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DevOps is concern as a group of concepts, which catalyzed into a movement and rapidly spreading all over the technical community.
When a company starts with devops mentality to develop applications the disabilities of the processes became clear.
DevOps is a term which arising to the collision of two major trends. The first “agile system” or “agile operations” it jumped from applying latest agile and tends tactics to the operations work. Second understands the value of collaboration among development and operations staff over all stages of the development.
When companies understand that though product modernizations are distributed to faster production and value is to deliver to customers on time then operational hurdles are more frequent which slow down the process of innovation. The devOps is an actively supporting process that clears of inefficiencies.
The top best practices are giving below which enable such change.
To collect the monitoring data many of organization are depend on 4 tools but it didn’t occur deliberately. Innovation has been occur every year in the monitoring space, so to fulfill all the monitoring requirements a large range of tools is using, but all these tools are not familiar to one another and require lot of work to combining the data. To seek out this problem a monitoring tool known as Full stack (all in one application) is introduced. It stipulates information about monitoring and inters link information so a single tool interprets all the monitoring, which four or more tool can be done.
Monitoring tools concentrate on individual data streams then perform analytics on streams e g anomaly detection this is a time taken manual process. To solve this first data must be enriched with contextual information, it is effective for prioritizing issues.
When something in the system breaks many of individual components not work well, that is a side effect of finegrained systems. The good way is to use contextual information to group alerts, it minimize the higher level problem and increases the speed of problem resolutions.
Depending on automated analysis to find out the reasons of operational issues is the essential in the highly dynamic environment using knowledge based algorithms, for monitoring data is very effective on many cases.
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