The cloud is expanding. More applications are being run online. More data is being stored online. More businesses are relying on public, private, and hybrid clouds for their apps, records, and backups. And more hackers are taking advantage. Why Security Breaches Happen in the Cloud Hackers aren’t attacking the cloud; the cloud is their access […]
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A central challenge for any digital transformation initiative is dealing with the ever-increasing pace of change – in the marketplace, in the technology environment, and in the world at large. Clearly, as customer expectations accelerate, our technology must keep up. Squeezing every last millisecond of performance leads to the demand for real-time – technology with no delays whatsoever, moving at the speed of thought itself. If we examine this real-time requirement more closely, however, important nuances emerge. First, real-time never actually means instantaneous, as it always takes a certain amount of time for bits to find their way to their destination. But even more important for any digital professional to understand, the concept of real-time has several subtly different meanings – and understanding the differences is critical for making effective technology decisions.
Think Big has demonstrated expertise in implementing open source big data technologies such as Hadoop, NoSQL databases including HBase, Cassandra and MongoDB, and Storm for real-time event processing. The consulting teams have deep-domain knowledge with a variety of Hadoop distributions such as Hortonworks, Cloudera, and MapR. In addition, Think Big provides a set of pre-built application components for Customer and Clickstream Analytics, Distributed Device Data Management and Analytics, and Risk and Trading Analytics.
Due of the rise of Hadoop, many enterprises are now deploying their first small clusters of 10 to 20 servers. At this small scale, the complexity of operating the cluster looks and feels like general data center servers. It is not until the clusters scale, as they inevitably do, when the pain caused by the exponential complexity becomes apparent. We’ve seen this problem occur time and time again.
In his session at 15th Cloud Expo, Greg Bruno, Vice President of Engineering and co-founder of StackIQ, describes why clusters are so different from farms of single-purpose servers that reside in traditional data centers, and why without an automated solution that can address the cluster requirements, real pain is coming and failure is certain.
Syncsort, a global leader in Big Data integration solutions, announced the results from a multi-stage industry survey conducted over the first half of 2014 which show enterprise IT decision makers are making serious strategic commitments to Big Data migration and analytics programs, signaling an industry evolution from trial to action. Syncsort polled over 100 IT decision makers, ranging from data scientists, data architects, developers and IT managers at the recent Hadoop Summit in San Jose and the Cloudera Session in Boston. The majority of respondents were from medium to large enterprises who indicated that 5% or more of their current budgets were allocated to Big Data projects, much of that effort focusing on offloading data warehouse data for enterprise wide use through analytics. These results show, regardless of Hadoop distribution preference, decision makers have transitioned their focus from test or stealth projects to real world execution of Big Data strategies.
With cloud computing there’s no longer a question about whether you should encrypt data. That’s a given. The question today is, who should manage and control the encryption keys? Whether talking to an infrastructure provider like Amazon or Microsoft, or a SaaS provider, it’s imperative to have the discussion about key control. The topic is […]
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Is your organization struggling to deal with skyrocketing volumes of digital assets? The amount of data is growing exponentially and organizations are having a hard time managing this growth.
In his session at 15th Cloud Expo, Amar Kapadia, Senior Director of Open Cloud Strategy at Seagate, will walk through the essential considerations when developing a cloud storage strategy. In this discussion, you will understand the challenges IT is facing, why companies need to move to cloud, and how the right cloud model can help your business economically overcome the data struggle.
The advancement of technology has led to widespread Cloud data and SaaS application usage throughout enterprises. And CIOs are unprepared for the (mostly unwelcome) implications – largely unaware of the “SaaS Sprawl” in their organizations.
These Cloud applications are available for just about every role in a company – from human resources to marketing, there’s an app for that. And odds are, someone in your organization is using it – most likely without IT knowing.
As app (primarily SaaS and Cloud) use within organizations continues to spread and accelerate, IT professionals are largely unaware of the massive scale of Cloud application utilization. However, IT continues to be held responsible for many of the implications resulting from this widespread proliferation.
A funny thing has happened in the technology world, the hype cycle has become far more than a cycle that you watch and smile at. It has become a sales frenzy, while people try to make a name and/or sell you stuff before the idea or product category has even solidified. You can see it all around you, and as has been going on for years, the trend seems to be worsening. I call it a funny thing because the truly revolutionary technologies – like server virtualization – really didn’t need a full-on hype cycle at all. Virtualization just kept growing year after year. People would declare “the year of virtualization!” and the year would pass, with more servers virtualized but no mass shift from one paradigm to the other.
This post is the first in a multi-part series of posts on the many options for collecting and forwarding log data from different platforms and the pros and cons of each. In this first post we will focus on Syslog, and will provide background on the protocol.
Syslog has been around for a number of decades and provides a protocol used for transporting event messages between computer systems and software applications. The protocol utilizes a layered architecture, which allows the use of any number of transport protocols for transmission of syslog messages. It also provides a message format that allows vendor-specific extensions to be provided in a structured way. Syslog is now standardized by the IETF in RFC 5424 (since 2009), but has been around since the 80’s and for many years served as the de facto standard for logging without any authoritative published specification.