Predict and Solve IT Incidents with AIOps
4.8/5 (6 reviews)Pros
Our logs are home-grown and Loom is the only product we found that is capable of analyzing them in their original format. Any other product in the market would require us to rewrite them first.
Cons
My team had been working with manual tools for 10+ years and it took us some time to get used to having and counting on an automatic system
We use Loom to monitor our OpenStack environment. first, we were skeptical of using the logs to detect issues, and not only for debugging, but, our experience with Loom was just excellent. it manages to analyze logs and metrics in real-time, correlate events across different services, and perform root cause analysis easily, a very short time after implementation.
I started using Loom recently over splunk, essentially as an AI layer above the data to help my team perform the actual analysis. so far, it seems very promising and it helped us solve problems short time after occuring and not only after a user opens a ticket.
Pros
Automatic
Log Correlation
Recommends resolutions
we used loom for log management in order to become more proactive and reduce the number of problems that were customer-reported in the organization. our 'proactiveness' keeps improving from month to month so far.
Pros
-advanced correlation between apps
-suggests next actions for issues
We use Loom on our middle-ware, to let it correlate multi-layer events in cross-environment/application context. Loom helps us gain visibility into our Middle-ware traffic.
good ROI tool. loom helps my team solve problems faster then ever and was a great platform for my team to share knowledge
I had dozens of logs which hadn't been analyzed at all. we picked loom to analyze this data automatically, with allocating as the least IT pros as possible. Loom proactively detects issues and then provides the user with the necessary inputs to solve the issue.