I’ve been working with Cisco UCS since the very beginning. From the earliest days, whenever a customer ran into problems, I would often be asked to help figure out what was going wrong and to help fix it. Generally, this would involve a review of the system, and when we found less desirable configurations we would work with the partner and customer to clean things up. As a part of this process, I began documenting the good and the bad I saw, which evolved into what I describe as UCS “better” practices. This post aims to describe some of these practices and why they are useful. Follow-up posts will expand on this and include additional important practices. Read More »
What do you say when your customers want a diverse range of cloud services—SaaS, IaaS, PaaS, private, public, hybrid—with the ability to deploy on demand? What if they want the flexibility to order and manage them all from the cloud, while keeping their data onsite? And what if they say they can’t wait weeks for you to build a solution, they’d like it immediately please?
If you’re United Data Technologies (UDT), you say, “Sure, no problem.”
UDT can meet all of these demands, and more, with its new eCloud managed cloud service offering, powered by the Cisco Cloud Architecture for Microsoft Cloud Platform.
Bringing the Cloud to New Customers
UDT serves a wide range of customers, from Read More »
Want to get the most out of your big data? Build an enterprise data hub (EDH).
Big data is rapidly getting bigger. That in itself isn’t a problem. The issue is what Gartner analyst Doug Laney describes as the three Vs of Big Data: volume, velocity, and variety.
Volume refers to the ever-growing amount of data being collected. Velocity is the speed at which the data is being produced and moved through the enterprise information systems. Variety refers to the fact that we’re gathering information from multiple data sources such as sensors, enterprise resource planning (ERP) systems, e-commerce transactions, log files, supply chain info, social media feeds, and the list goes on.
Data warehouses weren’t made to handle this fast-flowing stream of wildly dissimilar data. Using them for this purpose has led to resource-draining, sluggish response times as workers attempt to perform numerous extract, load, and transform (ELT) functions to make stored data accessible and usable for the task at hand.
Constructing Your Hub
An EDH addresses this problem. It serves as a central platform that enables organizations to collect structured, unstructured, and semi-structured data from slews of sources, process it quickly, and make it available throughout the enterprise.
Building an EDH begins with selecting the right technology in three key areas: infrastructure, a foundational system to drive EDH applications, and the data integration platform. Obviously, you want to choose solutions that fit your needs today and allow for future growth. You’ll also want to ensure they are tested and validated to work well together and with your existing technology ecosystem. In this post, we’ll focus on selecting the right hardware.
The Infrastructure Component
Big data deployments must be able to handle continued growth, from both a data and user load perspective. Therefore, the underlying hardware must be architected to run efficiently as a scalable cluster. Important features such as the integration of compute and network, unified management, and fast provisioning all contribute to an elastic, cloud-like infrastructure that’s required for big data workloads. No longer is it satisfactory to stand up independent new applications that result in new silos. Instead, you should plan for a common and consistent architecture to meet all of your workload requirements.
Big data workloads represent a relatively new model for most data centers, but that doesn’t mean best practices must change. Handling a big data workload should be viewed from the same lens as deployments of traditional enterprise applications. As always, you want to standardize on reference architectures, optimize your spending, provision new servers quickly and consistently, and meet the performance requirements of your end users.
Cisco Unified Computing System to Run Your EDH
The Cisco Unified Computing System™ (Cisco UCS®) Integrated Infrastructure for Big Data delivers a highly scalable platform that is proven for enterprise applications like Oracle, SAP, and Microsoft. It also provides the same required enterprise-class capabilities–performance, advanced monitoring, simplification of management, QoS guarantees–to big data workloads. With lower switch and cabling infrastructure costs, lower power consumption, and lower cooling requirements, you can realize a 30 percent reduction in total cost of ownership. In addition, with its service profiles, you get fast and consistent time-to-value by leveraging provisioning templates to instantly set up a new cluster or add many new nodes to an existing cluster.
And when deploying an EDH, the MapR Distribution including Apache™ Hadoop® is especially well-suited to take advantage of the compute and I/O bandwidth of Cisco UCS. Cisco and MapR have been working together for the past 2 years and have developed Cisco-validated design guides to provide customers the most value for their IT expenditures.
Cisco UCS for Big Data comes in optimized power/performance-based configurations, all of which are tested with the leading big data software distributions. You can customize these configurations further, or use the system as is. Utilizing one of Cisco UCS for Big Data’s pre-configured options goes a long way to ensuring a stress-free deployment. All Cisco UCS solutions also provide a single point of control for managing all computing, networking, and storage resources, for any fine tuning you may do before deployment or as your hub evolves in the future.
I encourage you to check out the latest Gartner video to hear Satinder Sethi, our VP of Data Center Solutions Engineering and UCS Product Management, share his perspective on how powering your infrastructure is an important component of building an enterprise data hub.
