Cross-Platform End-to-End Messaging
Transaction Analysis with OmniAnalyser
White Paper
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Definition of the Messaging Service
Using OmniAnalyser to collect and analyze messaging-service data
delivers the most complete metrics information about messages sent,
received or transferred in organizations of all sizes. Such messagingservice data-collection includes all individual transactions. The delivery
of a message from origin to destination is monitored end-to-end and,
technically, such delivery occurs across multiple systems in the
enterprise infrastructure. OmniAnalyser delivers comprehensive and
business-relevant end-to-end messaging-service metrics, such as
message transit times, perimeter transaction processing delays, instant
messaging transaction latencies. The service metrics provide business
users, as well as IT staff, with a complete and transparent view of all
aspects of IT service delivery.
To receive true end-to-end quality metrics, they should be
“technologically agnostic”, meaning that the service descriptions and
service level objectives should not depend on any particular technology
such as the type of mail server or hardware involved. This makes the
initial service definition understandable to the business user and allows
for comparable metrics across multiple systems and when any specific
technology is replaced.
Furthermore, having proper end-to-end metrics facilitates proactive
service management as opposed to a reactive process of responding to
incidents. This can only be accomplished through careful analysis of
the reasons for failures rather than by monitoring and reacting to
performance alerts.
Principles of End-to-End Messaging Transaction
Analysis
Metrics are the face of IT services turned towards the customer. Endto-end messaging transaction analysis using OmniAnalyser™ is
focuses on transaction histories, where a transaction equals an email
message in the e-mail case. Quality end-to-end metrics require
© Hypersoft Informationssysteme GmbH, 2008
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transaction integration across multiple platforms and systems in the
organisation’s infrastructure. Starting with a transaction definition at the
business level and detailing the transaction to its elements on multiple
systems and platforms is a key to building business metrics.
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To achieve quality metrics collection, an organization should integrate
key transaction-metering across platforms and systems, no matter how
large or diversified they are. OmniAnalyser™ re-assembles all data
related to each messaging transaction collected from multiple servers
and systems, so its database contains full information on each
transmitted email. Different pieces of the same transaction are pulled
together into the OmniAnalyser™ Integration Server and connected to
each other based upon common attributes of each message that
remain consistent across systems. Typically these are message IDs,
although those IDs may not be the same for all participating systems,
so multiple unique keys may have to be used for complex
infrastructures.
In the example illustrated by the diagrams above, London is a Sendmail
server with Postfix content filtering deployed on it, whereas Grenoble is
a Microsoft Exchange Server. Messages that go through both servers
are counted and analysed in their entirety as seen on the Event List
report.
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Benefits of this Approach for the Business User
End-to-end messaging transaction analysis ensures the collection of
meaningful information on the quality and volume of service.
Delivery delays are determined for all “real” user messages (not just for
probes as in some alternative approaches). Delivery times can also be
calculated for subsets of larger infrastructures, such as business units,
geographies, or specific types of servers.
End-to-end integration also delivers accurate volumetric data as
messages are counted when passing through multiple systems. A
different approach to that would deliver inaccurate numbers, which may
be off by orders-of-magnitude. OmniAnalyser™ delivers auditable and
accurate transaction volume data: the business user can determine the
number of messages being transferred in any context within the
organization, as well as in and outbound to/from the Internet. Those
numbers are auditable, so they can be detailed down to each individual
email and user. OmniAnalyser™ properly consolidates such information
across different servers and systems, leading to correct email counts.
Benefits for the Operator of the Servers
There needs to be a rational, process-oriented methodology towards
managing the messaging-service delivery in a transparent and efficient
way. OmniAnalyser provides the ability to produce both customerfacing and operational metrics. The operational metrics are sufficiently
granular for proactive problem analysis and forensics.
Hypersoft OmniAnalyser™ delivers the most comprehensive reports on
the technical state of the server, alerting if some threshold in analyzed
data has been reached. Thanks to this function, the administrator
operator of each server can always monitor the server’s technical state
real-time.
Another important operational benefit is the ability to precisely match
the scope of the metrics to the scope of the managed systems. © Hypersoft Informationssysteme GmbH, 2008
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Integration of End-to-End Metrics into Service Operation
Scenarios
Enterprise Operations needs metrics to be mapped to business units,
locations, categories of users, service hours, and other parameters in
the organization. All such parameters map differently to different
systems in use. A perimeter application (such as antispam) may be
shared across all business units, or there may be several perimeter
installations in different geographies (such as Europe and North
America). There may be one set of scheduled maintenance times for
mobile messaging (such as Blackberry) and a different set of
maintenance times for the enterprise mail system (such as Lotus
Domino). Having proper metrics and, in particular, delivery times and
mail traffic information is only realistic if the enterprise has a complete
transaction data history in the database repository. With complete
transaction information, operational metrics and subsets can be
generated by filtering the queries to the repository. Otherwise it would
need to re-collect raw data which is sometimes just impossible.
In summary, there are two principal approaches to service metrics
collection:
‐
‐
Top-down, starting with the business service definition and
proceeding to the technical metrics required to produce that;
Bottom-up, looking at available technical metrics and trying to
transform them into something understandable for business.
With the top-down metrics collection:
9 KPIs are understood by provider and client, both internal
and external
9 Clear assignment of service delivery metrics to business values
9 Standardized service portfolio
9 True end-to-end proactive monitoring for optimal service delivery
In the case of messaging services, the top-down approach requires
integrated transaction histories across multiple platforms. This is the
only way to keep the focus on the concept of the message’s
transmission (which is the key business value for a user) and not just
on the “technical” health of participating servers and systems.
© Hypersoft Informationssysteme GmbH, 2008
www.re-soft.com/metrics
203 972 8462 6
© Hypersoft Informationssysteme GmbH, 2008
www.re-soft.com/metrics
203 972 8462 7