SS8 Launches BreachDetect, An Analytics Platform For Detecting Security Breaches

On June 1, SS8 elaborated details of BreachDetect, a product that specializes in the retrospective detection of security breaches. Using analytics that facilitate the detection of security breaches and their associated devices of interest, BreachDetect has the capability to identify network-based breaches that may have escaped identification from other security tools and applications. BreachDetect generates and analyzes High Definition Records (HDR) based on data collected from software sensors that reside on the network. The platform’s learning and analytics engine correlates HDR data with data from users and devices in conjunction with sensors that have the ability to manage over 1,000 security protocols. Moreover, BreachDetect correlates threat intelligence regarding devices and breaches that have remained undetected. SS8’s capability to identify previously unidentified security breaches empowers organizations to take advantage of historical data and analytics to predict future attacks as noted by Faizel Lakhani, President and COO of SS8, below:

We get smarter about security every day, and while that knowledge helps us stop the known attacks, it doesn’t account for the breaches that went undetected. What’s needed in today’s complicated breach lifecycle is the ability to not only turn back the clock to uncover the unknown threats, but analyze the past to better forecast for new breaches. This time machine for breach detection takes our expertise in extracting intelligence from communications and delivers it to the enterprise to uncover the unknown threat.

Lakhani comments on the way in which SS8’s ability to deliver breach detection technology enables customers to “analyze the past to better forecast for new breaches” by building on SS8’s venerable history of deriving business intelligence from communications-related data. BreachDetect incorporates SS8’s impressive history of delivering communications analytics to the world’s premier intelligence and law enforcement agencies for counter-terrorism purposes as told to Cloud Computing Today in a phone interview with Lakhani. As such, BreachDetect translates SS8’s expertise identifying suspects of interest in the intelligence community to the related, but qualitatively different task of identifying devices of interest within IT infrastructures. The graphic below illustrates the visualization capabilities of SS8 with respect to breach detection:SS8-BreachDetect-iPad

The dashboard represents BreachDetect’s ability to identify instances of data exfiltration across a multitude of destinations that includes applications and file types. The graphic underscores SS8’s ability to transform its enterprise-grade platform for the intelligence community to IT security use cases that have the ability to not only detect stealth security breaches that have not yet been identified, but also proactively forecast breaches in ways that empower enterprises to implement controls and mitigations to pre-empt security breaches before they materialize.

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HP Releases Predictive Big Data Analytics Platform Featuring Distributed R

On Tuesday, HP announced details of HP Haven Predictive Analytics, a platform that delivers machine learning and statistical analysis for large-scale datasets. HP Haven Predictive Analytics features distributed R, an analytics platform based on the R programming language designed to tackle the most complex Big Data predictive analytics tasks in the industry. Moreover, the HP Haven Predictive Analytics platform boasts support for SQL and HP Vertica in addition to preconfigured algorithms that allow developers to leverage out of the box, R-based analytics. The hallmark of the offering, however, consists of the distributed R analytical engine that leverages parallel R processing to allow the power of R’s predictive analytics to tackle big data sets. The conjunction of the platform’s data acceleration functionality with its distributed use of the open source R programming language stands to improve analytic performance on large datasets and enable statisticians to derive actionable business intelligence from petabytes of data with speed and analytic sophistication. As such, HP Haven Predictive Analytics augments the analytic power of the SQL on Hadoop Vertica platform by delivering a Big Data predictive analytics platform capable of analyzing structured and unstructured data via the cloud or an on premise deployment.

Q&A With Umesh Mahajan, CEO of Avi Networks, Regarding Its Cloud Application Delivery Platform

Cloud Computing Today recently had the opportunity to speak with Umesh Mahajan, CEO of Avi Networks, about the company’s cloud application delivery platform (CADP). Avi Networks uses analytics to help ensure consistent end-user experiences of applications by way of a platform that delivers the application delivery and load balancing technologies used by internet giants such as Facebook and Yahoo to the enterprise. The Avi Networks HYDRA-powered Cloud Application Delivery platform empowers enterprises to optimize load balancing and application delivery within private cloud deployments as well as hybrid cloud infrastructures. Cloud Computing Today engaged Avi Network’s CEO Umesh Mahajan about the cloud application delivery space, the need for hyperscale application delivery platforms within the enterprise and HYDRA’s analytics capabilities.

