They say that data about your data is more important than the data itself. Having the right data in the data warehouse at the right time or loaded up for Hadoop Analysis is critical. I have heard of stories where the wrong product was sent to the wrong store for sale due to incorrect conclusions on what was selling best. This was due to reports and decisions being made on the wrong data. This can be a resume impacting decision in this modern world of data driven product placements around the globe. In previous blog about Enterprise Job Scheduling (aka Workload Automation) http://blogs.cisco.com/datacenter/workload-automation-job-scheduling-applications-and-the-move-to-cloud/ I discussed the basic uses of automating and scheduling batch workloads. Business intelligent, data warehousing and Big Data initiatives need to aggregate data from different sources and load them into very large data warehouses.
Let’s look into the life of the administrator and operations of a workload automation tool. The typical Enterprise may have thousands if not ten thousands of job definitions. Those are individual jobs that get run: look for this file in a drop box, FTP data from that location, extract this specific set of data from an Oracle database, connect to that windows server and launch this process, load this data into a datawarehouse using Informatica PowerCenter, run this process chain in SAP BW and take that information to this location. All this occurs to get the right data in the right place at the right time. These jobs are then strung together in a sequences we in the Intelligent Automation Solutions Business Unit at Cisco call Job Groups. These groups can represent business processes that are automated. They many have 10’s to hundreds of steps. Each job may have dependency on other jobs for completion. The jobs may be waiting for resources to become available. This all leads to a very complex execution sequence. These jobs groups run every day; some run multiple times a day, some only run at the end of the quarter.
The typical IT operations team has a group of people that design, test and implement these job groups by working with people in business IT that design and implement business processes. Often times these job groups need to finish by a certain time to meet the needs of the business. If you are a stock exchange some job groups have to finish say in so many hours after the market closes. If you have to get your data to a downstream business partner (or customer) by a certain time you become very attached to watching those jobs execute. No pun intended, your job may be on the line.
A new technology has hit the scene for our customers of the Cisco Tidal Enterprise Scheduler. It is called JAWS Historical and Predictive Analytics. http://www.termalabs.com/products/cisco-tidal-enterprise-scheduler.html . These modules takes all historical and real time performance data information from the Scheduler and through a set of algorithms produce historical, real-time, predictive, and business analytics historical and predictive analytics. This is the data about the data I mentioned previously. Our customers can do what if analyses as well as get early indication that a particular job group is not able to finish in time. The administrators can take action before it is too late. This is critical in getting the data in the right place so that analytics can be performed correctly and therefore not sending 1000 of the wrong product to the wrong store location. Thanks to our partners from Terma Software Labs http://info.termalabs.com/cisco-systems-and-terma-software-labs-to-join-forces-for-more-sla-aware-workload-processing/ .
Tags: data center, intelligent automation, job scheduling, workload automation
Robb Boyd and Jimmy Ray Purser hit this episode of TechWiseTV, titled “The Need for Speed”, out of the park as they dive into Cisco’s latest switching announcements including 10Gig and 40Gig line cards, Easy Virtual Network (EVN), and much more.
Tags: 100 Gigabit Ethernet, 40GE module, easy virtual network, nexus
IT shops deploying clouds over the past year have been focused on Infrastructure as a Service ( http://en.wikipedia.org/wiki/Infrastructure_as_a_service#Infrastructure ) as a way to drive speed in virtual and physical server provisioning, cost savings in operations, proactive service level agreements, and increased control and governance. In one of my blogs I introduced our Cisco Intelligent Automation for Cloud http://blogs.cisco.com/datacenter/the-secret-is-now-out-you-can-simplify-cloud-deployments-with-cisco-unified-management/ and how that addresses both private, hybrid and public clouds IaaS. Key to this is the service catalog and self service portal. Moving to cloud is NOT about taking hundreds of server configuration templates and moving to them immediate self service. All you are doing in that model is automating VM sprawl. They key is defining a limited set of services and options that your end users such as application owners and technical folks can order through a self service portal and manage their life-cycle.
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Tags: automated provisioning, Cisco CloudVerse, Cisco Intelligent Automation for Cloud, cloud, data center, data center provisioning, IaaS, intelligent automation, orchestration, private cloud, Public Cloud, self-service
The term server management conjures up different connotations in the mind of the listener. Depending on the type of server – software application server, virtual server or physical server, the issues they care about are different. Two tasks that instantly come to the fore are server configuration and server monitoring.
A software application server manager may visualize configuration of production middleware servers and the parameters may include database connections, memory size etc. A manager responsible for the virtual infrastructure in a data center may picture server configuration tasks as storing and accessing virtual images, operating system types etc. for the virtual machines. An infrastructure manager responsible for physical servers will take into consideration power, firmware and network configurations for the server.
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Tags: system management, UCS, UCS Manager
“Ow mommy, my leg huuuuuuuuuuurts,” complained my 4 year old. After a quick examination and check-in with the doctor (read: I opened a book written by Dr. Sears and consider that a check- in with “the doctor”), I determined the problem was simply growing pains.
Growing pains don’t apply only to small children and adolescents. They apply to small companies and large enterprises alike. And like the growing pains you experienced when you were 4, 12, and 18 years old, they can cause physical (in the form of operational costs) and emotional (in the form of stress) pain for your business.
For my 4 year old the solution to growing pains is a kiss, hug, and maybe some chocolate ice cream. Most businesses (all businesses? There is always an exception) need more than a band-aid; businesses want a long-term solution to business challenges with measurable results. One of the most common “growing pains” for businesses is controlling operating expenditures.
Recent research shows that up to 75 percent of enterprise IT costs are operating expenditures (Gartner ITKMD, January 2011). Let’s explore how Cisco has significantly grown its infrastructure while reducing operating costs.
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Tags: Cisco, ciscoservices, cloud, datacenter, jill shaul, tco