (57%) and improving environmental safety and emissions compliance (55%) are the three highest industry priorities according to the survey. The following table provides an analysis of the top business priorities by industry for the next three years with the shaded areas indicating the highest-ranked priorities by industry:

• The top three challenges enterprises face in implementing big data initiatives include the following: system barriers between departments prevent collection and correlation of data for maximum impact (36%); security concerns are impacting enterprises’ ability to implement a wide-scale big data initiative (35%); and  consolidation of disparate data and being able to use the resulting data store (29%), third. The following graphic provides an overview of the top three challenges organizations face in implementing big data initiatives:

In a perfect world, Application Performance Management (APM) has all the right elements in place, providing value to the business and IT by giving us the metrics we need and showing us the health of our applications. It alerts us to anomalies when slowdowns occur, and shows us trends on performance. But there are other elements in play that can make the operations a little smoother and our days a little brighter.

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Cloud computing has been named as one of 12 disruptive technologies which will change the relationship between the CIO and the boardroom, according to a report by Advanced 365.

The evolving role of the CIO, and the C-suite in general, has long been a feature of modern business. Opinions differ, whether it’s a wag who proclaims CIO to mean ‘career is over’, or whether it’s a report which advocates more fluency and fluidity between executives.

The Advanced 365 paper takes a look at the different types of CIO today and how it fits in to various businesses:

• CIO as manager: A CIO who delivers today, may not be as much of an ideas person but manages the business for commercial success
• CIO as leader: Engaging in and delivering change throughout the organisation, planning for tomorrow and designing new positions within the company
• CIO as entrepreneur: Dreams about the future, seeks out change and innovates against those changes to improve commercially

The conclusion with these three categories is that each boardroom needs a manager, a leader, and an entrepreneur in its deck. Not every executive will possess all these skills – Steve Jobs, for instance, one could argue is all three – but it’s about deciding which of these is best for your company’s CIO. Managers first ask ‘what?’, leaders first ask ‘how?’, and entrepreneurs first ask ‘why?’.

Boards are expecting more tech-savvy reports from their staff. A Spencer Stuart study saw that one in five boards look for directors with technology expertise. The National Association of Corporate Directors (NACD) said more than a quarter (27%) of boardrooms are unhappy with the quality of technology information they receive from below.

If we’re to accept cloud as an inexorable trend in the future – and we should, if research on enterprise cloud adoption is anything to go by – then cloud supports the ‘CIO as manager’ typology, the report argues. This is due to reducing IT costs, increasing IT agility and automating processes.

“In short, it represents a more efficient and cost effective way to run IT, which has long been the goal of the CIO as manager,” the report notes, however adding: “It could however also enable the construction of new cloud based business models and ecosystems, which ensures relevance to the CIO as leader, and especially, the CIO as entrepreneur.

“In this sense, the basic users of cloud computing is radical in impact from more advanced uses, and demands a different CIO.”

The report also notes the discrepancy between CIOs and boards, arguing the two must work more closely together if they are to gain competitive advantage from emerging technologies. Equally, CIOs need to maintain a close relationship with other C-level executives, enabling them “to better understand the operating model of the company, and be better placed to contribute tellingly to its evolution.”

The 12 disruptive technologies included in the report are cloud computing, mobile internet, automation of knowledge, Internet of Things, advanced robotics, autonomous vehicles, next generation genomics, energy storage, 3D printing, advanced materials, advanced oil and gas exploration and renewable energy. You can read the full report here.

I had the opportunity to present on Nov 5th at DevOps Summit by SYS-CON Events in Santa Clara, CA. Here are my slides.
The world is Hybrid. Organizations adopting DevOps are building Delivery Pipelines leveraging environments that are complex – spread across hybrid cloud and physical environments. Adopting DevOps hence required Application Delivery Automation that can deploy applications across these Hybrid Environments.

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Last week as I was writing Amazon Declares War on VMware, VMware was preparing to announce the acquisition of a pro services team to aid in cloud migration (see coverage in CRN): VMware Acquires Professional Services Firm To Boost Cloud Migration, DevOps Expertise. You can get my thoughts on Amazon’s frontal assault on VMware and […]

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Now is the age of information analytics. We have (very arguably) reached a point where the insight arising from data analytics can be applied to almost every aspect of a company, in every business vertical.
But what shape should that analytics be? Increasingly we talk about embedded analytics, but what do we mean? Should we be embedding analytics inside a) applications themselves, or should we b) look to embed analytics as business rules inside complete corporate processes – or should it be both?

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#DevOps #SDN

We keep saying that, does it mean what you think it means?

Operationalization (which is really hard to say, go ahead – try it a few times) is a concept that crosses the lines between trends and technologies. Both SDN and DevOps share the notion of “operationalization” as a means to achieve the goal of aligning IT with business priorities, like that of accelerating time to market for all important applications.

But what does it really mean to operationalize the network, or app deployments, or really, anything?

Operationalization is a lot like DevOps in that it’s more of an approach to how you deploy and manage operations than it is some concrete, tangible thing. It is a verb, it’s something you do that has concrete, measurable impacts on the application environment, aka the data center, and the processes that move an application from development and into the hands of its intended consumers, whether internal or external.

When we say “operationalize the network”, what we mean is to apply a systematic approach to automating network tasks and orchestrating operational processes in a way that meets measurable, defined goals that align with business priorities.

Consider the business priority to deliver projects on time. You know, get projects to market before the competition (to meet the business concern of revenue growth) or roll out internal apps faster (to meet the business concern of productivity improvements). The top CIO priorities are intertwined, and IT is in the business of applications as much as it is about technology.

