Anodot is the only monitoring solution built from the ground up to find and fix key business incidents, as they’re happening. As opposed to most monitoring solutions, which focus on machine and system data to track performance, Anodot also monitors the more volatile and less predictable business metrics that directly impact your company’s bottom line. Now there’s an easy way to measure the business impact of every incident.
Anodot CEO and Co-Founder David Drai joined Amazon Web Services and Xandr to discuss the shift to machine learning-based anomaly detection in business monitoring. Xandr Chief Technology Officer Ben John shared how their advertising marketplace is using Anodot platform to cut detection from “up to a week to less than a day”. You can watch the webinar at the link above or read on for the highlights of that talk.
Every decision that an engineer makes in the cloud impacts cost. Yet we know that engineers aren’t cost experts, and many worry that asking them to care about cloud cost will slow them down and distract them from delivering customer value. Top cloud-native companies dedicate entire teams of engineers to build custom tools to measure unit cost and deliver cloud cost to engineering teams. But I’m guessing you don’t have eight engineers you can spare to build internal cost tools?
Evaluating a new, unknown technology is a complicated task. Although you can articulate the goals you’re trying to achieve, you’re probably faced with multiple solutions that approach the problem in different ways and highlight varying features. To cut through the clutter, you need to figure out what questions to ask in order to evaluate which technology has the optimal capabilities to get the job done in your unique setting.
Over the last decade, data collection has become a commodity. Consequently, there has been a tremendous deluge of data in every area of industry. This trend is captured by recent research, which points to growing volume of raw data and growth of market segments fueled by that data growth.
You may be using your log data in a completely wrong way. Today, your business produces more data than ever before, and log data is at the center of all this because it contains the signals of what caused a problem. If your teams have to search for these signals in an ad-hoc manner, then they are wasting their precious time. Nearly every company in existence is dealing with this challenge because it may not have the tools to filter these signals from the noise.
Being able to easily monitor the health of all your sites and services from multiple global locations is a powerful tool for site reliability. However, no one wants to sit and stare at a status dashboard all day. Naturally, teams want to be alerted when there is an issue. We can do that with alerting in Kibana. And when coupled with Elastic machine learning, alerts can be automatically generated from anomalies that are automatically detected. That’s the power of Elastic Observability.
