How businesses use IT infrastructure monitoring to support their tech stack

It’s no secret that enterprise IT infrastructures are becoming steadily more complex, while performance and security are pivotal to business operations. Making sure all aspects of a data center are working in peak condition is both critical and increasingly difficult. As a result, while IT infrastructure monitoring has been a key part of enterprise tech strategies for a while, it is recently undergoing a transformation to keep up with virtualized and distributed environments.

Find out how to leverage IT infrastructure monitoring in your business, what to look for in monitoring tools, and how AI is transforming the industry.

What is IT infrastructure monitoring?

At its most basic, IT infrastructure monitoring tracks and analyses performance and health metrics of a data center infrastructure. This covers all aspects of the environment, including hardware, software, and applications.

While traditional monitoring was primarily focused on data center hardware, businesses and suppliers have had to adapt their approach to meet the requirements of emerging technologies and virtualized or distributed environments. This has led to a more holistic approach, covering both physical and virtual IT components and introducing automated and AI-native functions.

How does IT infrastructure monitoring work?

Businesses install or utilize specialized tools to collect and analyze data from data center components, including servers, operating systems, and storage devices.

The collection tools send the information to the monitoring platform, which then generates alerts of any anomalies detected or thresholds exceeded. There are two primary methods of IT infrastructure monitoring:

Method	Agent-based	Agentless
How it works	Businesses install a software on a system or device (instrumentation). This software is the agent, which collects metrics on the condition and behaviour of the host in real time.	Teams use built-in protocols, such as Windows Management Instrumentation, rather than installing software. These collect and deliver data to the monitoring solution.
Benefits	Proactive, real-time measurement facilitates the rapid identification and resolution of issues.	Works across all supported platforms rather than individual resources, offering flexibility in multi-vendor, multi-model environments. Reduced resource usage and performance impact compared to agents.
Drawbacks	Agents are resource intensive, which may put pressure on legacy systems or those with already-dense workloads.	Agentless monitoring offers limited data in comparison to agent-based monitoring. Network dependent.

Agentless monitoring is particularly useful for older systems with more limited resources, and hardware doesn’t allow for the installation of agents (routers and switches often use proprietary, closed OS which don’t allow for third-party installations).

Modern infrastructures tend to use a hybrid approach, leveraging solution platforms able to manage both methods.

Monitoring metrics and KPIs

Key metrics IT teams should track cover a range of parameters, including:

• Memory usage: The amount of RAM in use to run applications, services, and processes.
• CPU utilization: The percentage of processing capacity in use by the system.
• Network traffic: The volume of data transmitted and received across the network.
• Bandwidth utilization: A network’s total available data capacity in active use.
• Throughput: The rate at which data is successfully transmitted or processed over time.
• Storage usage: The amount of used storage capacity on a disk or storage device.
• Response times: How quickly a device, application, or service responds to requests.
• Error rates: The frequency of system, application, or network malfunctions over a given period.
• Humidity: The air moisture levels in the data center environment.
• Temperature: The heat levels within hardware devices or the data center environment.
• Disk I/O: The rate at which a hard drive or storage device is accessed for read and write operations.

Infrastructure layers that require monitoring – and the metrics to look out for

IT infrastructures are made up of distinct layers which work together. Each of these layers requires monitoring to ensure stability, security, and high performance. Here is a quick breakdown of the main layers of a data center infrastructure and the key performance indicators to keep an eye on:

Layer	What/where is it?	Metrics to monitor
Hardware	Physical components (servers, networking assets, storage devices, cooling equipment, power supplies).	CPU utilization Memory utilization Disk capacity Network throughput Temperature Hardware faults/alerts
Operating system (OS)	Software between the hardware and applications, managing factors such as resources, processes, and memory.	Service/process status System uptime Event log errors
Applications	Software that generates content and provides business functionality (web servers, databases, custom applications, etc.).	Availability Response time Error rate Resource utilization Application log errors

 

When can businesses leverage monitoring?

Making sure all aspects of a data center are working in peak condition is both critical and increasingly challenging. Infrastructure monitoring tools, services and best practices help businesses maintain visibility across their IT environments and utilize the data recovered to keep operations running smoothly.

Monitoring solutions provide real-time alerts when anomalies or performance issues arise. IT teams can then verify any impact on end-users, and quickly resolve bottlenecks, failures, or degrading performance.

