As part of our work to surface logs as additional context in LogicMonitor, we developed an initial integration to bring Unomaly logs into the LogicMonitor platform. This integration uses LogicMonitor EventSources and DataSources to display the log anomalies and known events collected by Unomaly and Monitor the frequency of these events over time.
Happy New Year! We’re starting 2020 with some exciting news. We are pleased to announce that as of today, Unomaly has become part of LogicMonitor, the leading global provider of infrastructure monitoring and intelligence across both on-premises and cloud.
Software used to be simple enough so that one could monitor its state in order to know if something was wrong and to immediately know why it was broken. One could create a set of alerts based on some known errors or known metrics and immediately react appropriately when one of those alerts were triggered. But in today’s systems, there are hundreds or thousands of potential causes. They are unknown. No amount of dashboards nor alerts can solve this fundamental problem. We need to change our approach and have the ability to ask any questions to our systems to observe them while they’re running.
We’ve tripled our key feature set to give you exponentially greater context when investigating incidents using your log data and understanding your software’s running state to discover unknown aspects of your infrastructure.
For the past few months, we have quietly tested a new way to run Unomaly on any platform that supports DockerCE with a few of our customers. Now we are opening our alpha program, codenamed Amelia, to anyone who is interested, whether you are a Unomaly veteran or trying us for the first time.
Google Cloud Platform offers a basic set of monitoring capabilities baked into the platform. Virtually anything that runs on top of GCP will get basic monitoring through health checks, basic alerting and basic log management.
Over the past several weeks, we’ve been working on Unomaly 3.4. In this series of releases, we’ve dedicated our efforts to creating the tools to help you understand your complex environments, slice and dice your data and provide clues for where to look when things go wrong.
By using the filter bar, it is easy to find value when you know exactly what you are looking for and drill down to learn more. However, what about cases when the user does not know what they are looking for? How can they find the signal when there is clutter hiding it?
Logs are generated everywhere, ranging from the printer in the corner of your office to your new application architecture running docker containers on top of Kubernetes — Regardless, to analyze any of those logs, you need to send these logs over your network to Unomaly.
Workflows answer the simple question, “what are my systems doing?” by providing you with a simple way to gain a deeper understanding of your infrastructure.