Automate all the network things

Accelerating the time to market (or time to roll out for internal applications) is an imperative that enables IT to meet several business and IT-related goals simultaneously. But to do that, IT has to operationalize all the things – including the network. Operations (whether network or security or application) has to focus on automating tasks and orchestrating processes to achieve the speed, scale, and stability necessary to roll out new or improved apps faster and, in some cases, more frequently. That means taking advantage of programmability (APIs, app templates and even data path) to integrate and automate the provisioning, configuration and elasticity of applications and the services that deliver them.

Does that mean you have to become a coder? Not necessarily. Much of the automation and orchestration of the network is being made available through ecosystems (like those around VMware, Cisco, OpenDaylight and OpenStack) that enable the integration necessary to occur through plug-ins, policies or templates rather requiring network engineers to become developers. No doubt some organizations will choose a more hands-on approach, in which case the answer becomes yes, yes you will have to become familiar with scripting tools and languages and APIs to enable the automation and, ultimately, orchestration required to achieve alignment with business and operational goals.

Measure all the deployment things

Automation and orchestration alone aren’t enough, though, to operationalize the network. Measures must be put into place that span the entire application deployment process. Those measures should align with other operations groups and align better with the business, measures that are typically associated with DevOps but are directly relatable to the network, too:

• Deploy frequency
• Volume of defects
• MTTR
• Number & Frequency of outages
• Number & Frequency of performance issues
• Time/cost per release (deployment)

Automation certainly impacts some of these measures, but not all. Process optimization is a critical component of DevOps and operationalization as well that impacts many measures but is people and analysis driven.

Optimize all the process things

Optimization requires understanding the processes that have likely ossified over time and re-evaluating each and every step to improve not just the speed but the efficiency, too (no, they aren’t the same, Virginia). Optimization of processes is about measuring and mapping processes to find the bottlenecks and idle time that causes the entire app deployment train to slow to a crawl.

The reality is that orchestrating poor processes just lets you fail faster and more often. So identifying those processes (that include handoffs between silos) causing bottlenecks in the deployment process (or where errors seem to constantly be introduced) is a critical component of successfully operationalizing the network (and other operations, for that matter). Giving the app infrastructure operations group an “easy” button to deploy the appropriate network services isn’t going to improve the process if that process is itself broken, after all.

The measures let you ascertain whether changes in the process are going to help or not. Modeling and math can do wonders to help determine where changes must be made to improve the overall results, but both require measurement first – and consistent measurement across groups and the deployment lifecycle.

Share all the app things

All of which requires collaboration. You can automate individual tasks and gain some improvements, yes, but you can’t orchestrate a provisioning and configuration process related to a given application or type of application unless you first understand what that application needs. And to do that you’ve got to talk to the people who develop it and deploy its infrastructure. You have to understand its architecture – is it three-tier? Two-tier? Microservice? Does it present APIs and take advantage of an app proxy or are the integrations and interactions all internal? How is success for this app measured? Productivity improvement? Revenue growth? User adoption?

The answers to these questions are imperative to understanding just what network services need to be deployed, and how. It isn’t enough to just give the app an IP address and put it on a VLAN. You’ve got to deliver value out of the network and that means providing services that will help that application meet its business goals, whatever they might be.

Operationalize. Everything.

Whether you’re approaching operationalization of the network from the perspective of implementing a SDN architecture or by applying the principles associated with DevOps you’re essentially going to have to embrace and adopt the same basic tenets: automation, sharing and common measurements that result in a cultural change across all of IT’s operational groups.

To succeed in an application world you’re going to have to operationalize all the things.

And that includes the network.

More in a presentation dedicated to this topic: Operationalize all the Network Things!

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Zenedge has announced the general availability of its latest Zenshield DOME platform with a simple goal: to protect your enterprise from what it perceives to be its weakest link.

That weakest link is a firm’s partner and supplier ecosystem, which Zenedge insists is a more likely target for hackers trying to infiltrate an enterprise in the cloud.

The product is a security platform as a service (SPaaS), and can be extended to a retailer’s partner and supplier network so organisations can oversee the entire ecosystem.

Zenedge explains how important third party security is becoming, after recent ecosystem weaknesses temporarily downed Target, Snapchat and Walmart among others.

“CISOs and hackers are discovering that the quickest path to breaking into a company’s classified data comes through remote, often inconspicuous, interconnected third parties,” said Zenedge co-founder and CTO Leon Kuperman. “It’s a reminder that networks are only as strong as their least protected link, and that all vendors need to be assessed, vetted and protected against cybersecurity risks.”

The system is self-updating, with Zenshield DOME identifying vendor access points and automatically closing ports that can expose your data. It also uses heuristic algorithms – in other words, finding a quick fix if an exact solution isn’t available – studies vendor traffic and adapts the network according to behavioural patterns.

“The IT industry has been aware of problems caused by external vendor vulnerabilities for some time,” said Rick Simpson, founder of Snow Commerce. “Seeing red flags pop up around the perimeter is one thing – being able to centrally, cooperatively act to avoid attacks against a large organisational target has so far proved more difficult.”

Zenedge has got plenty of backing from the industry, with the company pocketing $3.5m (£2.3m) in a series A funding round last month. With Black Friday and Cyber Monday just around the corner, there’s plenty of work for the Los Angeles firm to get stuck into for the time being.

Find out more about Zenedge here.