Welcome!

Weblogic Authors: Yeshim Deniz, Elizabeth White, Michael Meiner, Michael Bushong, Avi Rosenthal

Related Topics: Open Source Cloud

Open Source Cloud: Article

Don't Blame Batch Processing for Your Business Process Failures

Never take short cuts on adequate testing of changes and test planning

The recent train wreck that was the CA batch process failure at RBS should probably be ringing alarm bells for some folks running batch processes into their systems; however, more importantly it should remind us of a couple of different things:

  • Batch processing is real and present in many facets of IT data processing and systems at large
  • Never take short cuts on adequate testing of changes and test planning

A call I participated on a couple of months back with some students from an esteemed college in North America resulted in a conclusion that what I was talking about and showing these students wasn't very interesting because a lot of what I was focusing on, was batch processing of data.

For some naïve and deluded reason they were of the opinion that real time OLTP was a more interesting story and so wanted to focus on that aspect of the Winshuttle technology stack rather than on the mass and batch related activities.

In reality, our world of data processing and systems relies heavily on both aspects.  I have to confess that I hardly ever give the concepts of batch vs. real time much thought, but this recent failure in the payment runs for thousands of banking customers brought home the importance of batch processing and reminds us that batch processing is alive and well everywhere.

Payroll, transfers, interest calculations, reporting, diary actions, archiving,  amends, deletes, applications, returns, balancing etc are all activities that in the banking industry are often processed using batch processing cycles. In the longer term, many of these batch processes may move to real-time but there are a lot of benefits associated with the current batched approach.

Practically speaking, batch processing often represents a better value proposition for certain activities that involve pre-staged or staged data. In addition, even though your system may be a genuine real-time OLTP it is likely that the statistical and key figure reporting aspects of your system are all still bound up in batched processing.  In addition to this facet of summarization and aggregation reporting and data staging, there is the factor that OLTP resources that support all the things you could conceivably want to be able to do, is expensive and some processes really are not so urgent that they demand all the system resources to be available 24x7 in massively capable infrastructure.

Just the notion of point in time recovery of your system for example, can be incredibly expensive in terms of system resources and equipment. From a hardware perspective we have features like database mirroring, hardware redundancy, multithreading operating systems and built-in resource redundancy for failover contingency. For this reason too, database software companies have developed technologies that produce things like archive logs that facilitate point in time recovery of the database without having to revert to a state that only reflects the system view at the point of the last back up. This capability has improved disaster recovery and confidence that systems can reflect accuracy even after unexpected mishaps.

I said earlier, that batch processes aren't going to go away any time soon, in fact, major analyst firms estimate that some 70-90 percent of enterprise integration requirements are for batch processes and this situation is further compounded by analyst research that suggests that batch processes often represent a significant contribution to planned system downtime. Moving that figure will take some considerable cost and effort - it doesn't necessarily make sense to invest in changing that number even if there is the will to commit to it.  If one considers that batch processes are often bound up in automation tools one then one becomes acutely aware of the fact that these batched automation procedures actually provide greater visibility into the circumstances of the business and can provide reassurance on the integrity of processes. Compliance facets of strictures introduced by legislation like Sarbanes- Oxley and HIPAA are more easily addressed in particular, since processing activity is more easily identifiable through batch processing audit reports that are easily identified and consumed.

My second point around this whole fiasco is regarding testing and test planning. In an ideal environment any change that you're planning to institute in a system should include testing in development environment, performance and regression tested in a QA or pre-production environment and only after all testing is done and all issues addressed, scheduled for application against productive systems.

The RBS incident reminds us that even the most mundane of changes can have very far reaching implications. There will no doubt be a lot of finger pointing and deconstruction of the events that led up to the problem, but most importantly some questions that should be asked are, why did this change happen mid-week and was it tested adequately before the change was agreed to be made?

As the post mortem of the event progresses no doubt we will learn more. For ourselves at least, we should take away a lesson learned and make sure that our own batch and non-batch processes are not rendered at risk by poorly planned, tested and ill-prepared-for changes to our own systems.

Additional Reading:

More Stories By Clinton Jones

Clinton Jones is a Product Manager at Winshuttle. He is experienced in international technology and business process with a focus on integrated business technologies. Clinton also services a technical consultant on technology and quality management as it relates to data and process management and governance. Before coming to Winshuttle, Clinton served as a Technical Quality Manager at SAP. Twitter @winshuttle

IoT & Smart Cities Stories
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
Whenever a new technology hits the high points of hype, everyone starts talking about it like it will solve all their business problems. Blockchain is one of those technologies. According to Gartner's latest report on the hype cycle of emerging technologies, blockchain has just passed the peak of their hype cycle curve. If you read the news articles about it, one would think it has taken over the technology world. No disruptive technology is without its challenges and potential impediments t...
If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Bill Schmarzo, Tech Chair of "Big Data | Analytics" of upcoming CloudEXPO | DXWorldEXPO New York (November 12-13, 2018, New York City) today announced the outline and schedule of the track. "The track has been designed in experience/degree order," said Schmarzo. "So, that folks who attend the entire track can leave the conference with some of the skills necessary to get their work done when they get back to their offices. It actually ties back to some work that I'm doing at the University of San...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...