This Product Power Hour gave the community a practical look at how Internet Performance Monitoring, or IPM, is evolving . The session focused on how teams can improve visibility across the full internet stack, from network paths and employee endpoints to customer-facing digital experiences. The call centered on three core IPM lenses: network experience, workforce experience, and customer experience . Attendees saw how synthetic monitoring, real user monitoring, endpoint monitoring, Internet Sonar, Envision, and Edwin AI can work together to help teams answer critical operational questions faster, such as whether an issue is caused by the application, the network, a SaaS provider, a user device, or a broader internet disruption. Key Highlights ⭐IPM brings together synthetic monitoring, real user monitoring, and Internet Sonar to provide visibility across websites, APIs, applications, endpoints, SaaS services, cloud providers, CDNs, and network paths. ⭐In-session traceroute helps improve network troubleshooting by establishing a TCP connection before sending probes, which can result in cleaner, more complete path visibility compared to traditional traceroute approaches. ⭐Node-to-node monitoring enables teams to test connectivity across enterprise, cloud, backbone, last mile, and wireless nodes , with visibility into latency, jitter, packet loss, and path health. ⭐Workforce Experience Monitoring now includes test-level proxy configuration , allowing teams to define proxy behavior per test instead of managing proxy settings only at the individual enterprise agent level. ⭐Endpoint call quality monitoring gives IT teams visibility into Zoom and Microsoft Teams experiences , including application score, jitter, packet loss, packet drop, CPU usage, memory utilization, and geographic trends. ⭐Catchpoint data can be pushed into Envision and correlated in Edwin AI , helping teams connect external experience signals with infrastructure telemetry, identify root cause, and surface suggested remediation steps. Q&A Q: Are shared SmartBoard links dynamic and updated in real time? A: Shared SmartBoard links capture the selected timeframe, so they are static snapshots of the data from that investigation window. However, the shared view is still interactive, meaning users can click through records and explore the captured data. For a live, dynamic view, teams can put these matrixes into a custom dashboard and share that instead. Q: Why do I only see instant tests under Endpoint and not the endpoint features shown in the demo? A: Endpoint is a separate product and requires its own license. If Endpoint is not enabled in your portal, you may only see limited options, such as instant tests. Teams interested in trying Endpoint should reach out to their account executive to discuss access or a POV. Q: Can I add an endpoint to monitor an enterprise Zoom experience throughout the day? A: Yes. With Endpoint enabled, teams can monitor how an endpoint behaves throughout the day, including CPU and memory utilization, what the user accessed, and the quality of their experience while using applications like Zoom. Q: Is Internet Sonar required to drill down on endpoint data? A: No. Endpoint and Internet Sonar are separate products that provide different types of visibility. Endpoint requires an agent to be installed on workforce devices, whereas Internet Sonar provides visibility into broader SaaS and internet service issues without requiring installation. Used together, they can help determine whether an issue is isolated to a user or the workforce, or affects a larger region or service. Q: If call quality issues appear in one location, should I check Internet Sonar to see whether the issue is broader? A: Yes. If call quality issues occur in a specific area, Internet Sonar can help determine whether the issue affects other companies, regions, or services, or is isolated to your own users. Q: What is the best way to monitor end-user experience for custom integrations and microservices? A: A combination of test types is usually needed. For microservices, API monitoring is often the starting point, along with supporting checks such as DNS and network reachability. To get an aggregate view, teams can use custom dashboards and widgets that combine synthetic, endpoint, RUM, and Internet Sonar data. These views can also be pushed into Envision to compare experience data alongside infrastructure data. Q: Are Catchpoint synthetics similar to Selenium synthetics? A: Catchpoint synthetics go beyond traditional Selenium-style transaction testing. The platform breaks monitoring into different protocols and test types, including HTTP checks, full browser tests using Playwright, scripted user flows with Playwright and Puppeteer, API microservice tests, DNS checks, ping, and traceroute. This allows teams to monitor the individual protocols and services that power a user experience. Q: Can the same synthetic tests run from POPs and endpoint agents? A: The full set of synthetic monitors can run from public agents and enterprise agents. Endpoint agents are lighter weight, so they support simpler scheduled tests such as HTTP checks, traceroutes, and pings. They do not run full browser tests because endpoint devices are already running user workloads. Q: When should I use in-session traceroute? A: In-session traceroute is useful when traditional traceroute results show incomplete paths, repeated hops, or packet loss that makes troubleshooting difficult. It helps measure a cleaner path by establishing the connection before probing. Q: Can in-session traceroute be used with enterprise nodes, or is it only for backbone nodes? A: In-session traceroute can be used with any node type, including enterprise nodes and backbone nodes. Q: How do I enable in-session traceroute? A: It is a simple change in the traceroute sub-monitor type. Select in session as the sub-monitor type. Teams can also copy an existing test, run the traditional and in-session versions side by side for a few hours, compare the results, and decide whether to update more tests. Customer Call-outs 🌟“Thank you so much - It's really helpful.” 