CONTEXT
In order to maximize the performance and the quality of your business applications, the SAP Analytics Cloud platform, is used to build innovative stories to get actionable insights for your IT solutions. We build a data model that sits on an ODATA connection consuming SAP Solution Manager data through the Focused Insights services.
GOAL
Quickly analyze system performance issue in a blink of an eye.
APPROACH
Before consuming SAP Solution Manager’s data, make sure you have created corresponding gadgets in your Focused Insight’s Operations Control Center. For our example, we choose a time period of yesterday and daytime resolution for a faster download.
We have created gadgets accessing to the following metrics: Average Response Time, CPU usage, users and transactions information, user’s number of errors, jobs duration and the number of jobs executed. This information is relevant for an overview of a SAP system.
In order to retrieve SAP Analytic Cloud data, a connection is created by getting the data with the gadget number (GadgetTableSet for tables et GadgetSeriesSet for time series).
Then each data is modeled by verifying that the measures, the dimensions, the date and the timestamps are correctly assigned. When the model is created, the schedule setting must be set so that the data is recorded and synchronized every day.
When all necessary data is modeled, we can create a story to highlight the most relevant data.
STEP 1: Creation of the tree map with CPU and Respond Time
To answer the question, we start to build a Tree Map of the CPU and the Response Time. We join the two models with the Timestamp Dimension.
Through a Tree map, we can quickly identify the most critical Time Period where the system had the worst performance.
In the display above, July 21 is the darkest and largest area. On this day, system performance was weakest of the week.
STEP 2: Creation of the table for top jobs
We create a Bar/Column chart structure that gives us information about the jobs that took times, the users that generated the most errors, the slowest transactions…
STEP 3: Interaction between the Tree map and the table charts
By using the SAP Analysis Cloud’s “Linked Analysis” function, we will be able to filter the data at the same time by doing a linked analysis between several table charts. This function creates interactivity instantly and allow the user to deepen their analyzes with a single click. For the interaction be effective, it must be verified that each model is linked to the timestamps via “Linked dimension”.
In this section, you can configure the setting and select the hats that connect to the widget.
With this option activated, we can now select an area in the tree map that shows the CPU consumption and the average response time and display the information of this selected area in the table chart.
We can then easily see which user generated the most errors, which jobs took the longest time to respond, which transactions took times, in the selected area. This is information that IT departments can easily retrieve to solve their performance issues as quickly as possible.
CONCLUSION
Thanks to the development of the SAP Analytics Cloud’s Stories, you can identify the system performance issues by creating a Tree map that shows the most critical area based on CPU and Response Time. With the “Linked analysis” we can instantly display the most relevant information.
In order to maximize the performance and the quality of your business applications, the SAP Analytics Cloud platform, is used to build innovative stories to get actionable insights for your IT solutions. We build a data model that sits on an ODATA connection consuming SAP Solution Manager data through the Focused Insights services.
GOAL
Quickly analyze system performance issue in a blink of an eye.
APPROACH
Before consuming SAP Solution Manager’s data, make sure you have created corresponding gadgets in your Focused Insight’s Operations Control Center. For our example, we choose a time period of yesterday and daytime resolution for a faster download.
We have created gadgets accessing to the following metrics: Average Response Time, CPU usage, users and transactions information, user’s number of errors, jobs duration and the number of jobs executed. This information is relevant for an overview of a SAP system.
In order to retrieve SAP Analytic Cloud data, a connection is created by getting the data with the gadget number (GadgetTableSet for tables et GadgetSeriesSet for time series).
Then each data is modeled by verifying that the measures, the dimensions, the date and the timestamps are correctly assigned. When the model is created, the schedule setting must be set so that the data is recorded and synchronized every day.
When all necessary data is modeled, we can create a story to highlight the most relevant data.
STEP 1: Creation of the tree map with CPU and Respond Time
To answer the question, we start to build a Tree Map of the CPU and the Response Time. We join the two models with the Timestamp Dimension.
Through a Tree map, we can quickly identify the most critical Time Period where the system had the worst performance.
In the display above, July 21 is the darkest and largest area. On this day, system performance was weakest of the week.
STEP 2: Creation of the table for top jobs
We create a Bar/Column chart structure that gives us information about the jobs that took times, the users that generated the most errors, the slowest transactions…
STEP 3: Interaction between the Tree map and the table charts
By using the SAP Analysis Cloud’s “Linked Analysis” function, we will be able to filter the data at the same time by doing a linked analysis between several table charts. This function creates interactivity instantly and allow the user to deepen their analyzes with a single click. For the interaction be effective, it must be verified that each model is linked to the timestamps via “Linked dimension”.
In this section, you can configure the setting and select the hats that connect to the widget.
With this option activated, we can now select an area in the tree map that shows the CPU consumption and the average response time and display the information of this selected area in the table chart.
We can then easily see which user generated the most errors, which jobs took the longest time to respond, which transactions took times, in the selected area. This is information that IT departments can easily retrieve to solve their performance issues as quickly as possible.
CONCLUSION
Thanks to the development of the SAP Analytics Cloud’s Stories, you can identify the system performance issues by creating a Tree map that shows the most critical area based on CPU and Response Time. With the “Linked analysis” we can instantly display the most relevant information.
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