This document discusses key performance indicator (KPI) definition using WSO2 Business Activity Monitoring (BAM) 2.0. It provides an overview of BAM and the BAM 2.0 analytics design flow. It also presents two use cases - one for monitoring retail store performance and another for monitoring statistics across data centers and clusters. The document explains how to capture and analyze data, define indexes, create analyzer sequences, and design visualizations for these use cases in BAM 2.0.

1. KPI Definition With BAM 2.0
Tharindu Mathew – Product Manager, BAM
Buddhika Chamith – Software Engineer, BAM

2. WSO2
•
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Technologies & Standards and Open Source
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Producing entire middleware platform 100% open source under
Apache license
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Business model is to sell comprehensive support & maintenance for
our products
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Venture funded by Intel Capital and Quest Software.
•
Global corporation with offices in USA, UK & Sri Lanka
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150+ employees and growing.

3. Business Activity Monitoring
“The aggregation, analysis, and
presentation of real-time information
about activities inside organizations
and involving customers and
partners.” - Gartner

4. BAM In a Nutshell
1. Aggregate
2. Analyze
3. Visualize

5. BAM 2.0 Analytics Design Flow
Capture Data of Interest Aggregate
Define Indexes
Analyze
Create Analyzer Sequences
Design Visualizations Visualize

6. Capture Data of Interest
●
Using data agents.
●
Currently we have agents for service/ mediation statistics
and message tracing.
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Easy to write new agents to publish custom data using Agent
API.

8. Define the Indexes
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Required since these indexes are used for filtering and
fetching data from the data store during analytics.
●
Conceptually not that different from SQL indexes.
(Composite Indexes)..

10. Create Analyzer Sequences
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An analyzer is a unit of data processing in the data
flow.
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A sequence of analyzers makes up a data flow
doing some useful piece of analytics on raw data.
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Currently a XML based language.
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Possible to plug in custom analyzers.

13. Design the Visualizations
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Visualizations are based on gadgets.
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Using a drag and drop style modelling tool, Gadget IDE.
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Wire the data source to the visualization elements and
generate the gadget.

14. Use Case 1 : Retail Store
Let's assume a retail store. The owner wants to know
the performance of his product line. Total sales for
each of the product is required.

16. Retail Store : Incoming Data
{ “in_message_body” :
“
“,
“retailStream” : “retail”,
....
}

17. Stream filtering Index

18. Analyzer Sequence – Part I

19. Data Model

20. Analyzer Sequence – Part II

21. Analyzers Explained
The frequency in which the analyzer task will
run.
Get data of retail data stream in
batches of 1000 from the
database by using the created
index.
Extract item code and quantity
from received SOAP Body and
add them to the data flow.

22. Group the data by item code.
Drop unnecessary columns of
each row.
Sum the quantity of each item.
Store in 'productSummary'
table. If item already exists
in the table add current
quantity to the amount
present in database and
store.

23. Product Summary Indexer

24. Gadget IDE – Data Flow View

25. Gadget IDE – Design View

26. Use Case 2 : Statistics Monitoring
Two data centers each having a cluster of ESB and App server
nodes. It is required to monitor statistics such as request counts,
response times etc. for each data center and cluster.

28. Cluster Monitor : Incoming Data
{ “dataCenter” : “”,
“cluster” : “”,
“request_count” : “3”,
“response_count” : “2”,
“fault_count” : “1”,
“response_time” : “3.5”,
“clusterStream” : “cluster”,
....}

29. Analytics
●
Define two indexes. One for filtering out data for
'clusterStream' data stream. Other for querying
table 'clusterSummary' to which summarized data
from analytics are stored.
●
Analyzer sequence groups the data by both data
data center and cluster and aggregate request,
response, fault counts and averages the response
times and store the result in 'clusterSummary'
table.

30. Summary
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Introduction
●
BAM 2.0 Analytics Design Flow
●
Use Case 1 : Retail Store
●
Use Case 2 : Cluster Statistics Monitoring

31. Questions?
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Alpha available at this link
●
Beta release in March
●
GA in Q3 2012
● Ready for you to start POC/Development work

32. Use Case 2 – Analyzer Part I

33. Use Case 2 – Analyzer Part II

34. Use Case 2 – ClusterStreamSelector

35. Use Case 2 – ClusterIndex

36. Selected Customers
https://ail.google.com/mail/u/0/?
ui=2&ik=ad9ae58f41&view=att&th=1331a7
0983344a32&attid=0.1&disp=thd&realattid
=f_gtxto6mk0&zw

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