🌟“Yeah, that's very cool. That's the first time I've seen that [Catchpoint events] done live in there with those, popping that in and using Edwin to pull all that out.” What’s Next 🚀 1H Announcement Webinar Join us for the 1H Announcement webinar, which will serve as the official public presentation of the release themes and product updates previewed during this meeting. This will be the broader launch moment for the autonomous IT story, upcoming innovations, and related release details. May 12 at 12 PM CT 👉 Register here ⚡ Product Power Hour Join the next Product Power Hour sessions to continue exploring product updates, live demos, and practical use cases across the platform. These sessions are built for technical practitioners who want to see what is new, understand how features work in context, and ask questions directly to the teams behind the product. Optimize Cloud Spend with Confidence 📅 May 19 🕙10am CT Automated Remediation for Faster Issue Resolution 📅 June 17 🕛12pm CT 🍽️ User Group Dinner LogicMonitor is continuing to bring customers together through in-person user group dinners and regional sessions. These events are a great way to connect with peers, share monitoring strategies, and discuss real-world operational challenges with other practitioners. Join us in Chicago on May 27th Elevate Community Conference LogicMonitor’s annual conference is coming up in October and will bring the broader community together for product updates, technical enablement, customer stories, and peer networking. This is the best opportunity to go deeper on the platform roadmap and learn how other teams are scaling observability across their organizations. Registration opens mid-May Resources and Review 🏅Want to upskill? Earn your Catchpoint badge! 💻 Review the slide deck here 📹Watch the recording here or directly on the event page
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As LogicMonitor continues to evolve the dashboard experience, UIv3 Dashboards have now been deprecated in favor of the new dashboard experience. Dashboards are a critical part of how teams monitor performance, troubleshoot issues, and share insights across the business. Any change to that experience matters. The good news is that transitioning to the new dashboard experience is more straightforward than many users expect. Existing dashboards remain available, core functionality is still there, and the updated experience introduces meaningful improvements that make dashboards easier to use, manage, and share. To help users get up to speed quickly, we’ve put together a short set of videos that walk through the most important updates and show how to make the most of the new dashboard experience. What To Expect From The New Dashboard Experience The transition to the new UI is designed to be as seamless as possible. For most users, the biggest changes are not about rebuilding dashboards from scratch, but about learning a more modern, streamlined way to work. Here are a few practical tips to make the transition easier: Get Familiar With The Updated Layout The overall dashboard structure will still feel familiar, but navigation and actions are now more efficiently organized. Common controls like time range selection, adding widgets, and dashboard actions are easier to access, helping teams move faster in daily workflows. Watch: Navigation and Interface Updates Use Filters To Reduce Dashboard Sprawl One of the biggest improvements in the new dashboard experience is filtering. Instead of maintaining multiple versions of similar dashboards, users can quickly filter by customer, environment, or other criteria, and the full dashboard updates instantly. Saved views make repeat workflows even faster and more consistent across teams. Watch: Dashboard Filters: Improvements and Saved Views Share The Exact View You Want Others To See Collaboration is easier in the new experience. Shared dashboard links can preserve time ranges and applied filters, making it much easier to align teammates, stakeholders, or customers around the same set of data, without extra explanation. Watch: Sharing Dashboards and Enhanced Collaboration Take Advantage Of More Flexible, Query-Driven Analysis The Advanced Metrics widget brings a powerful new way to build dashboards. By using LMQL to define and reuse queries, teams can create more flexible visualizations for troubleshooting, reporting, and customer-specific views, all from the same underlying logic. Watch: Advanced Metrics Widget and Query-Driven Visualization Keep Using The Widgets You Already Know For teams already using Custom Graph, Big Number, and Pie Chart widgets, the good news is that those familiar capabilities remain in place. The main change is a cleaner, more structured configuration experience that makes widget setup and editing easier. Watch: Classic Widgets: Custom Graph, Big Number, and Pie Chart Why This Transition Matters The new dashboard experience is not just a visual refresh. It creates a stronger foundation for faster workflows today and more innovation going forward. With improved filtering, easier sharing, more flexible visualization options, and a more intuitive configuration experience, teams can get more value from dashboards with less effort. The move away from UIv3 Dashboards is an opportunity to simplify dashboard management, improve collaboration, and leverage a more modern experience built for how teams work today. With the right features already in place and guided walkthroughs available for the most important changes, getting comfortable with the new dashboard experience can be quick, practical, and immediately valuable.