In addition, you can read the MapR Blog, Building an Enterprise Data Hub, Choosing the Foundational Software.
Let me know if you have any comments or questions, or via twitter at @CicconeScott.
Tags: Big Data, blade server, blades servers, C240 M3 Rack Server, Cisco UCS, Cisco Unified Computing System, Cisco Unified Data Center, Cisco Unified Fabric, Enterprise Data Hub, Gartner, Hadoop, MapR, rack server, UCS Central, UCS service profiles
The Internet of Everything continues to gain momentum and every new connection is creating new data. Cisco UCS Integrated Infrastructure for Big Data is helping customers convert that data into powerful intelligence, and we’re working with a number of new partners to bring exciting new solutions to our customers.
Today, I want to spotlight Elasticsearch, Inc. and welcome them to the Cisco Solution Partner Program.
Elasticsearch excels at providing real-time insight into data – whether structured or unstructured, human- or machine-generated; by bringing a search-based architecture to data analytics. By combining the ELK stack with Cisco UCS, organizations benefit from a turnkey underlying infrastructure solution that provides them with real-time search and analytics for a variety of applications, from log analysis, to structured, semi-structured, or unstructured searches, as well as a web-backend for custom applications that use search-based analytics as a core functionality.
Mozilla is just one of the companies who are already benefiting from the joint solution with real-time search and analysis of data powering its defense platform, MozDef. The ELK stack leverages Cisco UCS’ fast connectivity for query, indexing and replication of data traffic. And Elasticsearch handles the full scale of event storage, archiving, indexing and searching of the data logs. The ELK stack and Cisco UCS also protect Mozilla’s network, services, systems, and audit data from hackers.
Partners like Elasticsearch are just one reason that Cisco UCS Integrated Infrastructure can help your company capitalize on the IoE data avalanche and deliver powerful and cost-effective analytics solutions throughout your enterprise.
Find out more at www.cisco.com/go/bigdata, or register for a webinar entitled, “Learn How Mozilla Tackles their Security Logs with Elasticsearch and Cisco”.
Thursday, November 13th
9:00 AM PST / 12:00 PM EST / 5:00 PM GMT
Are you interested in learning how to build enterprise applications on top of Elasticsearch and Cisco’s Unified Computing System (UCS) infrastructure? We’re holding a webinar to delve more deeply into how to optimize ELK on Cisco UCS infrastructure.
Cisco UCS unites compute, network, and storage access into a single cohesive system. By combining the ELK stack with Cisco UCS, businesses benefit by having a turnkey hardware-software solution for their search and analytics applications. In this webinar you’ll learn about the various UCS hardware profiles you should consider when deploying ELK and how Mozilla built MozDef, their custom SIEM application, using ELK on Cisco UCS.
- Introduction – Jobi George, Elasticsearch (5 minutes)
- Overview of UCS + ELK reference architectures – Raghunath Nambiar, Distinguished Engineer, Data Center Business Group, Cisco (10 minutes)
- How Mozilla Built MozDef on ELK and Cisco UCS – Jeff Bryner, Security Assurance, Mozilla (25 minutes)
- Q&A – Jobi George, Elasticsearch (~20 minutes)
OpenStack is gaining increasing industry attention and, while it can deliver huge advantages, some may say it is “hyped”. Although OpenStack has an ever growing range of enthusiastic practitioners and advocates, as you may be aware, OpenStack is not without its critics – including Gartner – who outline the challenges of OpenStack adoption. It’s therefore generally recommended that OpenStack adopters consider engaging professional services experts to help them avoid the pitfalls
With the November 2014 OpenStack Summit in Paris opening as I write this – you can find us at stand C3 along with our newest acquisition, Metacloud (Stand E37) if you are going – my thoughts turn to the issues and challenges facing our customers when they deploy OpenStack into production projects. And who better to ask than our Cisco Services consultants who are delivering OpenStack adoption services (which we launched this time last year at the Summit in Hong Kong).
These consultants are at the “coal face” (as we say in my part of the world, Scotland) of OpenStack– they are the experts digging deep in the IT equivalent of the mines working with real customers going live with real-world OpenStack. More than R&D investigations, these deployments are happening with customers who are betting their business dollars, pounds, yen and other currencies on OpenStack. However as the video (below) shows, OpenStack has its deployment complexities. Hence increasing numbers of our customers are engaging Cisco Services to help them on OpenStack.
To share our practical experiences with you, we sat down and came up with our “top 5” adoption challenges list which you may find useful if you are considering or embarking upon an OpenStack deployment:
- Cross-domain technical expertise is mandatory
- Going deep with Open Source
- “It’s just middleware”
- Don’t underestimate the learning curve
- Expect your OPEX to increase (sorry!)