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Internet complexity impacts sites
When it comes to the web, the name of the game is innovation.Networking protocols, web availability, and even hardware for spreadingthe Internet from ISPs has changed drastically from the beginning to now.With the evolution of smaller and smaller computer chips, the kinds of devices accessing the Internet today are more diverse than ever.
Websiteshaveevolvedalongside, from the elegant simplicity of the first binary code to the robust coding languages used today, in order to keep up.But regardless of how robust the language is, perfect website operation for all users is unattainable.
Where complexity can go wrong...and right
Features of a website that may work well for someone on a laptop might be deal-breakers to a person on a mobile, not to mention that users on mobile and tablet devices all have different screen sizes, chipsets,operating systems, and browsers.Developing a website that will work well for all users is very difficult to do.
A lot can go wrong during a page load, too. Site servers,routing protocols, service providers, and DNS serversare all potential points offailureduring a request for a page load. A site can be unreachable through no fault of your own, so perfect operation under all conditions is impossible.
However,new advancements in web technology has led to other technological developmentthat can help make monitoring easierandspeed upresponseto issues with website operation.Things like artificial intelligenceand machine learningcan be used to automate data identification.That includes data related to website operation– and there is no better example of this than Anomaly Detection.
What is Anomaly Detection?
Anomaly Detection implements machine learning to detect issues.Using both Real User and Synthetic Monitoringdata, Anomaly Detectionconstantly checks for real and potential hang-ups inperformance, JavaScript Errors, and vendor serviceor tags.
Blue Triangle’s Anomaly Detection can pinpoint issues on your site and show you the cause of the problem. We are continuallyrefining detection methods anddeveloping new methods for detecting anomalies, too.
Traditional site performance monitoring requires things like performance alerts, outage alerts,and user feedback. When the issue is only on a cart page for some users,for instance,the issue may go undetected for some time, and when a problemisdetected,it will require digging to identify which users it affects and why.
By usingAnomaly Detection to monitor data,youcan manageyoursite and keep it running smoothly in a way that takes a fraction of the time. Anomaly Detection replaces the need to comb through your site for errors or wait for user feedback.
How does it help?
Time is one of the most important things on your site. If there is a problem, how long does it persist? Howlong does it take to find it? To fix it? Anomaly Detection saves time in a couple of ways.
Anomaly Detection saves timebyautomating the alerting process. There areupwards of 10,000 elements on most sites, notincludingpages andvendor servicesor tags.Configuring alerts on even a subset of this data would take days or maybe weeks, not to mention that multiple things can go wrong – the First Byte time might be high, or perhaps Onload, or maybe JavaScript errors start happening with increasing frequency.
Amanual configurationof alerts on that many elementswould take an overwhelming amount ofresourcesthat would be better spent elsewhere.Real User data is gatheredforboth Desktop and Mobile devicesas well,so you can drill down into different types of userexperiences.This is especially valuable to smaller businesses that manage their own websites without an operations team.
Through alerting and notifying about potential problems on the site as a whole, Anomaly Detection also saves the time it would normally take to find specific issues.A site anomaly will let you know what changed and where. Importantly, it will also let you know how significant an anomaly is, allowingyou to narrow your focus to the most pressing current issues on your site.
What sets Anomaly Detection apart?
Anomaly Detection prevents anomaly detection during regular periods of low traffic, like overnight hours or maintenance windows.When a potential issue is found, it will also rate the severity of the issue bysignificance, pushingthe most significant issues to the top spotinyournotifications.
Here is howthe machine learningworks:
- Statistical averaging creates atrendof the same hourover the previous four weeksto create a baseline
- The data is logged by time of day as well as the day of the weekso irregularities are detected by time of day and day of week
- When an issue is found by comparing to the baseline,the machine learning algorithms rate the severity by the amount of change from baseline by each metric
This results in periods of low traffic being compared to similar periods of low traffic, and prevents things like daytime traffic on a weekday being compared to daytime traffic on a weekend.Because of this, Anomaly Detection generates only valuable alerts, making it a powerful reporting tool for any business.
Astheissues are found and reported, they are color coded based on severity, with the most pressing disruptions to your site colored in red and brought to the top of the list. Users can then easily prioritize fixing the most important problemsfirst andwork their way down to less severe issues.
Using Anomaly Detection to optimize monitoring
With a single click, users can instantly drill down into theissuesto find the source of the problem.Depending on where the issue is found, you will be able tosee domain and tag performance trended, performance on different pages and different devices in both synthetic and real userdata, and also JavaScript error reporting.
Drilling down into the issues lets you utilize the power of these reporting pages, and the diversity of analysis lets you pinpoint the exact problem and take steps to fix it. Not only that, but by saving time in identifying issues, you can fix any problems affecting your bottom line faster.
