Performance Challenges on the Cloud

 

 

A typical cloud implementation could have hundreds of CPUs running in parallel. Some cloud solutions could be like an S-class Mercedes, however to leverage its muscles, it needs to be configured and fine tuned to reflect an efficient model. Examples of factors affecting a cloud implementation performance would be the number of Key Figures in an Integrated Business Planning (IBP) solution. The more Key Figures the higher the demand on the system and lower the performance.

 

Examples of common cloud performance challenges I have seen on SAP and Salesforce implementations are:

• Slow login time which is usually driven by network latency, demand on the enterprise SSO or other security system, firewall settings, or network device configurations.
• Dropped connections could be difficult to troubleshoot. On one implementation SAP users would receive a dropped connection error on an intermittent basis after about 30 minutes of being active on the system. Two weeks of troubleshooting uncovered the root cause of the issue was not due to the SAP cloud, but a misconfigured load balancer group of servers at one of the client's data centers.
• Initial load of templates, views and report runs are common issues when customers process large amounts of data. On a healthcare SFDC implementation the customer had a Contacts view for all its members, a whopping 1.5 million records. Obviously loading the view would take a few minutes of its agents staring at their screen. Educating the client on customizing the views to show members in a particular region, or who match certain filter criteria allowed them to view smaller data sets which were also more meaningful to their work.
• Refresh time is also a factor of the amount of data being retrieved, the browser
• Simulations
• Long running queries

 

Vendors constantly monitor their cloud operations checking memory utilization, background jobs status, CPU utilization, table sizes, system activities, and other performance KPIs to ensure optimum performance for their customers.

SAP key figure calculations can reach 10 million rows per second for its IBP solution in some implementations. Some factors that can affect that metric are data aggregations, projection, joins and uinions. In general loading a Planning View is dependent on the slowest Key Figure atomic calculation speed and the volume of data it processes. Using filters can sometimes be effective if it reduces the number of stored Key Figures that are defined as inputs to a calculation chain. However if filters do not affect the number of key figures and only affects data size the impact on performance might be minimal.

 

What is an IOT Platform

IOT Platforms come in different flavors and capabilities. IDC defines an IOT platform as follows:

 

• connects to and manages IOT endpoints
• ingest and process IOT data
• visualize and present IOT data
• builds and hosts IOT applications
• integrates IOT data into existing applications

 

Do you have a different definition?

SAP Planning Areas Considerations

Without fine tuning your cloud implementation you might realize less than optimum performance without even noticing. This post shares some recommendations that could fine tune an SAP planning view performance.


Sizing
Verify sizing post implementation is accurate after data is loaded as part of go-live activities. Sizing includes data storage, processing memory, data density (number of relevant data output per time period), ex: 1 sale per month, will not be caught in the weekly runs), and safety factors. Processing data on a more frequent basis and keeping the results on the planning view affects the remaining free resources (memory and storage). Sizing should be done during the cloud service acquisition, at end of blueprint, as part of performance testing and after go-live.


Configuration Complexity
Master data types and overall attributes should be kept as minimally as required. Usually clients use 20%-40% of the attributes they have defined in their implementations impacting performance with no true business value realization. Using non-key figure attributes of master data types as root attribute in a planning level is another approach to improve performance. Minimizing the number of calculations that include input levels is another way to improve performance, however care should be taken to avoid the need to increase the number of key figure values needed to store data. On the fly transformations should also be avoided to avoid performance bottlenecks.


Calculations
The approach used to perform calculations can significantly impact performance. Examples are the selection of key figures for a calculation, the calculation chain, stored key figures inputs, key figures base planning levels, placement and configuration of filters among other factors.


Planning Views
Keeping planning views to a reasonable number of rows is a generally recommended practice. Usually setting the rows to 2000 - 5000 does not impact performance negatively. Utilizing VBA-based templates instead of formula-based templates is another approach to improve performance as recommended by SAP. Using filters in templates when saving and opening templates is highly recommended to ensure reasonable load times. In SAP 1708 users will receive a warning message if no filters are defined in a planning view.


Running Operators as User-Defined Scenarios
Algorithms such as multi-stage inventory optimization affect the whole supply chain network. This large run-time can cause time-outs when run in simulation mode. A recommendation is to run these simulations as user-defined scenarios for improved performance.

Business Agility: Do You Have Some?

There have been various attempts to define business agility out there. Many are bogus definitions and very incorrect, so I thought I shed some light on the proper meaning of being agile, and what it means to an enterprise. Michael Hugos defines agility to be a product of visibility, motivation and training. I do not fully agree with his point of view, it is too specific and focused on enablers rather than the definition of agility. Agility needs enablers, and these could be some of the required enablers, but not necessarily all, moreover, each environment and enterprise might require different enablers.

According to Webster's College Dictionary, agility is being in a quick and well coordinated state, or nimble, active and lively. So agility is a state when one is able to act quickly and to the extent needed. Over-acting is not agility, its actually exerting more than needed, and under-acting is low performance.

So applying this to an enterprise means that it is able to act quickly and in a lean way. The terms quickly and lean are a little vague, so its not a bad idea to add some context to them.

• Quick is being able to respond to a stimulus in a time-frame that allows the enterprise to capture an opportunity or mitigate a threat.
• Lean is being able to respond with only what is needed to accomplish the point above, no more and no less.

An agile enterprise is one that has the capabilities to execute and realize what needs to be accomplished, without overstretching itself or wasting resources.

Some close definitions to mine are Brad Appleton's, which is a little too specific by listing energy and also specifying it along with economy and efficiency; and Wikipedia's definition which ties it specifically to cost. There are many ways to enable agility in your enterprise. Nicholas Evans promotes mobility solutions as one approach. I believe cloud computing will also make possible many enablers for an agile business. An example of how cloud can make telecom providers agile is illustrated in my recent patent.

Agile = Quick + Lean

Some examples of lean enterprises are those that:

• Can quickly change their website to respond to a trend, or customer need
• Can easily and without introducing additional cost reposition a product line
• Can enter a new market area with no additional overhead
• Can serve new types of customers with no impact on its customer support resources

Developing an agile enterprise is an on-going process, and it pulls from many areas of the enterprise architecture. An agile enterprise has agile business, technology and governance, reflected in its operations, systems, infrastructure and competitive abilities.

A New Buzzword in Town - Cloud Computing

So first it was Application Service Providers (ASPs) then Utility Computing and now comes Cloud Computing... It seems that every couple of years the industry needs a new set of buzzwords to keep the PR machine running.

Well there might be some slight differences between utility and cloud computing, but I would not really identify them as differences, I would just note them as the same with a slightly different scope. Instead of renting computing resources - utility computing - cloud computing rents applications and IT services.

So what is this cloud computing after all? Reading through various articles it seems to be nothing more than an application service provider hosting enterprise IT services for its clients. Its just technology improved from what was available in the mid-nineties, and vendor are looking for a way to get over the unsuccessful connotation of ASPs by relabeling the concept into cloud computing.

Some links on the topic from various trade rags for those interested:

http://gigaom.com/2008/02/28/how-cloud-utility-computing-are-different/
http://www.businessweek.com/magazine/content/07_52/b4064048925836.htm
http://www.gartner.com/it/products/research/cloud_computing/cloud_computing.jsp
http://www.technologyreview.com/Infotech/19397/?a=f
http://www.businessweek.com/technology/content/nov2007/tc20071116_379585.htm