Venture Capital

Numerify Raises $37.5M In Series C Funding For Cloud-Based Analytics For IT Management

On October 22, cloud-based analytics vendor Numerify announced the finalization of $37.5M in Series C funding led by Tenaya Capital. The funding raise was completed with additional participation from Sequioa Capital and Lightspeed Venture Partners and new investors in the form of the Silicon Valley Bank and Four Rivers Group. The capital raise represents powerful validation of Numerify’s business model based on a cloud-based analytics platform that delivers actionable business intelligence regarding areas such as IT infrastructures, business units and business processes. In contrast to cloud-based analytic solutions that focus on delivering data in formats that enable reporting and analytics, Numerify differentiates by using its analytics platform to identify opportunities to improve operational efficiency, reduce costs, increase revenue and enhance analytics related to risk, fraud, and threat intelligence. Gaurav Rewari, CEO and Founder of Numerify, remarked on the significance of the capital raise as follows:

As one of the first IT business analytics providers on the market, we are delighted that this space is growing so quickly. With our pre-built analytic applications in the cloud that combine domain best practices with hundreds of metrics, reports, dashboards and a unified analytical data model embracing the full sweep of IT business operations, this new investment will support us through our next phases of exponential growth.

Here, Rewari highlights the platform’s “pre-built analytic applications” that use industry-specific best practices to deliver reports and dashboards featuring metrics, KPIs and analytic insights that help optimize IT business operations. The product spans the gamut of IT operations by including processes such as HR, call center operations, finance, assets, infrastructure and project management within its analytical purview. The funding will be used to accelerate product development and expand sales and marketing operations. Thursday’s funding raise brings the total capital raised by Numerify to $60M.

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Teridion Announces $15M In Series B Funding And GA Of Platform For Bi-Directional Content Acceleration

Israel-based Teridion today announces the general availability of its Global Cloud Network for bi-directional content acceleration. Teridion’s Global Cloud Network delivers performance improvements of a factor of 20 with a focus on improving bi-directional, personal internet experiences for content providers and their consumers. Teridion’s cloud-based platform delivers intelligent routing to cloud applications based on considerations related to bandwidth, latency and geography. The Teridion Global Cloud Network allows customers to pay for utilization and integrates with well known cloud providers, thereby allowing customers who host their applications on large public clouds to retain the infrastructure used for their application deployments. Teridion also announces $15M in Series B funding led by Singtel, Innov8, JPVC and Magma. The Series B round brings the total capital raised by Teridion to date to $20M and empowers the company to expand sales operations and aggressively accelerate its go to market strategy.

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Kentik Emerges From Stealth With SaaS Network Analytics Solution And $12M In Series A Funding

Kentik emerged from stealth to reveal details of a cloud-based platform for network visibility that delivers an exceptional degree of visibility into network performance and operations in comparison to existing products. Formerly known as CloudHelix, the Kentik direct service aggregates network-related data from customers into a non-relational database and subsequently performs analytics to give customers real-time visibility into traffic within their network infrastructures. Kentik allows customers to upload data directly to its SaaS platform or to a virtual appliance that encrypts the data prior to its transmission. The solution has gained early traction with customers such as Box and Yelp in addition to large internet service providers. Sam Eaton, Director of Engineering Operations at Yelp, remarked on the innovation enabled by Kentik as follows:

Kentik has given us the insight and visibility that we have not been able to achieve through other network performance monitoring products or open source tools. With over 100 million average monthly unique visitors coming to Yelp, we see traffic reaching many gigabits per second, so it’s critical for us to be able to look deeply into all network traffic in real time and gain real insight. That’s where Kentik has helped. We can see things we simply couldn’t see before.

Here, Eaton remarks on Kentik’s ability to deliver real-time, granular insights into Yelp traffic that exceeds “gigabits per second.” Similarly, leverages Kentik to obtain geography-specific insights into network traffic that allow for timely and proactive remediation of network-related problems before they intensify. Today, Kentik also announces the finalization of $12M in Series A funding led by August Capital. The company’s Big Data platform for aggregating and analyzing network data aims to disrupt networking analytics by delivering an unparalleled degree of insight into network behavior in ways that support high availability, performance optimization and security-related use cases.

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Redis Labs Raises $15M In Series B Funding For High Throughput, Low Latency, NoSQL Database Platform And Cloud

On June 25, Redis Labs announced the finalization of $15M in a Series B funding round led by Bain Capital Ventures and Carmel Ventures. The funding raise validates the traction of Redis Labs and its cloud platform, the Redis Cloud, a fully managed cloud platform for running Redis databases. An open source, in-memory, key value data store, Redis boasts the capability to facilitate a high volume of read and write requests with sub-millisecond latency. The single threaded event-driven architecture of Redis in conjunction with its other protocols allows Redis to claim speeds that exceed its in-memory database competitors by 5-10x. Popular use cases for Redis involve leaderboards, session management and player profiles with reference to gaming applications. Other use cases include message queues, search engines and caching in highly interactive web applications that need to scale to tens of millions of users, each of which may have a unique user profile and representation in dynamically updated, application-related lists that represent how many “objects” are being “followed” or “saved” by a user. Last week’s funding raise brings the total capital raised by Redis Labs to $28M. With paying customers that include Hotel Tonight, Bleacher Report and Docker and a healthy infusion of Series B funding, Redis Labs stands poised to capitalize on its meteoric growth since the company was founded in 2011. Within a broader landscape of growing adoption of NoSQL databases and a proliferation of datacentric, mobile and web-based applications that require real-time updates that cascade across a constellation of database objects, expect Redis Labs to continue to drive innovation with respect to enterprise-grade Redis deployments and to spearhead Redis adoption more generally.

