What is infrastructure monitoring?

These components, from memory chips and processors to the operating system and application server, each play a vital role in delivering an application or service to end users, and they can exist across cloud, on-premise and hybrid environments. Monitoring these systems is necessary because application downtime and service degradation can result in user churn, significant revenue loss and damage to the company’s reputation.

Infrastructure monitoring involves employing specialized tools that automatically collect, aggregate and analyze data and metrics from servers, virtual machines, containers, databases and other back-end components. Infrastructure monitoring tools cover a wide range of parameters such as central processing unit (CPU) and memory usage, network traffic, disk space, response times, error rates and more. They generate alerts or notifications when predefined thresholds are exceeded or anomalies are detected, allowing IT teams to investigate and address potential issues before they escalate. The ultimate goal of infrastructure monitoring is to ensure reliable, secure and efficient operations of the IT infrastructure.

Infrastructure monitoring has evolved significantly over the years, driven by advancements in technology and changing business needs. Initially, infrastructure monitoring focused primarily on hardware components in the data center such as servers and network devices. These static components were relatively easy to monitor.

With the adoption of cloud platforms, including Amazon Web Services, Microsoft Azure and Google Cloud, infrastructure monitoring has expanded to include virtualized environments, cloud infrastructure, containers, microservices, Kubernetes and other modern technologies. Along with the ability to monitor ephemeral infrastructure components, today’s infrastructure monitoring software must incorporate automation, artificial intelligence, real-time monitoring, end-to-end visibility, scalability, flexibility, DevOps integration, visualization, analytics and built-in security features.

Infrastructure monitoring works by continuously collecting data from the various traditional and cloud-native components of an organization's IT infrastructure and analyzing that data to assess the systems’ performance, availability and health.

The two methods for collecting system data are agent-based and agentless.

An agent is a lightweight software layer installed by engineers on a host (any system or device that needs to be monitored), which collects relevant telemetry data about the state of the system. This process of installing agents on hosts is called instrumentation. With today’s leading infrastructure monitoring solutions, agents are able to use sensors to discover components up and down the infrastructure stack after configuration.

Once everything is fully instrumented, each agent begins collecting a wide range of metrics and measurements that reflect the behavior and status of the infrastructure. These metrics can include CPU and memory utilization, network bandwidth, disk space usage, response times, error rates, transaction counts and more. Ideally, the performance monitoring platform is continuously capturing this data in real time at one-second intervals with no sampling. This type of granularity is a primary benefit of agent-based collection, which makes it easier to identify and troubleshoot issues as they arise.

Agent-based collection also allows for proactive monitoring. By setting up thresholds that trigger alerts when things like CPU utilization exceeds a certain percentage, administrators can stay one step ahead of potential performance issues. Alerts can be sent through email or SMS, or integrated into notification systems like Slack or PagerDuty.

The primary benefit of agents is that data collection is much richer. In addition, things like diagnostics and issue remediation can happen automatically. On the downside, agents consume system resources such as CPU cycles, memory and network bandwidth to collect and transmit monitoring data. This can have a slight impact on system performance if the monitoring is resource-intensive or if a system has limited resources.

Unlike agent-based collection, the agentless method doesn’t require a separate software agent to be installed on the host. It relies on built-in protocols such as Windows Management Instrumentation, Simple Network Management Protocol, Secure Shell protocols and NetFlow to collect and deliver system data to the infrastructure monitoring solution. Often, it is the only option for specialized hardware on which an agent can’t be installed, such as routers, switches and load balancers. It is also used for legacy systems and devices with limited available resources.

One benefit of agentless collection is that it works across different operating systems and platforms as long as the required protocols or application programming interfaces (APIs) are supported. This makes it more flexible in heterogeneous environments.

Agentless also reduces performance impact. Since agentless monitoring doesn't require software agents running on individual systems, there is no additional resource consumption or performance impact on the monitored systems.

Agentless monitoring capabilities rely on the data exposed through network protocols or APIs. Therefore, the available data may be limited compared to agent-based collection, as not all system-level metrics or application-specific data may be accessible through these methods. In addition, the agentless method is heavily network-dependent and will most likely fail should the network go offline.

With today’s complex modern architectures, both agent and agentless collection methods are used. Leading infrastructure monitoring solutions can centrally manage both agent and agentless collection methods.

Infrastructure monitoring serves various use cases across different industries and organizations. The following are some common ways that infrastructure monitoring can be utilized:

These are just a few examples of how infrastructure monitoring can be utilized. Ideal use cases will vary depending on the industry, organization size and the criticality of the monitored systems for business operations.

Whatever your business needs, there are several best practices to follow that will help you make the most of your investment in an infrastructure monitoring solution.

Establish baseline performance metrics and KPIs for your infrastructure components during normal operation. Baselines and KPIs provide a reference point for detecting anomalies and deviations from normal behavior. As your infrastructure evolves, update and adjust baselines so you don’t develop any blind spots.

Create alerts that are meaningful, actionable and relevant to the specific problem at hand. Avoid creating alert noise by setting proper thresholds and filtering out false positives. Ensure that alerts provide sufficient information to diagnose and resolve issues efficiently.

When configuring a monitoring solution to deliver notifications about specific types of events, determine which types of notifications should be prioritized. Major incidents like server outages that affect the user experience must be addressed with extreme urgency.

Waiting until an actual emergency happens is no time to be putting your monitoring system to the test. Schedule a test run of your monitoring system to ensure everything is functioning exactly as it should.

Today’s leading infrastructure monitoring solutions allow you to create custom-configured dashboards based on each user’s role. After all, the data and alerts that a member of the SecOps team cares about will be vastly different than those relevant to a CFO.

If you encounter issues or problems with configuring and using your infrastructure monitoring solution, lean on the provider for support. Let their consultants, help center and support staff guide your troubleshooting toward a resolution.

By following these best practices, organizations can establish a robust and effective infrastructure monitoring framework that provides actionable insights, enables proactive problem resolution and contributes to the overall stability and performance of their IT systems.