Cisco is a Zettabyte sponsor at this week’s Strata Conference + Hadoop World in New York, NY, October 28-30.
Everyone’s talking about big data, but who’s actually doing it right—and how? Find out at Strata + Hadoop World, where big data’s most influential decision makers, architects, developers, and analysts gather to shape the future of their businesses. If you want to tap into the opportunities brought by big data, data science, and pervasive computing, you’ll want to be there too.
Stop by the Cisco Booth and please attend our breakout session:
“Deeper Insight into Operational Big Data Clusters”, delivered by Samuel Kommu, Cisco Technical Marketing Engineer
Wednesday at 1:45pm. Check here for more details.
We will showcase how our Cisco Nexus, UCS and our workload automation solutions--all configured specifically for Hadoop-- that enable rapid deployment, predictable performance, and massive scale to help you get the most value from your big data deployments.
Also, stop by the Cisco booth to receive you free copy of Unleashing IT Big Data Edition. This special edition of Unleashing IT is all about Big Data. There is nothing simple about scaling up to the challenge of managing the mountain of data flooding into your data center every day. To learn how to start extracting value, avoid pitfalls, and best practices of big data management, check out our new edition, containing expert advice, thought leadership, and industry insight.
Big Data blogs I follow:
Cisco Big Data Resources: www.cisco.com/go/bigdata
Tags: Big Data, Cisco Unified Management, Hadoop World, Strata Conference, Tidal, Tidal Enterprise Scheduler, unified management, workload automation
On June 20th, Cisco and MapR will join with Forrester Research Big Data analyst Mike Gualtieri to discuss “productionizing” Hadoop. But what does it mean?
Mike has developed a list of 7 architectural best practices that will help your enterprise quickly, and easily develop or move your Hadoop environment into standard data center processes. Following his guidelines, your can get your Hadoop environment up and running in no time, saving time by being proactive on the headaches and pitfalls that are unique to Big Data environments.
Joining Mike will be MapR CMO, Jack Norris discussing their best practices and how they line up with the Big 7 from Forrester.
Finally, Cisco IT will showcase a MapR production environment and how they have streamlined the complex Big Data workloads, automatically moving data into and running analytics out of their Hadoop environment.
Keeping the Hadoop production environment up and running smoothly is the name of the game here and in the face of resource constraints, Cisco IT has standardized on Cisco Tidal Enterprise Scheduler—with its seamless integrations into MapR, Hive, and Sqoop—giving your enterprise the ability to “productionize” complex workloads from any data source.
Join us as we walk you through the 7 architectural best practices for Big Data, MapR and Cisco Tidal Enterprise Scheduler.
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Tags: Big Data, cisco live, forrester, Hadoop, MapR, Tidal Enterprise Scheduler, unified management, workload automation
Guest Blog by Jack Norris
Jack is responsible for worldwide marketing for MapR Technologies, the leading provider of a enterprise grade Hadoop platform. He has over 20 years of enterprise software marketing experience and has demonstrated success from defining new markets for small companies to increasing sales of new products for large public companies. Jack’s broad experience includes launching and establishing analytic, virtualization, and storage companies and leading marketing and business development for an early-stage cloud storage software provider.
Big Data use cases are changing the competitive dynamics for organizations with a range of operational use cases. Operational intelligence refers to applications that combine real-time, dynamic, analytics that deliver insights to business operations. Operational intelligence requires high performance. “Performance” is a word that is used quite liberally and means different things to different people. Everyone wants something faster. When was the last time you said, “No, give me the slow one”?
When it comes to operations, performance is about the ability to take advantage of market opportunities as they arise. To do this requires the ability to quickly monitor what is happening. It requires both real-time data feeds and the ability to quickly react. The beauty of Apache Hadoop, and specifically MapR’s platform, is that data can be ingested as a real-time stream; analysis can be performed directly on the data, and automated responses can be executed. This is true for a range of applications across organizations, from advertising platforms, to on-line retail recommendation engines, to fraud and security detection.
When looking at harnessing Big Data, organizations need to realize that multiple applications will need to be supported. Regardless of which application you introduce first, more will quickly follow. Not all Hadoop distributions are created equal. Or more precisely, most Hadoop distributions are very similar with only minor value-added services separating them. The exception is MapR. With the best of the Hadoop community updates coupled with MapR’s innovations, the broadest set of applications can be supported including mission-critical applications that require a depth and breadth of enterprise-grade Hadoop features.
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Tags: Big Data, enterprise scheduler, Hadoop, informatica, job scheduling, MapR, Tidal Enterprise Scheduler, UCS, workload automation
It’s close to 11 p.m. on the last day of the quarter in a large corporation. IT gets an urgent request to postpone a closing of the books process because there’s a large order stuck in the CRM system.
This means that the order won’t hit the books and be recorded as a booking. The customer won’t get her order, the salesperson won’t get paid, and finance will show a missing number.
This generates an urgent call to the team that manages the workload automation platform: Hold the closing workflow! Stop the presses!
The admins have to get to their console to find the job and pause it. Not a huge deal, except there are thousands of jobs to be run and hundreds of business people calling on a regular basis, at all kind of hours.
Some customers have created help desks for their workload automation teams or they may even off-shore the call center to serve these kinds of requests.
No more. Introducing self-service for workload automation.
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Tags: data center, intelligent automation, job scheduling, orchestration, Tidal Enterprise Scheduler, unified management, workload automation
Today, Big Data and Hadoop are arguably the hottest (and most mysterious) subjects in computing for most technology workers. Ask any person in IT about Big Data/ Hadoop and you’ll probably get a look of utter confusion. Here at Cisco, I’ve recently taken on the role of Product Manager for Cisco Tidal Enterprise Scheduler (TES) and part of my job is to help you face your fears and put your arms around the Big Data boogeyman.
Big Data’s growth in the market has exploded and it’s clear why: data-driven decision-making results in optimal business outcomes. With Big Data/ Hadoop, analyzing massive datasets has become easier and we glean new business insights, which can be a massive competitive advantage.
I just arrived in NYC for Strata Conference + Hadoop World 2012, where I’m part of the Cisco team here to show off the new 6.1 release of Cisco Tidal Enterprise Scheduler announced yesterday. With 6.1, Cisco TES includes Hadoop integration – to help our customers address the Big Data challenge and gain even more value from your infrastructure. The workload automation features provided by TES are an integral part of getting the most out of your Hadoop deployments.
At the Strata event, we’re featuring Cisco UCS servers and Cisco Nexus switches for Big Data as well as our Cisco TES support for Hadoop. To see Cisco TES and Hadoop in action, check out this online demo here. This demo runs on UCS and schedules a Hadoop MapReduce job every 15 minutes to track tweets at the conference – revealing the biggest Twitter topics and the most active tweeps in Big Data this week.
In addition to our support for Hadoop and Big Data, with TES 6.1 we’ve announced a self-service portal, support for Amazon Web Services’ (AWS) EC2 & S3 features, and an iPhone app. AWS support adds the advantages of cloud-based Hadoop by providing the scalability and agility to expand capacity as needed coupled with Hadoop’s analytical strength. Throwing TES 6.1 into the AWS mix provides automated, efficient provisioning of cloud resources.
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Tags: Big Data, data center, Hadoop Summit, Tidal Enterprise Scheduler, unified management