CONTEXT
The SAP Analytics Cloud platform allows us to create innovative stories and to retrieve data from different products in order to find on the same page the key data to analyse the system security. It's much more convenient and faster to summarize everything in one story. In order to ensure secure, up to date, healthy running system, we build story consuming from 2 scenarios: Configuration and Security Analytics data through in Focused Run services and System Recommendation data in Solution manager services.
GOAL
Mixing data from different data sources to ensure secure, up to date, healthy running system
APPROACH
Before consuming SAP Solution Manager’s data and Focused Run’s data in SAP Analytics Cloud, you need to create corresponding instances and gadgets in the Operations Control Center Dashboard.
The configuration and Security Analytics (CSA) application collects configuration items and support different views on them:
So that the system Focused Run can through the part CSA Validation shows the results of a validation rules of a policy, you need to define them. To do this, in your launchpad, in the Advanced Configuration Monitoring, click on Configuration et Security Analytics.
A scope selection page appears, where you can enter information for filtering such as the System Type. For the future story, I choose as System Type: Application Server ABAP.
Then you can choose the rule you want to analyse. The rules are stored in Policy. So, click on the Select button and you will find all the rules that you could check for compliance. When I selected a rule, this rule is active for some systems and for each system we have the names of the technical systems that are not compliant and compliant according to this rule.
To display these information, you can go to your OCC Dashboard, create a page, modify system settings and policies. Then you can have a dashboard like below.
In Solution Manager, there is a very useful feature called System Recommendation.
System Recommendation checks every day in the system, which notes have been implemented and which new notes have been released in real time. With this information, the customer can see that some notes have not been implemented and that he should check them. This scenario is called System Recommendation, it is basically checking for each system which notes are implemented, checking which new notes that have been released are not implemented on the system and informing the customer.
To access this feature, in your launchpad, in Change Management, click on System Recommendation. You will find a report where you can select your system to get a first overview. To display this information in the OCC dashboard, we need to extract the information via the Solution manager system. Then you can create your gadget.
In our example, the most relevant information for an overview of the analysis of our system is contained in the created table (relased_date, system_name, note_number, priority, software component, description ...).
Moreover, we choose for more precision a time period of the last 360 days and a daily resolution.
For more details, please refer to this usefull link:
Now that we have the information from the two different data sources. To retrieve them in SAP Analytic Cloud, we need to identify for each system (Solution manager and Focused Run), the information such as the entity and the filters. For each data service, I build a model that sits on an ODATA connection consuming data through Focused Run services and Solution Manager services.
For Focused Run, you need the ID of the gadget and the ID of the page which can be retrieved by clicking on See page and view ids in your OCC dashboard that you have created before.
A connection is created by getting the data with the entity TacSacSet and we filtered with the GadgetId and the DashbordId.
For Solution manager, you need the ID of the gadget. To get it, in your OCC dashboard that you have created, you switch in Toggle Edit Mode and on Dashboard Layout you will find the number of your gadget ID. Here, the GadgetId is 1024.
A connection is created by getting the data with the entity GadgetTableSet and we filtered with GadgetId:
The next step is to create the model for each data source: one that will contain the data from Focused Run and the other from Solution Manager.
Models are where you do all your data modelling in preparation for analysis. Data modelling entails data wrangling or cleaning, defining your measures and dimensions, and enhancing your data by establishing hierarchies, setting units, and adding formulas.
Then don't forget to schedule setting must be set so that the data is synchronised and recorded every day.
For this story, the goal is to mix data from different data source to ensure secure, up to date, healthy running system. To analyse it, we need information from the recommendation system but also from CSA. That's why I mixed this information on a single story to allow the customer to gather all the necessary data for the analysis.
STEP 1: Security Landscape
This part gives you an idea of the overall landscape with only 3 widgets.
The first one shows you that there are 144 very high priority "HOT NEWS" or security notes that need to be implemented. It provides information about the security status of the entire landscape. This data comes from Solution Manager.
The second one uses data from Focused Run. It represents the average compliance by policy of the landscape. For example, the Open Client security base line is a policy of Focused Run that is used to verify that the clients have the right configuration in productive environments. Here, we can see that half of the system landscape is not compliant, so it needs to be verified. To get the average compliance measure, I have created an Edit calculation. In fact, in the raw data I only had the noncompliance information.