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Rancher Labs Releases Container Infrastructure Platform In Beta After $10M Series A Funding Raise

On June 15, Rancher Labs announced the availability in Beta of Rancher, an open source platform for managing infrastructure for containers. Rancher’s platform delivers enhanced visibility into infrastructure performance for environments that include Docker containers. The platform enables communication between containers residing on different hosts or cloud platforms in conjunction with elastic load balancing functionality that optimizes the distribution of resources across different containers. Additionally, the Rancher platform’s functionality includes storage management, resource management and service-discovery that allows for the discovery of services subsequent to container self-registration as services within a specific infrastructure. Sheng Liang, co-founder and CEO of Rancher Labs, remarked on the significance of the Rancher platform as follows:

Much of the excitement around Docker is its use as a universal packaging and distribution format. However, as users deploy containers across different infrastructures, they quickly realize that different clouds, virtualization platforms and bare metal servers have dramatically different infrastructure capabilities. By building a common infrastructure backplane across any resource, Rancher implements an entirely new approach to hybrid cloud computing.

Here, Liang elaborates on the way in which the Rancher platform supports the ability to “deploy containers across different infrastructures” and thereby undergird a technology ecosystem that enables communication between containers housed in different infrastructures. Unlike many of the existing container management platforms, Rancher Labs focuses on infrastructure in contrast to application performance management and, as such, represents one of the increasing number of vendors dedicated to cloud-based infrastructure management and visibility, albeit in this case in the context of container-based applications. The Rancher team features an impressive roster of talent including a leadership team that built, the company that morphed into the well known Apache CloudStack software platform. The Beta release of Rancher builds on the June 9 finalization of a $10M Series A capital raise from Mayfield and Nexus Venture Partners.

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Menlo Security Raises $25M In Series B Funding And Reveals Isolation Platform For Malware And IT Security

This week, Menlo Security emerged from stealth to reveal details of a security platform that leverages isolation technology to tackle malware and related threats to IT security. In contrast to IT security models that focus on perimeter defense or behavioral analytics to identify anomalous behavior, Menlo Security deploys an isolation platform to quarantine web-based applications in disposable containers as illustrated in the graphic below:

As the graphic illustrates, all content is housed within Menlo Security’s isolation platform, irrespective of whether it poses a security threat or not. Because the platform disposes of all content, security threats never reach endpoint devices or infrastructures. The platform removes malware from web traffic, attachments and email without requiring the installation of endpoint software. In addition to announcing details of its isolation platform, Menlo Security revealed the finalization of a Series B funding raise totaling $25M. The Series B funding raise was led by Sutter Hill Ventures and complemented by participation from General Catalyst and Osage Partners. The finalization of Menlo’s Series B round means that it has now raised a total of $35.5M, building on a November 2014 Series A funding round of $10.5M. The launch of its isolation platform promises to disrupt cloud security methodologies by delivering a model for disposing of malware without relying on analytics to detect deviations from “baseline” usage patterns or perimeter defense approaches. As such, Menlo’s isolation platform places it in a unique ballpark when it comes to cloud security and malware detection by taking the discussion about cloud security away from what is good and bad, toward a different model entirely.

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JethroData Raises $8.1M In Series B Funding For Its Innovative SQL On Hadoop Platform

On June 9, JethroData announced the finalization of an $8.1M Series B funding raise led by Square Peg Capital with additional participation from Pitango Venture Capital. The funding will be used to accelerate product development and sales and marketing initiatives for the company’s breakthrough SQL on Hadoop offering. As told to Cloud Computing Today in a phone interview with JethroData CEO Eli Singer, the company’s SQL on Hadoop platform differentiates itself from the landscape of SQL interfaces for Hadoop by way of its superior performance with respect to querying Hadoop-based data. The JethroData platform derives its exceptional performance by indexing Hadoop data and subsequently limiting queries only to rows of data containing the relevant indices. Rather than querying the entire cluster, JethroData’s queries hone in on the subset of Hadoop data containing the relevant index attributes and thereby delivers results in a fraction of the time required by its competitors. For the use case of constructing predictive modeling algorithms, however, JethroData queries the entire Hadoop dataset in question as opposed to a subset for the purpose of creating models that illustrate trends and variations in data points and various aggregations. The platform’s design supports interactive business intelligence applications that depend on rapid data refreshes for both their analytics and visualizations and, as such, integrates with the likes of Tableau, MicroStrategy and Qlik. Tuesday’s announcement of the company’s funding raise validates the company’s early traction and supports JethroData’s claim to deliver queries on the order of 100x faster than competing SQL on Hadoop platforms.

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