Here is how businesses can use infrastructure monitoring to their advantage:

• Troubleshooting issues to safeguard performance and security
• Optimizing performance to make operations more efficient
• Forecasting requirements, such as resource consumption, to plan budget and scaling strategies

 

How to use monitoring to detect bottlenecks and failures early

Identifying bottlenecks and failures quickly is critical to their quick and effective containment and resolution, before the issue affects operations and the user experience.

What is a bottleneck?: Bottlenecks are components or resources that slow down a system’s overall performance by restricting capacity and speed.

Tracking the following metrics helps detect bottlenecks early, promote stability, and optimize connectivity and performance:

Metric	Why it causes bottlenecks	How monitoring helps
CPU saturation	If the central processing unit reaches its maximum processing capacity, it can no longer keep up with incoming workloads, causing performance degradation.	Helps identify when processing resources are reaching their limits.
Network latency and packet loss	High latency and packet loss can slow data transmission and disrupt communication between systems.	Helps detect network bottlenecks that can impact application and service performance.
Connectivity optimization opportunities	Congestion, misconfigurations, and capacity issues can restrict workflow efficiency.	Identifying congestion and capacity constraints highlights opportunities for improvement.

Reducing downtime through proactive monitoring

Leveraging IT infrastructure monitoring tools, and especially AI, facilitates real-time anomaly detection. This helps contain issues quickly, while root-cause analysis allows enterprises to find and resolve the source of the issue before it degrades or causes extended downtime.

Proactive monitoring limits damage and downtime by quickly identifying and treating the root-cause of IT issues.

Infrastructure monitoring best practices

Here are some guidelines to help your enterprise get the most out of its monitoring tools and services:

1. Establish baseline metrics and KPIs. Measuring the standard activity and behaviour of your IT infrastructure helps identify anomalies.
2. Make sure alerts are usable. Unclear or irrelevant alerts can confuse IT teams, leading to ineffective or delayed resolutions.
3. Prioritize notifications by type of event and the criticality of the device.
4. Test monitoring and resolution measures to make sure they work when required.
5. Ensure consistency across teams to avoid visibility gaps and miscommunications.

It is also good practice over the long term to demonstrate if monitoring is improving the stability of your systems with KPIs such as uptime, MTTR, MTTD, incident rates, and service reliability. This helps businesses clarify if their tools or strategies are worth the investment or require reconsiderations.

MTTR: Mean Time to Resolve

MTTD: Mean Time to Detect

Both KPIs should be low, reflecting quick issue detection and resolution.

 

AI Ops and automation in infrastructure monitoring

AIOps means Artificial Intelligence for IT Operations. On the one hand, the boom in AI is causing a range of issues for data centers, from increased water and power usage to memory shortages. On the other, we can’t deny its usefulness. AI is increasingly being utilized in infrastructure monitoring tools for faster and more effective issue resolution. Here are a few ways you can utilize AI to optimize monitoring tasks:

• Noise reduction: instead of sending teams hundreds of minor alerts, AI groups them into one clear, actionable incident.
• Issue prioritization: machine learning can analyze and prioritize vast amounts of data quickly, helping businesses manage the most critical issues first.
• Task automation: automating routine tasks frees up time and focus for human teams and reduces the risk of human error.
• Proactive management: Real-time monitoring and root-cause analysis helps to rapidly resolve existing problems (reducing MTTR) and even predict possible issues in the future.
• Consistency: AI tools which track and support systems across distributed sites provide consistency for teams, as well as improved overall visibility.
• Effective dependency mapping: Mapping helps to understand how the hardware and software relate to each other and therefore predict possible bottlenecks.

Choosing monitoring tools and services

In reality, developing a monitoring strategy and selecting the correct tools for your IT infrastructure depends heavily on your particular business’s systems, current priorities, IT budget, and scaling plans. This means there’s not one sole solution for every enterprise.

However, here are some tips to help you choose the right tools for your data center infrastructure. Businesses should look for:

• Customizable alerts to align with business priorities and circumstances.
• Unified platforms to provide a complete overall context and consistency across teams and systems.
• Cloud-native support for virtualized environments.
• Scalability to keep up with evolving tech stacks.
• Automation capabilities to reduce manual work and risk of human error.
• Real-time monitoring for fast issue detection and resolution.
• Analytics to indicate not just what the issue is, but also why it happened and how to avoid it in the future.

Evernex’s trained engineers can support your data center monitoring and issue resolution strategies, from our local, onsite Smart Hands services to third-party data center maintenance.

Frequently Asked Questions (FAQs)