Video: What is Moogsoft? ►

This video describes some of the benefits and key concepts of Moogsoft.

What Is Moogsoft?

Moogsoft is a solution that combines the best of observability and AIops correlation, and does above and beyond the traditional monitoring tool.

Noise reduction and correlation functionality let you focus on the most important issues.

The level of insights you gain with Moogsoft Express is rich with context, so you get the whole picture of the behavior of your systems.

It is a single pane of glass to view the cross-source information, so you don’t have to jump around multiple interfaces to synthesize the information. With a tool like this, not only the traditional IT operations staff but the SRE and DevOps engineers can benefit from its findings.Before diving into the product, let’s take a moment to visit these characteristics one by one to better understand them.

Noise reduction is a key functionality when you ingest a large amount of data from multiple sources.  Moogsoft identifies the duplicate events, aggregates them into a single alert, then correlates them into Incidents.  Having all relevant information in one place makes it easy to analyze and remediate.


Here’s one type of data flow.

The source monitoring system forwards the events it detected.

These source event data is then mapped to the Moogsoft event data fields.

Then Moogsoft uses some of the event fields as the deduplication keys, and if the values match, those events are bundled into an alert.

At this point, we can avoid different operators working on different occurrences of the same problem at the same time.


Then, Moogsoft’s correlation engine further groups those alerts by their related-ness into incidents.  By algorithmically identifying the relation between alerts, Moogsoft does the correlation work for you.   So by the time you access the incidents, all related data about the issue is already identified and grouped together.


Here’s an alternate flow of data.  Rather than integrating with your monitoring systems, you can install a collector to your data source, and have it perform the data collection.  The rest of the noise reduction process works much the same way,


Next, what do we mean by Rich context?

Moogsoft can ingest both raw metrics and the alerts from your monitoring systems.

Then the data is correlated to provide a comprehensive global view of what’s happening in your infrastructure and applications. Let’s use an example to illustrate the benefit.

Let’s say you got Nagios watching the CPU utilization of a server, and it’s creeping up steadily since last week.  Meanwhile, your APM system has detected that application A is getting slow.

Typically, when you troubleshoot a case like this you’d check multiple systems to gather diagnostic information.  You see an application is slowing down in one dashboard..  You may also learn from another source that the CPU usage is trending up.  Then you may learn from yet another source about a particular process that got inefficient since the last release.  After synthesizing the information you know why application A has gotten slow.

But wouldn’t it be nice if you don’t have to compare different types of data from multiple sources, and synthesize the information yourself? wouldn’t it be nice to be able to see all relevant information in one place rather than jumping around multiple systems yourself?That’s what Moogsoft does.


Intelligent metrics Analysis is another strength of Moogsoft.

We offer anomaly detection at the edge.

This is the traditional monitoring model.  The data from the sources are sent to the central data lake for your analysis.  This model requires a lot of bandwidth, and adds processing delays to churn through the data lake once all pieces of information are present.


Departing from that traditional model, Moogsoft’s data collectors have a built-in intelligence that performs the right at the source.  Not only this eliminates the financial burden of storage and computing cost, it also reduces the latencies involved in transferring raw data from sources to a central location.


How does the collector know what to report?  It has the ability to learn the norm on its own, and responds when the metrics deviate from it.


Take advantage of the trial instances and see the power of Moogsoft now! 

Thank you for watching!