Countless studies and analyst recommendations suggest the value of improving security during the software development life cycle rather than trying to address vulnerabilities in software discovered after widespread adoption and deployment. The justification is clear.For software vendors, costs are incurred both directly and indirectly from security flaws found in their products. Reassigning development resources to create and distribute patches can often cost software vendors millions of dollars, while successful exploits of a single vulnerability have in some cases caused billions of dollars in losses to businesses worldwide. Vendors blamed for vulnerabilities in their product's source code face losses in credibility, brand image, and competitive advantage.
The Cisco UCS solution provides all management and configuration services at the centrally located Fabric Interconnects, so you can manage large-scale deployments from a single location. This method lets you consolidate hardware and streamline management. The IBM Flex System solution uses a distributed management model with chassis-level control. This method adds to the complexity to the hardware configuration, which can increase management needs.
All enterprises need to have mitigation solutions in place. Information security is vital in the workplace and DDoS has become more complex over time. Determine whether services are the best option for primary protection through this whitepaper.
Traditional remote access technologies were created twenty-years ago, before businesses were distributed, mobile, and users of cloud. View this slideshare to learn 3 reasons why now is the time for a new remote access model.
Published By: Datastax
Published Date: Aug 23, 2017
Part of the “new normal” where data and cloud applications are concerned is the ability to handle multiple types of data models that exist in the application and persist each in a single datastore. This data management capability is called a “multi-model” database.
Chances are you are getting bogged down by various data models that require support — key-value, tabular, JSON/document and graph. This not only raises your operational expenses, but also slows down your time to market and ultimately revenue growth.
Download this free white paper and explore the multi-model concept, its rationale, and how DataStax Enterprise (DSE) is the only database that can help accelerate building and powering distributed, responsive and intelligent cloud applications across multiple data models.
Published By: Vertica
Published Date: Oct 30, 2009
Independent research firm Knowledge Integrity Inc. examine two high performance computing technologies that are transitioning into the mainstream: high performance massively parallel analytical database management systems (ADBMS) and distributed parallel programming paradigms, such as MapReduce, (Hadoop, Pig, and HDFS, etc.). By providing an overview of both concepts and looking at how the two approaches can be used together, they conclude that combining a high performance batch programming and execution model with an high performance analytical database provides significant business benefits for a number of different types of applications.
When you extend the global reach of your enterprise, you’ll find new markets for your products and services. That means reaching more potential customers, bigger growth potential, and higher ROI. But to tap into those emerging markets, you need to provide the best, most consistent user experience. Now, it’s possible for you to build, deploy, and manage modern apps at scale with a globally-distributed database—without the hassles associated with hosting in your data center.
Read the e-book Build Modern Apps with Big Data at a Global Scale and learn how Azure Cosmos DB, a globally-distributed turnkey database service, is transforming the world of modern data management.
Keep access to your data available, consistent, and safe—with industry-leading, enterprise-grade security and compliance. Start developing the best app experience for your users based on five well-defined consistency models:
Strong: Favors data consistency. Ideal for banks, e-commerce processing, and online booking.
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas.
Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.”
From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud.
Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
Published By: Symantec
Published Date: Jul 11, 2017
The technology pendulum is always swinging. And chief information security officers must be prepared to swing with it—or get clocked. A look at recent history illustrates the oscillating nature of technology. In the 1980s, IBM mainframes dominated the landscape. In the ’90s, client-server computing came on the scene and data was distributed on personal computers. When the Web assumed predominance, the pendulum started to swing back to a centralized server. Then, just as quickly, mobile took the lead, with apps downloaded to workers’ devices—the new client server. Now, as mobile devices continue to populate the enterprise at a rapid rate, the IT model is changing again—to the provisioning of information on a just-what’s-needed, just-in-time basis from centralized servers consolidated in the cloud. The pendulum continues to swing and IT workloads are moving to the cloud en masse.
Recent regulatory additions require that companies take proactive measures like penetration testing to enforce data privacy and integrity. By deploying a distributed model companies can execute testing from different security levels which is important in challenging posture based on level of access.