Cloud Computing Today: How do you envision the cloud application delivery space? What is the key differentiation of Avi Networks within the cloud application delivery space?

Umesh Mahajan (CEO, Avi Networks): Over the past decade, requirements for application delivery have gone through a complete transformation driven by changing modes of application consumption and an evolution of application architectures. In an attempt to keep up, traditional ADC vendors have brought forth incremental improvements in performance, scale, security and availability. I call this device-centric innovation, that is, making existing appliances better, bigger, faster. However, today we are faced with mega trends such as hybrid cloud adoption and a mobile-first access policy in most large enterprises. This has resulted in the emergence of the software-defined data center, which legacy networking technologies are hard-pressed to support.

In this new world, Avi Networks bring three key pieces of innovation. First, we use real-time analytics that tracks and uses a number of telemetric data to dynamically adapt the application delivery services being provided. This enables IT to guarantee application SLAs and accounts for sudden spikes in user traffic. Second, we have developed the industry’s first distributed load-balancing architecture that’s based on SDN principles with a clean separation of control from data plane. This provides a dramatic simplification of network operations via a single centralized controller while the data plane services can span, serve and scale multiple data center and cloud locations. And finally, as opposed to a “pay-upfront” model that exists today with appliance based application delivery solutions, we price our software-only solution based on the actual network services our customers consume.

Cloud Computing Today: Avi Networks attempts to bring the application delivery and load balancing technologies enjoyed by the likes of Facebook and Google to the enterprise. Describe the business need to bring the application delivery capabilities of companies such as Google and Facebook to enterprises that have vastly different workloads and business needs than internet companies that ingest petabytes of data daily.

Umesh Mahajan (CEO, Avi Networks): Companies such as Google, NetFlix and Facebook who deal in hyperscale environments are important because they have redefined the online end-user experience. It amazes me how a Google app can almost predict my next move and suggest ways to auto-complete my text. The other important benchmark hypersale vendors have established is the expectation that their applications will never, ever go down. These are realms that most enterprise apps can dare dream about today.

We build Avi Networks with the goal of enabling the same level of application experience for enterprise apps enjoyed by Web 2.0 and hyperscale users. We’ve also taken inspiration from and have integrated ways to make data centers more efficient through software that can run on any hardware processor and appliance. Of course, the use of real-time analytics to drive smarter even predictive load balancing is another hyperscale innovation that we’re using. A relevant example is the Facebook Autoscale project that the company designed to enable energy- and CPU-efficient load balancing. Finally, these companies have shown the power of automation that drives a “self-service” and agile operating model for the network admins, which also distinguishes Avi from legacy ADC vendors.

Cloud Computing Today: What is most notable about HYDRA’s built-in analytics capabilities?

Umesh Mahajan (CEO, Avi Networks): At the highest level, we’re committed to making the job of the network administrators dead simple so that they can focus on strategic initiatives instead of simply keeping the lights on and troubleshooting application performance issues. It’s very common that the networking teams get the brunt of the blame for poor application performance, irrespective of the real reason for the issue. That’s where Avi comes in by arming network administrators with real-time data and troubleshooting capabilities to shorten what some people refer to as the “mean time to innocence.”

But what’s truly notable about the HYDRA architecture is that it is a true software-defined network model, composed of a centralized controller and a distributed, scalable data plane (called service engines) that can be co-located with the applications within and across the cloud. This tight alignment not only enables service engines to serve as micro load-balancers but also as integrated data collectors that pick up the ambient statistics about every user-to-application transaction. This way they become hundreds of eyes in the data center, ever vigilant. This data is streamlined via reduction filters and compression techniques and then sent to a continuous data store within Avi Controller. The output is very granular and gives real-time insights about the end-to-end timing of application transactions, application health score, client logs, and client insights that can predict and proactively prevent any degradation in application performance – at any scale, any location for every user.

