MMC control for failing flows consistently
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1) The Mule Management Console (MMC) is a tool for deploying and monitoring Mule applications and flows. 2) By default, MMC will raise alerts for each exception encountered but does not consider failure ratios over time. 3) The document proposes a solution using Java code to calculate failure ratios, Spring to call this code periodically, and JMX to expose the ratio as a bean monitored by MMC alerts. This allows alerts based on consistent flow failures rather than each individual exception.
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MMC control for failing flows consistently
- 2. Mule Management Console ( MMC ) is a great tool to deploy Mule applications and control. Using MMC you can perform many operations like Deploy, Un deploy, Redeploy along with Monitoring of flows etc. MMC provides options to monitor the failing flows and inform people about failures. In MMC Alert mechanism you can create Alert definitions for different types of exceptions and send mail to people using Alert notifications.
- 3. Typically MMC will raise alerts for each exception it encountered on the configured deployed applications. There is no intelligent mechanism on MMC itself to raise the Alerts based on exception ratio ( Based on no of service calls and no of failures among that )
- 4. Unfortunately there is no ‘out of the box’ MMC feature to solve this, so we have to cater for it ourselves. Luckily Mule provides some APIs that give us good statistical information. Using these APIs, we can write a small class that calculates the ratio of the error messages coming in a flow compared to the messages that were processed successfully. To Monitoring the consistently failing flows from MMC and raising alerts on ratio based instead of for each exception, we can add 1) Java class to calculate the ratio. 2) Spring code to call the Java class for a period of time Continuously. 3) Spring code to expose value as Mbean 4) Alert creation in MMC for the JMX value (Mbean) Now Will see how to Implement this
- 5. Consider a simple web service like below
- 6. Now we will write Java code that calculate the failure ratio
- 8. The idea is to have the monitor() method execute every couple of seconds. On each execution, we receive updated statistics of execution errors versus completed executions. From these values, we subtract the same values recorded in the previous run so that we get the values for just this period. Once this calculation is complete, we divide the errors with the total events to get a ratio of the two values. If the ratio exceeds a certain threshold (by default set to 0.5), then the String class variable constantlyFailingString is set to true. Having the monitoring code ready, we need to instruct Mule to execute this code every few seconds; 10 seconds for example . We also need to tell ConsistentlyFailingMonitor which Flow to monitor. Spring comes in very handy to do just that. Spring code we need add the in the simple web service mule flow and it follows like
- 9. Below XML code shows the call of Java code for every 20000 milliseconds time
- 10. So at this stage, we have a class monitoring our flow for a stream of consistently failing messages. This is all well and good, but we need a way to raise an alert if our flow is failing. For this will use JMX attribute. The value of ratio we stored in a variable that we need to expose as a Bean, SO MMC will monitor bean and if it crossed the mentioned thresh hold value, it will raise Alert. To expose as Bean again we need to use Spring and the XML code follows like below
- 11. To Review what ever done, it follows like 1) We created sample web service. 2) We created Java code to monitor the failures and calculate ratio. 3) Configured Spring code in Mule flow, to call the Java code continuously. 4) Configured Spring code to expose the Ration Value as bean. After these steps, below steps need be done in MMC 5) Create alert definition for the JMX value and configure the threshold value. Whenever the JMX value (Ration value ) crosses the threshold value, MMC will raise Alert. I hope this will help.
- 12. THANK YOU By Ramakrishna Narkedamilli