Moogsoft Reviews

I was contacted by someone regarding PeerSpot because she learned I was working with the Moogsoft tool.

I have been working with the Moogsoft tool for the last 3 years, and we handle the monitoring aspects with it.

I am currently working with Moogsoft, which is a monitoring tool, and we monitor different alerts, including DevOps alerts, Cisco alerts, DPA Dynatrace alerts, and Iceland alerts. We also create separation for servers and CM and IDs.

I also work on ServiceNow for incident management, receiving alerts from networking devices, and we monitor incident numbers before routing tickets to the appropriate tech teams.

I find Moogsoft beneficial for separating tasks, so during activities, users will not receive any alerts, allowing them to work silently without distraction.

Moogsoft helps manage alert fatigue by consolidating various alerts into a single portal instead of monitoring them across different devices, allowing team members to own alerts and monitor them efficiently, which benefits the whole team.

Moogsoft offers various benefits, including incident response, reduced noise alert fatigue, increased availability and uptime, helping companies gain a better understanding of their IT environment, proactively addressing issues, and improving services.

We have deployed the tool. It’s an event correlation tool. Unlike tools like Splunk, which have their agents running on servers to send telemetry data and logs, Moogsoft operates differently. It collects data published from various telemetry tools and then handles the correlation. For example, if a web server goes down, Moogsoft will generate an alert indicating that the server is down. However, this alert alone may not provide meaningful insights. If the web server is down, there might be other related issues, such as database connection problems or API failures. This can overwhelm users with numerous alerts.

Moogsoft addresses this by filtering the noise and consolidating alerts into a single situation report. This way, users won’t be bombarded with alerts. Instead, they’ll receive a clear overview of the problem, identifying where it lies and what components are affected. This allows the Site Reliability Engineer to understand the situation better. Once a situation is identified, you can define workflows. A workflow might involve an automated repair plan that outlines specific actions if certain conditions are met. If action A is performed, then feedback will dictate the next steps. We have deployed Moogsoft for an automobile client and a bank in Singapore.

We have observed improvements since integrating Moogsoft into our system. Initially, we had various monitoring tools, including Datadog, OpenSearch, CloudWatch alerts, and Prometheus. Each team was working in silos, using different tools without a cohesive view from a business perspective. Once we integrated these tools and allowed data to flow into Moogsoft, we could establish workflows correlating events, clarifying our monitoring efforts.

Moogsoft excels as an event correlation tool but requires substantial data to provide effective insights. On the first day, it may not offer comprehensive visibility. Dynatrace provides immediate insights upon deployment, making it superior in terms of initial usability. While it captures essential data, it may lack deeper visibility into interactions between servers, only showing which IPs data is sent to.

Moogsoft becomes much more functional as more data is onboarded. Its machine-learning capabilities take about one to two weeks to identify similar past situations. 

We were looking to replace the product we have, which was Moogsoft. However, the project got canceled, so we are not looking anymore. While we are looking for another solution, as of right now, management decided to keep it. So maybe in the next financial year, it will be a topic again. Still, we are not pursuing it anymore.

The operations are familiar with how to use Moogsoft, so they are keeping it. We want to increase the incident response, reduce the number of tickets, and integrate Moogsoft with ServiceNow.

We are a service provider. We have the product under an MSP license. We offer this solution to our customers internally within the group and company. We are also using it for our few business units.

The solution's core functionality is noise filtration, which is pretty robust. We've implemented this to interconnect multiple tools. It acts as alert consolidation for multiple internal products. It is a centralized plug-and-play solution.

I find the unsupervised learning algorithms for noise reduction particularly valuable. The algorithm's ability to identify and reduce noise is a feature we initially liked. The anomaly detection feature is excellent for maintaining system uptime as it helps identify problems quickly.       

People use Moogsoft to filter out alerts in their NOC and IT service management.

The solution has an AI engine that reduces false positives and gives some context to some tickets. The tool's event correlation and AI are its strongest parts. They have a thing called the Situation Room that also helps put all different events related to one situation into one place. Instead of having several different events looked at by several different people, you put all correlated events into one big problem, which will then be dealt with as a single thing.

Incident management is streamlined with Moogsoft. One standout feature is its unique situation-creation capability, differentiating it from other fault management tools. While other tools typically convert alarms directly into tickets or incidents, Moogsoft adds a middle layer where multiple alarms can be aggregated into one incident. Moogsoft's strong AI capabilities also allow it to correlate similar alarms automatically based on past experiences.

The solution comes with a collaboration feature. This feature allows team members to communicate and work together on various issues. If there are ten incidents, then ten chats will be open.

The solution comes with features like PRC, designed to streamline alarm flow, reduce noise, and prevent alarm flooding. These features are particularly beneficial when used with a basic understanding of network operations. It has a time-based algorithm that continuously learns from alarm flows. When the alarm flow reaches a certain limit, it collects all alarms together based on historical data. This is particularly useful during major events such as power outages, where alarms could flood. In such cases, the product activates to hold all alarms for a certain period, anticipating a fluctuation rather than immediately triggering the alert manager.

The tool needs to improve its support. It appears that the support responsiveness from Moogsoft is not aligned with the severity of the incident. Instead of proactively addressing issues, customers have to chase Moogsoft for resolution. In Moogsoft, unlike other tools like Splunk, the process follows a step-by-step sequence. You need to start each process in a specific order, typically following a sequence. 

I'm using this tool as a MoM tool, manager of manager. We have integrated a lot of monitoring tools, enterprise monitoring, infrastructure monitoring, and database monitoring tools with Moogsoft to provide one unified console to the NOC guys so that they don't need to jump around on multiple tools to view the issues. Through Moogsoft, using a single layer and a single screen, they can see all the issues and they can act. 

Further, Moogsoft is integrated with the ticketing tool ServiceNow. We are converting those alarms into tickets for further actions on resolving the issue.

We are developers, integrators, and consultants. We do everything.

There are AI features in Moogsoft. Moogsoft has one wonderful feature that allows you to convert multiple alarms into situations. Generally, all other MoM tools get the alarms, and then convert it into an incident directly. There is one extra layer they have added before converting any alarm into an incident. Suppose there are multiple alarms that are somehow all related to a single source of issue. It converts all the alarms into a single situation, which then gets converted into an incident.

Suppose your database is down, and all the applications associated with the database are also down. Moogsoft has its own AI capability as well as some inputs from us as well. We can give the inputs, and once the database goes down, then whatever alerts will come from that source tool, monitoring tool to Moogsoft, it will automatically put all those alarms into a single situation and convert it into an incident. Eventually, it is reducing your ticket count and extra burden on the system. That is one of the best features.