And the last widget shows the distribution of the overall note and it allows to answer questions like “How many notes are not implemented per priority? “
STEP 2: System Recommendation
For this part of the story, I created 2 controls that will allow to filter the other widgets by System and Priority. They will allow us to focus on the system or priority we want in two clicks. Moreover, the other widgets are:
- DISTRIBUTION: % of notes per system and per priority
- TREND: Notes per System for this month
- HEATMAP: Notes by priority and system
- TREND: Notes per System for the current year
- COUNT: Number of notes for selected Systems
- COUNT: Notes per System filtered by priority HOTNEWS and HIGH PRIORITY
For example, you can select only one system and all widgets are automatically updated and will consider only the selected system. Typical questions that this dashboard can answer are: How many notes in function these filters have been released for this system? Or which system according to the priory needs attention?
For this second part, I added another control that filters according to the software component. So, these 4 widgets can be filtered by system, by priority but also by software component. Maybe you want to focus only on the special software component per specific system. And I created a summary table with some details to have specifically the Description. Also, you can create jump-in from the SAC to an external URL. Indeed, it is interesting to be able to access system recommendation of the selected system.
STEP 2: Configuration and Security analytics
In this section also, I have created a control by System that will allow us to directly check the non-conformity of each policy by System. I have created 3 widgets to show the possibilities you have to represent the percentage of non-compliance policies.
Conclusion
Through the platform SAP Analytics Cloud, we can mix different data sources from different applications of different systems or products in one consistent Story/Dashboard. Here, we want to analyse the whole system and with this approach, we can get actionable insights to ensure secure, up to date, healthy running system.
Thanks for reading and don’t hesitate to share feedback or thoughts in a comment!
The SAP Analytics Cloud platform allows us to create innovative stories and to retrieve data from different products in order to find on the same page the key data to analyse the system security. It's much more convenient and faster to summarize everything in one story. In order to ensure secure, up to date, healthy running system, we build story consuming from 2 scenarios: Configuration and Security Analytics data through in Focused Run services and System Recommendation data in Solution manager services.
- Configuration and Security Analytics from Focused Run is an application who helps you to determine whether the systems in your landscape are configured consistently and in accordance with your requirements and security policies.
- SAP System Recommendation function in SAP Solution Managerhelps to check SAP landscape systems relevant notes & patches in order to keep all systems up to date.
GOAL
Mixing data from different data sources to ensure secure, up to date, healthy running system
APPROACH
Data validation
Before consuming SAP Solution Manager’s data and Focused Run’s data in SAP Analytics Cloud, you need to create corresponding instances and gadgets in the Operations Control Center Dashboard.
FOCUSED RUN: Configuration and Security Analytics
The configuration and Security Analytics (CSA) application collects configuration items and support different views on them:
- Validation checks the configuration items against a defined policy, whether the setting for the password length fits to the security requirements
- Changes displays the changes over time
- Search and Store Browser help to find configuration items and the objects
So that the system Focused Run can through the part CSA Validation shows the results of a validation rules of a policy, you need to define them. To do this, in your launchpad, in the Advanced Configuration Monitoring, click on Configuration et Security Analytics.
A scope selection page appears, where you can enter information for filtering such as the System Type. For the future story, I choose as System Type: Application Server ABAP.
Then you can choose the rule you want to analyse. The rules are stored in Policy. So, click on the Select button and you will find all the rules that you could check for compliance. When I selected a rule, this rule is active for some systems and for each system we have the names of the technical systems that are not compliant and compliant according to this rule.
To display these information, you can go to your OCC Dashboard, create a page, modify system settings and policies. Then you can have a dashboard like below.
SOLUTION MANAGER: System recommendation
In Solution Manager, there is a very useful feature called System Recommendation.
System Recommendation checks every day in the system, which notes have been implemented and which new notes have been released in real time. With this information, the customer can see that some notes have not been implemented and that he should check them. This scenario is called System Recommendation, it is basically checking for each system which notes are implemented, checking which new notes that have been released are not implemented on the system and informing the customer.
To access this feature, in your launchpad, in Change Management, click on System Recommendation. You will find a report where you can select your system to get a first overview. To display this information in the OCC dashboard, we need to extract the information via the Solution manager system. Then you can create your gadget.