Bio: Umesh Mahajan, Chief Executive Officer & Co-founder of Avi Networks

A seasoned executive and entrepreneur with 25+ years of experience in tech industry, Umesh has helped develop the vision, strategy, and execution plan for several innovative technology products. Before co-founding Avi Networks, Umesh was the Vice President / General Manager for a $2B Data Center switching business at Cisco where he led engineering, product management, marketing and operations for Nexus 7000, MDS switching products, and the NX-OS operating system.

Prior to his work at Cisco, Umesh led the software team at Andiamo in architecting and delivering SAN-OS. Umesh has a Master of Science degree in computer science from Duke, a Bachelor of Science degree from IIT Delhi, and has 29 patents to date.

Numerify Announces Impressive Growth For Its Cloud-Based Analytics Platform

Cloud-based analytics vendor Numerify recently announced the addition of notable product enhancements to its Numerify360 for IT platform marked by solutions dedicated to the needs of managed service providers and retail and higher education institutions. In addition, Numerify revealed a slew of updates to its portfolio of products that facilitate the operation of IT as a business by enhancing its change management, location analytics, incident analysis and text analytics solutions. Unlike many IT analytics vendors that focus on infrastructure and application-related metrics such as latency and throughput, Numerify differentiates itself by building applications focused around empowering IT leadership to obtain visibility regarding its performance as a business that serves other business units within the organization. For example, Numerify’s location analytics capability enables IT to derive granular business intelligence about technology performance in different geographies to facilitate proactive interventions to mitigate technology-related disruptions. Similarly, Numerify’s change management analytics facilitate the identification of changes resulting in service interruptions to minimize the disruptive effect of changes to applications and infrastructure.

News of Numerify’s updates to its platform arrives in conjunction with company announcements of “significant growth” since its April 2014 stealth launch marked by quarterly revenue growth in the triple digits and a bevy of new customer signings. Backed by Lightspeed Venture Partners and Sequoia Capital, Numerify delivers a unique level of analytics that empowers IT to focus on the metrics that impact the satisfaction of their customers rather than remaining mired in technology-related metrics that require the imposition of another level of abstraction to understand their business value and significance. The bottom line here is that the increasing heterogeneity of contemporary IT infrastructures means that the application and infrastructure analytics space is red hot, and likely to continue burning brightly given the sprawl of on-premise, cloud-based and distributed applications. Expect Numerify to continue building on its impressive market traction in the remainder of 2015 and expanding a customer roster that currently includes Netflix, Aruba Networks and the University of San Francisco.

Internet Of Things Predictions For 2015 From ParStream

The following represent Internet of Things Predictions from ParStream, the company behind the analytics platform built for the internet of things.

1. The Rise of the Chief-IoT-Officer: In the not too distant past, there was an emerging technology trend called “eBusiness”. Many CEO’s wanted to accelerate the adoption of eBusiness across various corporate functions, so they appointed a change leader often known as the “VP of eBusiness,” who partnered with functional leaders to help propagate and integrate eBusiness processes and technologies within legacy operations. IoT represents a similar transformational opportunity. As CEO’s start examining the implications of IoT for their business strategy, there will be a push to drive change and move forward faster. A new leader, called the Chief IoT Officer, will emerge as an internal champion to help corporate functions identify the possibilities and accelerate adoption of IoT on a wider scale.

2. Analytics Will Be the #1 Priority for IoT Initiatives: 2014 was about sensors and devices. The initial objective of many IoT projects was about simply placing sensors on critical assets such as aircraft engines, cell phone towers, cargo containers, and more to start collecting data from real-time events. Early IoT pilots demonstrated the wealth of information made possible by sensors and connections. 2015 will be about value. The attention will quickly shift from simply “enabling IoT” to truly “generating benefits from IoT”. Timely analytics is key in gaining actionable insights from data, and hence, a prerequisite for realizing the full potential of IoT. To drive more business value from IoT, companies will analyze more real-time data and implement new, innovative ways of delivering analytics to the “edge” or source of data.

3. IoT Platform to IoT Platform Integration Will Drive Relevance: Forrester recently proclaimed “IoT software platforms will become the rage in 2015”. Indeed, many IoT software companies are thinking “platform” rather than just “modules” to help deliver something closer to a “whole offer” for customers. However, an IoT platform’s real value will be driven by its integration with other IoT platforms. The reality is that there is no single, end-to-end IoT platform, which can deliver device management, data aggregation, analytics, visualization, etc. for the breadth of potential IoT use-cases. Hence, the power and value proposition of an IoT platform will be driven by its connection and integration with other complementary IoT platforms.

