Overview
LogicMonitor Edwin AI
Edwin AI is an agentic AIOps product built to act, not just observe. It correlates alerts, identifies root causes, and recommends remediation. Edwin AI helps IT teams eliminate noise, resolve incidents faster, and scale workflows with confidence. Teams can move from daily firefighting to proactive operations, increasing productivity and scaling capabilities without increasing headcount. Built on Amazon Bedrock, Edwin AI leverages model flexibility, native agent capabilities, and AWS integration to autonomously triage, correlate, and remediate incidents at scale. Customers have seen immediate results like 80% noise reduction, 30% fewer ITSM incidents, 60% faster MTTR, and a 20% boost in operational efficiency. Designed for real-time operations, Edwin AI deploys quickly and delivers measurable impact in days, not months.
Highlights
- Agentic AIOps: Edwin AI is a native, purpose-built AIOps product, designed for IT operations teams. It brings contextual understanding of the ITOps environment and observability dataset to correlate events, identify root causes, and drive remediation.
- Unified Data Context: Edwin AI stitches together observability telemetry, CMDB data, topology, and ITSM context into a unified ITOps knowledge graph, enabling explainable, data-driven decisions across hybrid environments through over 3,000 integrations.
- Quick Time-to-Value: Edwin AI delivers immediate measurable improvements in alert noise, MTTR, and ITSM ticket volume.
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
Pricing
Dimension | Description | Cost/12 months | Overage cost |
|---|---|---|---|
LogicMonitor Edwin AI | Edwin AI with auto-billing of overages | $120,000.00 |
Vendor refund policy
Custom pricing options
How can we make this page better?
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
Customer reviews
LogicMonitor Topology Mapping: Real-Time Dependency Visibility for Complex Cloud Infrastructure
The majority of monitoring systems merely provide a list of green/red boxes. Boring! LogicMonitor's Topology Map is not only a visualization of the relationships between all the resources, but it is visualizing this relationship in real time. Yesterday I just sat for 3 hours looking at the maps that one generates by using our hybrid environment. It's great at capturing the dependencies – if one microservice in AWS is communicating with an on-prem database, it'll capture that dependency instantly. This is as if you had x-ray vision on your architecture! I've never seen any dependency chains so accurate, dependency-wise, on maps! It’s pure magic. I'm sending this information to all of the architects that I know—to say that if you don't have this on a map, you are flying blind!
Onboarding: No longer handing documents out when new engineers come on-board. I simply log them in to the LogicMonitor map. It's the truth and nothing more than the truth!
Total Clarity: I'm sleeping better at night because I can see everything that's going on my infrastructure. It isn't only monitoring, it's architectural enlightenment!
BUY IT NOW. DON'T WAIT.
Predictive Forecasting Controls Are a Math Nerd’s Dream
LogicMonitor has cut our MTTR 42% and provided tight ROI.
Ring logic is good. We used switches for dynamic thresholds for CPU and memory instead of static thresholds. This was the reason alert noise is going down by 62%. We were receiving 400 alerts a week from our on call team and now we are receiving 150 actionable alerts a week! Full support for integration with Terraform. Monitoring is "As Code". Very low API response time - always <50ms for metric queries.
Benefit can only be quantitative:
Now, with the visibility into the exact root cause node in dashboard, Mean Time to Resolve (MTTR) is improved to 26 minutes, down from 45 minutes (42% improvement).
The uptime of the infrastructure is improved from 99.91% to 99.99% for last two quarters.
Capacity planning report made it very easy to identify and downsize 40 idle VMs. This optimization is soaring the savings in cloud billing by a sum of exactly $3,200 a month.
Complete overall ROI is realized after just 8.5 months.
Hands-Free Multi-Cloud Monitoring with Easy Collector Setup and Fast Alerts
Dashboards are very interactive and easy to build. I built a lot of custom dashboards for app teams and database teams to view their own metrics. Also, alerting is very fast and reliable. When any one of my pods is crashing or when the CPU hits 90, I receive Slack and PagerDuty messages immediately. Easy to set, but once it is in place it will be totally hands-free.
Another thing is writing custom datasources. If default monitoring is not there, we need to write scripts in Groovy for custom datapoints. For beginners, learning Groovy for monitoring is very difficult and slow. Further, if you place too many graph widgets in a single dashboard, UI will be slow loading sometimes.
Helping me find the root cause of an issue very quickly. Application speed is slow—server metrics, network traffic and database load all can be viewed in one place, simultaneously. It saves our lot of time and MTTR (Mean Time to Resolve) is reduced nicely. Obtaining bugs before it's being reported to us.