Overview Good alert management is not about generating more notifications. It is about generating the right signals at the right severity and getting them to the correct team so they can act quickly and resolve the issue. A strong foundation starts with threshold-level setting, tuning, routing, and clear day-to-day alert operations. Key Principles Treat default thresholds as a starting point, not a finished configuration Tune before you route Every alert should be meaningful and actionable Route by ownership, not just by severity Use alert data and reports to drive decisions, not assumptions Alert Management Features and Methods Threshold foundations LogicMonitor’s metric alerting model is built around datapoints and thresholds, with static thresholds providing the default baseline for most out-of-the-box monitoring. That baseline is useful because it provides teams with immediate coverage, but it sometimes needs to be tuned to the behavior of a specific environment and device type. Thresholds can be adjusted at multiple levels in the hierarchy, including the global DataSource level, the resource group level, and all the way to the individual instance level. In practice, that means teams should tune at the highest level that accurately reflects shared behavior, and reserve one-off overrides for true exceptions. Tuning workflow Internal training guidance is consistent on one point: tune first, then route. The alerting curriculum frames tuning as an iterative process supported by alert reports, dashboards, threshold review, and investigation of noisy or redundant conditions. On the support side, report types such as Alerts, Alert Trends, and Alert Thresholds help teams identify high-volume alert conditions, review instance alert behavior levels and trends over time, and see where defaults have been overridden. That combination is what makes tuning practical instead of reactive. Routing fundamentals Alert rules determine which alerts are routed and how. LogicMonitor evaluates rules in order of priority, starting with the lowest number, and stops at the first match. That is why specific rules should take precedence over broader catch-all rules. Alerts that do not match a rule still appear in the portal, even if they are not routed externally. Escalation chains define who receives the alert and how it is delivered. They support staged delivery, multiple recipients, time-aware routing, and rate limiting, which makes them the core building block for sending alerts to the right team without creating unnecessary noise. Escalation chains can be sent to individual users, groups, or an external ticketing system. Day-to-day operations The Alerts page is the main page where practitioners can filter alerts of all levels, sort, investigate, and act on active or historical alerts. It supports saved views, custom table settings, and detail panels. Users can acknowledge and escalate alerts, add notes, and place an alerted device or group in SDT (Scheduled Down Time), making it the operational center for daily triage. Best Practices Set Up Alerts with Intent Start with datapoints that represent real operational risk. Use default thresholds for fast initial coverage. Validate whether default thresholds reflect normal behavior in your environment before broadly routing alerts. Focus first on alert conditions that are meaningful and actionable. Tune at the Right Level Apply group-level tuning when multiple resources share similar behavior. Use instance-level tuning only when a specific disk, interface, or service truly behaves differently from its peers. Avoid unnecessary one-off overrides that make alerting harder to manage over time. Review overrides regularly so tuning debt does not accumulate unnoticed. Route with Clarity Build specific alert rules above broader or catch-all rules. Align escalation chains to real operational ownership. Make sure alerts reach the team that can actually take action. Avoid routing everything to everyone just because it is easy to configure. Improve the Responder Experience Write alert messages that quickly communicate what happened. Include enough context for responders to understand what to check next. Use token-based message customization to make alerts more actionable. Treat alert message quality as part of alert quality, not as optional polish. Implementation Checklist ✅ Review which default thresholds are producing the most noise ✅ Run alert reports before changing routing behavior ✅ Tune thresholds at the correct hierarchy level ✅ Build specific alert rules before catch-all rules ✅ Validate escalation chains, stages, and intervals ✅ Save filtered views for common triage workflows ✅ Review custom threshold overrides on a regular cadence Conclusion Strong alert management starts with signal quality. When teams tune alerts based on evidence, route alerts by ownership, and use the Alerts page as an operational workflow rather than a passive feed, they build trust in the system and improve response quality over time. Additional Resources Static Thresholds for Datapoints Different Levels for Enabling Alert Thresholds Choosing a Report Type Alert Trends Report Alerts Thresholds Report Managing Alerts from the Alerts Page Alert Rules Escalation Chains Datapoint Overview
