Adtech Leader Natural Intelligence Now Resolving Glitches in Minutes Rather than Days

Natural Intelligence runs comparison websites that generate millions in ad traffic. A glitch could easily cost the company thousands in ad revenue. VP R&D Lior Schachter shares the difference Anodot’s real-time analytics, with machine learning anomaly detection, has made across the company.

Creating an Alert in Anodot is Now Easier Than Ever

When you first set up your Anodot account, you create alerts on the KPIs that matter most to you. Advanced alert configurations enable you to define various parameters so that you only get alerts that are important to you: selecting the metric, building a query, grouping the data by dimensions, selecting triggers and conditions, choosing who and where it should be sent to, and so on.

Performance Marketing Company Replaces In-House Business Monitoring System With Anodot

In performance marketing, KPIs are directly proportional to revenue. Avantis is a performance marketing company that, prior to Anodot, had used a variety of in-house monitoring solutions and SAS tools to monitor the KPIs that drove their business. But they found their top metrics, such as impressions, clicks, click-through rate (CTR) and postbacks, were often much different than their publishers’.

Leading Chief Data Scientists Weigh in on Building Time Series Anomaly Detection

In our recent webinar on what it takes to build time series anomaly detection, industry experts Arun Kejariwal, Ira Cohen and Ben Lorica shared valuable advice for ways to successfully implement and execute anomaly detection systems in today’s increasingly complex corporate world.


5 Best Practices for Using AI to Automatically Monitor Your Kubernetes Environment

If you happen to be running multiple clusters, each with a large number of services, you’ll find that it’s rather impractical to use static alerts, such as “number of pods < X” or “ingress requests > Y”, or to simply measure the number of HTTP errors. Values fluctuate for every region, data center, cluster, etc. It’s difficult to manually adjust alerts and, when not done properly, you either get way too many false-positives or you could miss a key event.


AI/ML - Are We Using It in the Right Context?

There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketers stepped in. Widespread overuse of the terms AI/ML in marketing have managed to thoroughly confuse the meanings of these words.