Redwood City, CA, USA
Jul 11, 2019   |  By Yuval Dror
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.
Jul 11, 2019   |  By Ira Cohen
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.
Jun 27, 2019   |  By Anodot
To keep you up-to-date with what’s going on in anomaly detection, we keep an ongoing list of the biggest glitches happening in the business world. Here is what made waves in June. June 25, 2019 When Dutch telco KPN suffered a major outage on the evening of Tuesday, June 25, the 112 emergency number was also knocked out across the country. “We have no reason to think it was (a hack) and we monitor our systems 24/7,” the company spokesperson told Reuters.
Jun 27, 2019   |  By Aviad Lotan
Companies invest in anomaly detection in order to proactively identify risks, such as revenue loss, customer churn and operational performance issues. Anomaly detection essentially enhances traditional BI and visualization tools, venturing beyond a summary view of your data. It constantly scans every metric, at a granular level, to find abnormalities. But in order for this technology to have an impact, you must be able to trust it.
Jun 27, 2019   |  By Anodot
Machine Learning (ML) algorithms are designed to automatically build mathematical models using sample data to make decisions. Rather than use specific instructions, they rely on patterns and inference instead. And the business applications abound. In recent years, companies such Google and Facebook have found ways to use ML to utilize the massive amounts of data they have for more profit.
May 24, 2019   |  By Anodot
This introduction to next-generation analytics includes a step-by-step comparison between legacy BI and Autonomous Analytics, from data integration to anomaly detection and forecasting.
Mar 1, 2019   |  By Anodot
Learn how different industries are using Machine Learning Powered Analytics.
Mar 1, 2019   |  By Anodot
Learn now anomaly detection can remedy urgent problems faster and capture opportunities sooner.
Feb 1, 2019   |  By Anodot
Immediately address data quality problems and save weeks of dealing with inaccurately reported data.
Feb 1, 2019   |  By Anodot
Learn how leading adtechs like Rubicon Project, Uprise, and NetSeer are leveraging the power of machine learning - discovering outliers in time series data and turning them into valuable business insights.
Jun 10, 2019   |  By Anodot
Anodot is a proactive way to run your IT Operations, used by the world’s leading data-driven companies. Our Autonomous Analytics platform uses AI to continuously scan all ETL metadata to monitor changes in behavior. Billions of events are filtered into just the alerts you need.
May 29, 2019   |  By Anodot
Personalization is key to eCommerce today. But with all the app permutations, how do you maintain great service for every customer? For every experience? Anodot is a proactive way to run your eCommerce business, used by the world’s leading data-driven companies. See how our patented AI/ML analytics platform gives you just the alerts you need, cutting time to detection and time to resolution, and saving you from costly incidents.
May 29, 2019   |  By Anodot
Anodot is a proactive way to run your IT Operations. Used by the world’s leading data-driven companies. How? Using AI. Our Autonomous Analytics platform continuously scans all ETL metadata to monitor changes in behavior. Billions of events are filtered into just the alerts you need.
May 20, 2019   |  By Anodot
Arun Kejariwal and Ira Cohen, both thought leaders in the deep learning space, share a novel two-step approach for building more reliable prediction models by integrating anomalies in them. They then walk you through marrying correlation analysis with anomaly detection, discuss how the topics are intertwined, and detail the challenges you may encounter based on production data. Present at the 2019 O'Reilly Artificial Intelligence Conference.
May 6, 2019   |  By Anodot
Anodot VP Product and Marketing Amit Levi discusses the next wave of data analytics and how AI/ML is allowing companies to scale their event monitoring and anomaly detection.