Creating SLA on business metrics – it is easier than you think

As we all know, creating a Service Level Agreement (SLA) over Application Performance Management (APM) performance data is very easy, in fact it is so easy that you can actually complete your SLA to reflect your current application in less than 1 minute.

 

You can download Application Performance Manager on SaaS here and try it in your environment

 

It is so easy because SLA leverages all your existing configuration (from topology to threshold settings), so all you need to do is select the relevant application and define your objective (via offering level).

The result is the screen below which clearly shows your services from a business perspective.

 

SLA.png

[Fig. 1: Unified dashboard showing real time and offline perspective of your services]

 

In the following link (Chapter 7, Quick start - SLM) you can view the current documentation on SLM Quick Start.

 

However I often receive requests to have SLA reports that reflect business data as well--not only performance statistics. From my experience, the performance data often delivers only a portion of the health perspective of your service. Instead you need to define SLAs that manage and enforce business metrics alongside performance data can truly deliver the end-to-end solution you need.

 

Recently one of the largest cellular providers in Europe approached me with this exact scenario. He had his services covered by the APM tool but was really interested in measuring and reporting SLA compliance as well as the amount of successful business transactions, driving the data from his own priority database.

 

The implementation was much easier than he anticipated, and we configured the required reports in less than a day.
We created SiteScope DB monitor that every five minutes queried the number of total transaction and the number of failed transaction.

 

SiteScope sent this data to BSM in a general format with two columns: column 1 (total number of transactions) and column 2 (the number of failed transactions).

We use the out-of-the-box “API Simplified Average Rule” to calculate the percentage of failed transactions where column 1 is the denomination and column 2 is the numerator.

 

The SLA rule engine took it from there, calculating the percentage of failed transaction for any given time and period and comparing it to the different objectives defined by the customers.

 

In the end we managed to complete all of this in less than day and presented the results to management the following day. The tricky part was to bring the data into BSM (and for that we used SiteScope DB monitoring), from there we had all the flexibility we needed to create the needed SLA. 

 

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