Server monitoring means tools and approaches used for auditing the application performance as well as that of web servers. Basically, it refers to gathering machine- and infrastructure-level metrics like memory usage, Disk I/O, CPU utilization, and throughput. Though these metrics are helpful in monitoring the health of their infrastructure, they fail to identify and troubleshoot issues with respect to application code.
Fine tune slow performance by going down to code level detail
Foresee server health and map your application topology
Track important server metrics and trend performance over time
Resolve issues before they affect your end users
No Automatic Application Discovery with Server Monitoring Tools
AppDynamics discovers and maps your application topology and shows where the latency exists amid different application tiers.
Server Monitoring Tools Lack Business Transaction Context
Unlike server monitoring, application monitoring understands Business Transactions. This makes it easy to prioritize performance bottlenecks on the basis of their criticality and the transactions that they affect.
Agentless Server Tracks Can't Do Call Stack Traces
Server monitoring software lacks code-level insight into performance bottlenecks. But AppDynamics provides class and method-level detail about performance bottlenecks, which helps to identify and solve problems.
Server Monitoring Tools Use Basic Alerting Thresholds
Many server monitoring tools have alerting abilities, but in its case, the static alerts are set either too high or too low. This leads to either few or too many alerts but all alerts tend to be inaccurate. In the case of AppDynamics, you get alerts from algorithms that measure deviation from normal behavior so that you get accurate alerts.
Server monitoring a foundational component to any data center monitoring architecture but it has become a crutch and a deterrent to successfully building out a holistic monitoring platform. Servers exist to run applications and you will never properly monitor applications with server monitoring...
In the last post I covered several architectural techniques you can use to build a highly scalable, failure resistant application in the cloud. However, these architectural changes – along with the inherent unreliability of the cloud – introduce some new problems for application performance...