Cloud Server Monitoring is quite different from on-premises server monitoring and requires a fundamental change in mindset. The situation is further complicated when working with hybrid cloud infrastructures or pursuing a multi-provider cloud strategy. Two key questions that need to be answered are...
How does IT ensure they are delivering the desired performance for cloud services while at the same time operating within an appropriate cost structure?
What are the attributes of a proper cloud server monitoring strategy?
How are cloud servers different from on-premises?
Organizations continue to wrestle with what applications should move to cloud servers and which should remain on-premises. The differences between the two server deployment models impact the approach organizations take to server monitoring.
Attributes for proper cloud monitoring
Monitor with no discernible overhead – The gathering of key performance indicators (KPIs) is an integral part of any server monitoring initiative. Monitoring should be non-intrusive, meaning there should be no discernible overhead generated by the monitoring technology in the targeted environment. The last thing an IT organization wants to do is implement server monitoring that adversely affects cloud or application performance.
Proactive and Intelligent Alerting - The goal of server monitoring is to anticipate and then alert IT staff to server and application performance issues. Keeping the information sent to IT relevant and timely goes a long way towards a server monitoring strategy that saves time rather than takes time.
|Organizations can pay a heavy price for mis-sizing cloud resources - both in terms of lost productivity and revenue as well as the time and effort required to counteract any resistance towards future cloud initiatives.
An even more costly problem occurs when cloud resources are over allocated, as even though the servers and accompanying applications are performing to expectations they are operating at a significantly higher and wasteful cost structure.
Over allocating server resources is a more insidious problem to detect because it requires either a bit of sleuthing by IT or the implementation of technology with intelligent alerting.
The problem can only be uncovered when actual resource usage is correlated with available cloud resources.
|Longitude dashboard showing hybrid cloud health|
Capacity Planning - Collecting and correlating server performance behavior is an invaluable tool that helps predict what the future holds.
Server capacity planning is ultimately about getting advanced warning of resource problems that will not only impact the business, but also affect IT’s reputation. Remember, while many a success are taken for granted, it only takes a high-profile mistake to quickly destroy credibility. IT needs to be proactive about adjusting the IT infrastructure to accommodate changes in the business.
Capacity planning is never a one-and-done process as server workloads are constantly changing. While the easiest resource issues to spot are those that are sudden and immediately impactful, the more challenging diagnosis occurs when resource depletion problem is slow and gradual. It is critical that IT maintain a constant watch even when performance doesn't seem to be an issue.
|Longitude Summary Report showing server health|
Ultimately it is about ensuring consistent and cost-efficient service levels across multiple environments. This can only be accomplished by aggregating and evaluating public, private, and hybrid resources.
Although the deployment of cloud resources can be quick and easy there can be a significant trade off between expediency and cost. Proper cloud server monitoring needs to deliver to IT the decisive information they need to accurately size and optimize their deployments.
Implemented properly, server monitoring is not heavy in terms of system overhead or arduous in terms of the effort required of IT to deploy, manage, and interpret.
The challenge is optimizing the time required of IT to manage and monitor cloud resources against the actual costs of the cloud infrastructure itself and maximizing IT's return-on-effort. This can only be accomplished with automated monitoring, reporting, and capacity planning.