What is cloud performance monitoring?

Application performance monitoring

Cloud performance monitoring is often seen as simply being application performance monitoring. It is a part of application performance management (APM) and is the task of monitoring the overall performance of software applications. APM at large includes monitoring availability, usability issues, and anything that could impact the end user experience, not simply the raw performance. APM includes functions, such as, for example:

• Digital experience monitoring (end-to-end user experience monitoring)
• Application discovery, tracing, and diagnostics
• Application analytics

APM thus goes beyond pure cloud application performance monitoring and is a system for not only optimizing the performance of applications, but to discover the pain points of end users, improve their experience, perform diagnostics on the applications, and discover the root causes of issues more efficiently than by performance monitoring alone. APM solutions help IT administrators to get the most comprehensive overview of the performance metrics for business-critical applications, and can help to improve and update software that is vital for an organization's infrastructure.

Cloud performance monitoring is contained in APM, and it goes beyond the scope of simple cloud performance management. Here we will focus specifically only on cloud performance monitoring, but it was important to clarify what APM is, as it is a term that is often paired with performance monitoring.

High performance cloud computing

High performance computing (HPC) is a term that describes the processing of high-volume workloads that require vast computing powers, or the management of large datasets. Such workloads are increasingly being migrated to the cloud, and high performance computing on the  cloud is one of the main users of cloud services. With the scalability and default power of many virtual servers offered by cloud providers, these days it is possible for any organization to execute HPC workloads on the cloud. Previously such workloads required a large amount of resources that were not economically and/or technically feasible for small companies.

Whether you need high capacity processing, or need to sustain short bursts of high CPU usage, or are managing large datasets, high performance cloud computing is your solution. Cloud performance monitoring is vital to implement with HPC workloads, as the performance in high performance computing is critical for the application to perform its tasks, and no disruptions or dropouts can be tolerated. Keeping track of the key metrics in an application generating vast CPU loads or volumes of data is even more of a necessity for cloud administrators to implement than with less power-hungry applications.

Cloud performance monitoring tools can handle high-demand HPC applications just as well as handling those less heavy on resources. High performance computing on cloud is an increasing requirement for today's enterprise businesses, and necessarily needs to fall within cloud performance management to ensure that all of the HPC workloads are running at their most efficient performance.

What metrics to check in cloud performance monitoring?

Enhancing cloud performances through monitoring is a complex endeavor that includes analyzing many metrics, depending on the type of service and the resource used. Some are more CPU-heavy, others rely more on an efficient network, and many others need to be as responsive as possible and avoid any type of lag or delays.

Cloud performance management of course includes monitoring and this relies mainly on a series of metrics to check. These metrics assume different names depending on the cloud  provider and the exact resource or service monitored. Identifying the metrics should be trivial however, as most of their names are self-explanatory. In the following chapter the metrics and their use for your monitoring will be introduced. 

1. Resource utilization metrics

In a cloud environment, monitoring resource utilization is fundamental for achieving operational efficiency and optimized performance. Key metrics include CPU, memory, and storage usage - these indicate how efficiently your cloud application uses the resources it runs on. By collecting and analyzing these performance data, administrators can ensure effective resource allocation and prevent overprovisioning or resource exhaustion, both of which can degrade system performance. Resource utilization metrics often go hand in hand with network health metrics as they are key for transferring data and receiving external requests. 

2. Network health metrics

The second essential category involves network health, encompassing latency, throughput, and error rates. As we are speaking of cloud applications and resources, network health is key for transferring data and receiving external requests. If a network is congested or its connections are shaky, global cloud performances can greatly suffer. Maintaining optimal network conditions is critical to ensuring efficient data transfer within and outside your cloud infrastructure, which is why proactively monitoring these metrics is essential.

3. Availability and uptime metrics

In the worst cases, interruptions and complete service outages can occur. Comprehensive monitoring must include checking the uptime and availability of every application or cloud resource - a step that may seem obvious but is often taken for granted. Most cloud performance monitoring tools or application performance management systems support regular pinging of applications to ensure they remain reachable and active. 

4. End-to-end latency and application response time

Also relevant to network performance are all metrics related to end-to-end latency and application response time. These metrics provide real-time visibility into the time it takes for a user request to receive a response. Typically - though not exclusively - they inform cloud administrators about the health of the network, although poor performance may also stem from issues within the application itself. 

5. Auto-scaling and queue related metrics 

If using an auto-scaling system, as often happens with cloud providers, make sure to check the metrics related to its efficiency, such as the number of instances added or removed from a system. If queues are applicable in your case, queue-related metrics should also be taken into consideration in your monitoring efforts.

Wrapping up

Performance-wise, these are the most important metrics to keep an eye on. They are far from the only ones, and depending on your infrastructure and the cloud resources that it uses, tens of other metrics may be worth monitoring. Cloud performance monitoring is a complex topic, the tools that perform it, as with Checkmk, include lots of checks to encompass the largest sets of metrics. For the most comprehensive possible overview of your cloud infrastructure and its performance, implement a monitoring tool that is capable of providing you with as many metrics as possible. Checkmk aims to do just that. Supporting multiple cloud providers (AWS, Azure, and GCP), Checkmk can perform cloud performance monitoring for you, from moderate up to HPC scenarios.