Welcome to the April edition of What’s Happening at LM! Each month, we bring you the latest on events, programs, and opportunities to get more involved in the LogicMonitor Community. Whether you’re looking to sharpen your skills, connect with other users, or stay current on product updates, this monthly roundup is your go-to source for staying plugged in. Let’s take a look at what’s ahead this month. Ways to Engage ⚡️ Product Power Hour: Smarter Alerting That Drives Faster Action Join us to explore how to increase signal fidelity, ensure alerts reach the right teams, and accelerate response with a scalable approach to alerting and topology-aware operations. Thursday, April 23 at 1 PM CT ➡️ Register here ⚡️ Product Power Hour: Detect Digital Experience Issues Earlier with Catchpoint See how Catchpoint helps teams detect digital experience issues earlier and gain clearer visibility across web, network, and end-user performance so they can troubleshoot faster and respond before issues become business-impacting incidents. Tuesday, May 5 at 11 AM CT ➡️ Register here 🚀 1H Announcement Webinar: Autonomous IT is Here: What’s New Across the LogicMonitor Platform Join us on for a live look at the latest innovations across the LogicMonitor platform. The webinar will cover how AI-driven automation, contextual intelligence, and end-to-end visibility are coming together to support the journey to Autonomous IT. 📅May 12 at 12 PM CT ➡️ Register here 🍽️ User Group Dinners Connect directly with LM users and LogicMonitor leaders in a casual, small-group setting. Share ideas, hear real-world stories, and grow your network with fellow practitioners. San Francisco/Bay Area: April 28 Chicago: May 27 Build Your Skills Accelerate Edwin AI Teams with Enablement LM Academy’s Edwin AI Training Program is designed to help teams drive successful implementations, speed time to value, and increase adoption through greater confidence and better outcomes. Earn the Edwin AI Badge Start with foundational knowledge and core capabilities through the Edwin AI Badge. This on-demand learning path is a strong first step for new users who want to build confidence with Edwin AI. For all new users 2 hours on-demand Begin with the badge ➡️ Start here Edwin AI Administrator Live Class Designed for admins, key stakeholders, and power users, this one-day instructor-led class helps teams prepare for deployment, optimize implementation, and drive business workflows. 1-day live instructor-led training Hands-on labs in Edwin AI sandbox beginning in Q2 Pre-deployment On-site or virtual delivery $6,000 for up to 12 participants Edwin AI End-User Live Class Built for end users such as Tier 1 engineers, this live session advances users from navigation to confident, effective usage. 3-hour live instructor-led training Hands-on exercises Post-deployment Virtual delivery Included at no cost with the Edwin AI Administrator training package For more information about Edwin AI training packages, please reach out to your account manager. Product Updates April Releases: v237 Highlights - coming soon Enhanced dashboard widgets and reporting Improved query and log usability with bulk actions and property sorting Introduced Cloud Budgets and alerting for cost control Improved platform scalability and tenant-level limits Delivered compliance and data retention enhancements For the latest details, be sure to check the release notes and documentation updates in Community and Support. Platform Lifecycle & Security Updates Apache Groovy 2 to 4 Migration: Key Milestone Update An upcoming patch release will remove support for Apache Groovy 2 on the GD Collector. Targeted for April 13, 2026 End of Sale for On-Demand Legacy Websites Effective April 30, 2026 , non-SKU subscribers using Legacy Websites on an on-demand basis will no longer be able to purchase or use the product. This change does not affect currently subscribed customers. As part of this transition, LogicMonitor is guiding customers toward LM Uptime , our next-generation website and service monitoring solution. End-of-Life for API v1 and v2 for New Customers Only Starting April 30, 2026 , new portals created after the EOL date will support API v3 only . UIv3 Dashboards Deprecation Beginning April 30, 2026 , UIv3 Dashboards will be retired. Customers will continue using UIv4 Dashboards. Deprecation for Legacy Versions 5, 6, 7, and 8 for LM Container and Argus Access to versions 5 through 8 will be removed on July 31, 2026 . Thanks for tuning in to this month’s update! We’re excited about all the ways you can connect, learn, and grow with us, both online and in person. Keep an eye on the Community for more announcements, and look out for next month’s edition of What’s Happening at LM as we continue to share new opportunities and highlight what’s coming next.
