What is an Anomaly? And How to Detect Them

What is an anomaly?

a·nom·a·ly/əˈnäməlē/ noun

1. something that deviates from what is standard, normal, or expected. "There are a number of anomalies in the present system."

This is the same in IT. An anomaly in your IT environment means that something is not running or performing as expected. Some anomalies are transient and have little to no impact. Others are early warning signs that something troublesome is brewing. It is the latter anomalies that you need to proactively recognize and analyze. Proactively triaging a troublesome anomaly before it wreaks havoc in your IT environment can eliminate downtime, unacceptable performance and unexpected results.

Is the black swan in the image, above, an innocuous anomaly or a troublesome one? Probably innocuous, but if its large size and perhaps aggressive personality threatened the lives of the white swans, it could be troublesome. Unfortunately, IT anomalies are not always as easy to spot as a black swan in a sea of white ones!

In this article, you’ll learn what anomaly detection is all about and some common strategies that companies use. 

Introduction to anomaly detection

Companies today are relying on technology more than ever thanks to widespread digital transformation and cloud initiatives. Digital transformation - and the complexity and disruption that comes with it - is increasing the need for safe, efficient and reliable IT environments. 

But maintaining operational IT stability is very difficult when considering the complex and dynamic nature of today’s IT environments. In fact, IT environments are constantly changing, with new network devices, users and software versions coming into existence. This ever-evolving environment increases risk and puts more pressure on IT professionals — especially those with budget and staffing limitations.

Given these points, anomaly detection is becoming increasingly important for IT departments. Technology professionals need to have a finger on the pulse of their various systems. By doing so, they can immediately detect changes across multiple systems when they arise. 

What Is anomaly detection?

An anomaly is something that deviates from expectations. If you had a collection of Granny Smith green apples and there was one blue apple in there, the blue apple is an anomaly. Is it something to be concerned about? Blue apples are highly unusual, in fact, they probably don’t exist. So, yes, that would be an apple you’d want to isolate from the rest of your apples and maybe not eat until you have had a chance to investigate further. 

Some anomalies matter and some don’t. The issue for IT teams is to know when anomalies occur - and to proactively address ones that could go on to become full-blown incidents.

Anomaly detection refers to the discovery of abnormal events that deviate from standard operating procedures within IT environments. Within an IT environment, there are multiple categories of anomalies. Here are a few examples. 

Network anomalies

Network anomalies occur when there are changes in network behavior. One of the most common examples is a network traffic anomaly, where a network suddenly receives a large volume of incoming requests. In these scenarios, it’s important to have real-time visibility to determine whether the traffic is legitimate or indicative of a threat like a DDoS attack. 

Application performance anomalies

It’s also important to track deviations within applications — especially high-volume applications that handle critical workloads and process sensitive data. Application performance monitoring typically involves scanning system performance to determine whether components are up or down. As responsiveness degrades, latency increases.

How to detect an anomaly in your IT environment

Most companies today are using a variety of monitoring and security tools to detect changes in their environments. Despite this, companies often have glaring blind spots that make it difficult to detect and remediate anomalies.  

For best results, companies need to focus on connecting the dots among all their various monitoring tools and centralize visibility across all IT systems. Having a unified approach allows organizations to move with greater speed and precision and avoid missing critical changes. 

With that in mind, here’s a breakdown of what you need to effectively detect anomalies across your IT environment. 

Telemetry data

It’s necessary to combine telemetry data like events, logs and metrics across external IT deployment, provisioning and management tools. Ideally, your system should make it fast and easy to ingest and convert data into actionable insights. Otherwise, you could encounter slowdowns that could make it harder to act quickly and remediate issues. 

Event tracking

Engineers look for small events or activities when engaging in anomaly detection. In most cases, it’s possible to trace large issues like data breaches and system failures to small misconfigurations, policy changes and deployment errors, among other things.  

Individual events may not provide a great deal of insight. But when you string events together, it can become possible to identify larger trends. The trick is to track and monitor events and trends in real time so that you can proactively address issues as they materialize. 

Historical analysis

In order to investigate anomalies, you need to be able to go back in time and analyze your environment. This is necessary for comparing events and tracking changes.

Tracing

Tracing is an observability technique that enables you to analyze how requests and actions perform across distributed systems — and where breakdowns may occur.

At a high level, tracing allows engineers to observe how containerized, serverless, and microservices-architected applications operate while making it easier to identify areas that could be improved, where bottlenecks are occurring, and more. 

Simply put, traces are a critical component of observability since it helps teams understand more about the issues they’re trying to resolve or the features they’re trying to improve. This, in turn, makes it easier to build highly performant applications that deliver strong user experiences.

Real-time communication

It’s impossible to overstate the importance of communication with anomaly detection. IT teams need to communicate efficiently with one another when investigating system anomalies. At the same time, IT leaders need to communicate with other departments when making changes that could disrupt or impact operations.  

As such, it helps to use a platform like Slack, Discord or Teams to provide timely updates and answer questions. A common platform can also help facilitate communication and interaction when performing root cause troubleshooting and investigating system changes and errors. 

Full stack observability

At the end of the day, data points are meaningless without context. You need to have context in place in order for data to be actionable. 

This is where it helps to have full-stack observability and topology data across your entire stack — including virtual machines, networks, containers and services. Having full-stack observability eliminates blind spots and helps detect granular anomalies that would otherwise be impossible to discover. 

Why detecting anomalies matters

It may be tempting to avoid allocating resources to anomaly detection and choose to deal with issues only when they arise. But this approach is very risky, especially if your business is entirely dependent on its networks and applications.  

It’s far more efficient and cost-effective to take a proactive approach to anomaly detection and focus on detecting issues early on. Here are some of the top reasons why detecting anomalies matters.

Maximize uptime

IT teams need to keep a close watch on underlying systems and applications to maximize uptime and avoid outages. Oftentimes, it’s possible to avoid outages by detecting issues ahead of time and making necessary adjustments. This improves network health and system reliability. 

Ensure operational efficiency

Companies today need to have high-performing applications and digital services. Poor experiences can cause customers to lose faith and seek out alternative options. By prioritizing anomaly detection, it’s possible to enhance operational efficiency and guarantee a stronger user experience. This leads to happier customers, better reviews, and healthier profits.  

How StackState streamlines anomaly detection

StackState offers a full-stack observability platform that streamlines anomaly detection — combining topology, telemetry and tracing data, over time.  

With StackState in place, your IT teams will have an easy time discovering and eliminating potentially dangerous anomalies across all IT systems, including microservices, containers, web services, serverless, cloud and on-prem environments.  

StackState provides the insights that companies need to identify and resolve potential anomalies, solve IT issues promptly and ensure reliability and uptime. Your business will lower the time and cost of issue resolution and benefit from a healthier and more responsive IT environment containing fewer bugs and vulnerabilities.  

To experience StackState in action, request a demo today.