4. Industrial/Enterprise IoT Will Take Center Stage in the Media Spotlight: Driven by well-publicized acquisitions (e.g. Google/Nest) and high-profile new products (e.g. Fitbit, Apple Watch, etc.), consumer IoT has received a disproportionate amount of media attention compared to industrial IoT. While consumer IoT will eventually be a huge market, the hype greatly outweighs the near-term reality with respect to adoption. However, the tide is turning and industrial IoT will take the spotlight in 2015 as the media starts to more frequently cover the massive opportunity and traction of enterprise IoT in driving efficiency and creating new business models (e.g. Harvard Business Review’s cover story on IoT in their November 2014 issue).

Avi Networks Emerges From Stealth With Cloud Application Delivery Platform And $33M In Funding

Avi Networks today emerged from stealth to announce the general availability of its Cloud Application Delivery Platform. The Avi Networks Cloud Application Delivery Platform leverages a disruptive technology branded the Hyperscale Distributed Resources Architecture (HYDRA) that attempts to bring the application delivery and load balancing technologies enjoyed by internet giants such as Facebook and Google to the modern enterprise. HYDRA takes advantage of software defined networking marked by a separation of the control plane and the data plane in conjunction with distributed microservices that apply a multitude of services such as load balancing and SSL termination to incoming network traffic in parallel. HYDRA also features built-in analytics that give customers real-time visibility into resource consumption specific to applications and swathes of network traffic. The Avi Networks HYDRA-powered Cloud Application Delivery platform empowers enterprises to optimize load balancing and application delivery within private cloud deployments in addition to hybrid cloud infrastructures that additionally take advantage of the services of a public cloud environment to complement an on-premise infrastructure.

Founded by former Cisco executives, Avi Networks has raised a total of $33 million in funding from Greylock Partners, Lightspeed Venture Partners and Menlo Ventures. In addition to delivering revolutionary load balancing and application delivery technology to the enterprise, the Cloud Application Delivery Platform promises to assist cloud service providers achieve the performance benefits and economies of scale enjoyed by platforms such as Google’s Andromeda platform and Facebook’s Autoscale system. Expect more details about the Cloud Application Delivery Platform to emerge in subsequent months but for now, the application delivery and load balancing space features a new incumbent focused on improving end-user experiences given the proliferation of cloud-based applications that impose new demands on application-delivery infrastructures. Umesh Mahajan, Founder and CEO of Avi Networks, elaborated on the significance of the company’s value proposition by noting that, “In today’s mobile cloud era, the traditional appliance-centric, monolithic application delivery approach doesn’t work anymore,” and as such, the company conceived and operationalized a disruptive application-delivery and load balancing framework that competes with the likes of F5 and Citrix.

Glassbeam Integrates With Apache Spark And Enhances Its Analytics And Machine Learning Functionality

Santa Clara-based machine data analytics vendor Glassbeam recently revealed details of a new version of Glassbeam SCALAR marked by deep integration with Apache Spark. Apache Spark is a parallel data processing framework that facilitates real-time analytics, machine learning and real-time analytics by storing the results of data operators in memory and performing low latency, iterative calculations on in memory computational results. Known for its ability to automate the parallelization of tasks and jobs, Spark boasts operational efficiencies over MapReduce by a factor of 100 with respect to the execution of calculations on large datasets. Glassbeam SCALAR’s integration with Apache Spark enhances its computational capabilities as well as the platform’s machine learning functionality and capacity to perform real-time analytics on streaming datasets by means of the Spark Streaming and MLLib components of the Spark stack. Built on Cassandra, Spark’s addition to the Glassbeam’s cloud analytics platform gives it the benefits of Cassandra’s distributed data management architecture in addition to Spark’s computational, analytic and machine learning functionality. As such, today’s announcement strengthens Glassbeam’s position in the nascent but exploding internet of things analytics space by augmenting its ability to ingest, process and analyze massive amounts of data as well as enhancing Glassbeam SCALAR’s advanced analytics, machine learning and predictive analytics capabilities.