In our example, the most relevant information for an overview of the analysis of our system is contained in the created table (relased_date, system_name, note_number, priority, software component, description ...).
Moreover, we choose for more precision a time period of the last 360 days and a daily resolution.
For more details, please refer to this usefull link:
- Focused Run Expert Portail: https://support.sap.com/en/alm/sap-focused-run/expert-portal/configuration-and-security-analytics.ht...
- Solman System Recommendation: https://support.sap.com/en/alm/solution-manager/processes-72/system-recommendations.html
Data extraction
Now that we have the information from the two different data sources. To retrieve them in SAP Analytic Cloud, we need to identify for each system (Solution manager and Focused Run), the information such as the entity and the filters. For each data service, I build a model that sits on an ODATA connection consuming data through Focused Run services and Solution Manager services.
For Focused Run, you need the ID of the gadget and the ID of the page which can be retrieved by clicking on See page and view ids in your OCC dashboard that you have created before.
A connection is created by getting the data with the entity TacSacSet and we filtered with the GadgetId and the DashbordId.
For Solution manager, you need the ID of the gadget. To get it, in your OCC dashboard that you have created, you switch in Toggle Edit Mode and on Dashboard Layout you will find the number of your gadget ID. Here, the GadgetId is 1024.
A connection is created by getting the data with the entity GadgetTableSet and we filtered with GadgetId:
The next step is to create the model for each data source: one that will contain the data from Focused Run and the other from Solution Manager.
Models are where you do all your data modelling in preparation for analysis. Data modelling entails data wrangling or cleaning, defining your measures and dimensions, and enhancing your data by establishing hierarchies, setting units, and adding formulas.
Then don't forget to schedule setting must be set so that the data is synchronised and recorded every day.
Data visualization
For this story, the goal is to mix data from different data source to ensure secure, up to date, healthy running system. To analyse it, we need information from the recommendation system but also from CSA. That's why I mixed this information on a single story to allow the customer to gather all the necessary data for the analysis.
STEP 1: Security Landscape
This part gives you an idea of the overall landscape with only 3 widgets.
The first one shows you that there are 144 very high priority "HOT NEWS" or security notes that need to be implemented. It provides information about the security status of the entire landscape. This data comes from Solution Manager.
The second one uses data from Focused Run. It represents the average compliance by policy of the landscape. For example, the Open Client security base line is a policy of Focused Run that is used to verify that the clients have the right configuration in productive environments. Here, we can see that half of the system landscape is not compliant, so it needs to be verified. To get the average compliance measure, I have created an Edit calculation. In fact, in the raw data I only had the noncompliance information.
And the last widget shows the distribution of the overall note and it allows to answer questions like “How many notes are not implemented per priority? “
STEP 2: System Recommendation
For this part of the story, I created 2 controls that will allow to filter the other widgets by System and Priority. They will allow us to focus on the system or priority we want in two clicks. Moreover, the other widgets are:
- DISTRIBUTION: % of notes per system and per priority
- TREND: Notes per System for this month
- HEATMAP: Notes by priority and system
- TREND: Notes per System for the current year
- COUNT: Number of notes for selected Systems
- COUNT: Notes per System filtered by priority HOTNEWS and HIGH PRIORITY
For example, you can select only one system and all widgets are automatically updated and will consider only the selected system. Typical questions that this dashboard can answer are: How many notes in function these filters have been released for this system? Or which system according to the priory needs attention?
For this second part, I added another control that filters according to the software component. So, these 4 widgets can be filtered by system, by priority but also by software component. Maybe you want to focus only on the special software component per specific system. And I created a summary table with some details to have specifically the Description. Also, you can create jump-in from the SAC to an external URL. Indeed, it is interesting to be able to access system recommendation of the selected system.
STEP 2: Configuration and Security analytics
In this section also, I have created a control by System that will allow us to directly check the non-conformity of each policy by System. I have created 3 widgets to show the possibilities you have to represent the percentage of non-compliance policies.
Conclusion
Through the platform SAP Analytics Cloud, we can mix different data sources from different applications of different systems or products in one consistent Story/Dashboard. Here, we want to analyse the whole system and with this approach, we can get actionable insights to ensure secure, up to date, healthy running system.
Thanks for reading and don’t hesitate to share feedback or thoughts in a comment!
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