Best Practices
BPM employs, as may be required, best practice benchmarking to establish design criteria and strategic approach to determine the gaps between our client's "as is" system and the desired "to be" state. We maintain a data base of best practices in a wide variety of systems disciplines. And, as the specifics of the situation require, we conduct tailored best practice evaluations on behalf of a client.
Sample results for one benchmark participant (which just happens to be one of the largest, most successful, e-commerce sites in the world) is presented below, as an example. This case study, which maintains the confidentiality of the client and participant, illustrates the value and the comprehensiveness in the BPM best practice approach.
We invite you to compare your own site's performance the design principles and metrics presented in this actual benchmark below. We know you will benefit greatly by doing so. We also ask you to extrapolate the value of applying this same technique, analogously, to the challenges you may be facing in this or other systems disciplines. Though the benchmark below is specific to e-commerce infrastructure, we have applied this same approach for numerous clients in such diverse areas as telecommunications billing design, operations management process design, enterprise software cost evaluation , data center budgeting, and other related areas. We have learned the incredible power of this approach. We invite you to as well.
Criteria |
Best Practice Sample Result Internet Operations and Architecture |
Business value (Actual participant) |
3 years to develop and achieve, from no e-commerce applications to current state where e-Commerce accounts for:
|
Applications
|
|
Volume |
|
Architecture |
Ř Design principle: design
based on segregation of function, allocating of distinct functions to
distinct servers. Ř
Design principle: application
design is fat client (significant user/appl interaction takes place in the
browser, resulting in full transaction gets sent to / processed by server) Ř
Design principle: uses a
caching engine for inbound and outbound traffic Ř
Design principle: design
such that you are dependent on any IP specific design Ř
Design principle: design
so that multiple data base engines hit same data base concurrently Ř
Design principle: design
for cloned instances of the same service Ř
Design principle: design
not to have mixed packet sizes running at the same time Ř
Design principle: you
must design for persistence (state must be know at any and every point
that the internet connection might get interrupted). This is necessary due
to unreliable nature of the internet connection. Our preferred approach is
to capture state and send this info to a state server; if you get
disconnected you can retrieve state form the state server. (this is the
internet version of checkpoint restart). Ř
Design principle: avoid
sequential design--launch (and process) multiple queries concurrently;
this is superior to/faster than sequential design. It also enables the
screen to be painted faster (as the screen can be painting concurrently
with a longer running query being processed). Ř
Lesson learned: using
load director is not the way to go. Big IP and Resonate are alternative
load balancing product solutions that enable you to distribute load across sites so (Vs load director who does not). Therefore this
the preferred approach Vs Load Director. Ř
Lesson learned segregation of workloads is the only way to predict and
manage capacity Ř
Lesson learned found caching for inbound traffic highly valuable (reduced
I/O by 50%) Ř
Lesson learned choose large capacity boxes (eg E10000s). It is easier/less
cost to manage a smaller # of large capacity devices. Opposite approach
larger # of smaller boxes adds an administrative burden (eg contrast with
Dell which adds 70 NT servers per month) Ř Lesson learned: manage capacity by dynamically balancing load real time both across configurations and across processors within a single configuration. |
Product
set |
|
Change management process design |
|
Reliability
design |
|
Scalability
design |
Supports horizontal scalability design via:
|
Availability
metrics |
|
Support
requirements |
|
Again, although the best practices benchmark presented above is specific to e-commerce infrastructure, we have applied this same approach for numerous clients in such diverse areas as telecommunications billing design, operations management process design, enterprise software cost evaluation , data center budgeting, and other related areas. We have learned the incredible power of this approach. We invite you to as well.
To see the outline that drove this particular best practice benchmark click: benchmark outline