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Both Holmes and Policy adopt Drools as the rules engine. The main difference between these two projects is that Holmes is mainly targeted at correlation analysis between different alarms while Policy is aimed to implement control loops by triggering a series of actions. Briefly speaking, Holmes is targeted at root cause analysis but policy is aimed for auto-healing/auto-scaling.
Policy does not need to face the original alarms directly with the help of Holmes. The root cause is picked out from all the original alarms by Holmes and then, the most suitable policy ID is selected and published accordingly. In this way, Policy is liberated from triggering similar or duplicated actions which are caused by the alarms with internal relations. For example, if there are 3 events A, B and C which could lead to a power down fault, and B and C are caused by A. Without Holmes, all of these 3 events will be sent to Policy and 3 corresponding actions are going to be triggered. After we add Holmes to the close loop controller and make it the upstream system of Policy, only Event A will be sent to Policy and thus only one action will be triggered, which makes the close loop control more precise and efficient. A Scenario without Holmes
A Scenario with Holmes
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Scope:
Alarm Correlation Rule Management
- Holmes provides basic rule management functionalities which allow users to design, create or modify rules via a rule designer.
Collect Alarms from Different Alarm Sources
- Holmes supports different kinds of alarm sources, including NFV, SDN and any other legacy systems (as long as the corresponding interfaces of the source system are exposed).
- Alarm Analysis
- Holmes can pick out the root cause from the ocean of alarms with the assistance of the topology information provided by other related systems.
- Persistence of the Results of Data Analyses
- All analytic results are written to DB for persistence.
- Holmes provides the functionality for users to view the statistical result of data analysis.
- Publish the Analytic Results to Subscribers
- Besides result persistence, Holmes publishes the analytic results to a specific topic. Any potential users can subscribe to the topic to get the results in real time.
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