Overview LogicMonitor’s March 31 Product Power Hour highlighted how AI-driven investigations are becoming more precise, explainable, and operationally useful for technical teams working through incidents at speed. The session focused on recent enhancements to Edwin AI, including problem management, topology-based correlation, deeper log-driven root cause analysis, and change-aware investigations that help teams move from alert to action faster. A major theme throughout the conversation was trust. Attendees wanted to understand not just what Edwin recommends, but why it made that recommendation , what evidence it used, and how that information can be pushed into the tools their teams already rely on. The product team addressed that head-on by showing how Edwin surfaces logs, change requests, topology context, and knowledge sources directly inside the investigation experience. Key Highlights 🌟 Edwin AI now provides richer AI investigations with natural language summaries, root cause analysis, and actionable remediation guidance based on alert, log, and change data. 🌟 A new problem management experience helps teams identify recurring issues across the last 90 days so they can focus on deeper root cause resolution instead of repeatedly treating symptoms. 🌟 Topology-based correlation is helping Edwin group alerts more intelligently by understanding device relationships and dependency patterns. 🌟 The team shared that ServiceNow change integration is available today , with Jira planned next. 🌟 Customers showed strong interest in extending Edwin with additional data sources, especially Catchpoint, SOP and knowledge content, and metrics-driven reporting . 🌟 The discussion reinforced that users want Edwin to support both workflows: deep investigation in the Edwin UI and pushing relevant context into ITSM systems. Q&A Q: Is build of the topo maps dependent on monitoring protocols used? For example, SSH versus SNMP to monitor network devices? A: Yes. How we pull information from LogicMonitor depends on their dedicated topology sources, which use a mix of four or five different protocols to build the maps. It depends on the type of devices you are monitoring in LogicMonitor, and that dictates how the maps are built. We also are not limited to only network and network maps in the Element Vision side. If you have VMs, you will still get a map or connections that we can pull through to Edwin soon as well. Q: Can you use topology maps from other products such as NetBrain? A: Not right now. We are currently experimenting with Dynatrace, which has an MCP available that lets us fetch topology information. In theory, if NetBrain or another third party has an equivalent way for us to fetch topology information, then yes, we would be able to layer that into what we have. The key requirement is access to topology information in a format where we can determine how systems are connected. Q: What sources can you tap into for SOP-type material? A: Right now we are connected to ServiceNow, so you can set up the LMDX integration to allow us to read those articles. Next on the list are Confluence articles and SharePoint via MCP. If there is another data source you are interested in, please share it, because we are able to start adding those integrations. We can also do a public knowledge search, so if you want to tap into vendor documentation or other publicly available web content, you can query that from the agent too. Q: Is the change integration available today? A: Yes, it is with ServiceNow. If ServiceNow is your ITSM, that is available today. We are working on Jira next for changes. Q: It seems like there used to be an available Edwin AI Python SDK integration under Settings. I do not see it now. Am I misremembering it being available? A: It is available. We might just have to pass you the files for the SDK, because I do not think it is available to download anywhere. It should include how you send through events if you want to set up a custom integration. The other option is to use the webhook if you want to send events or information into Edwin, and it sends to that same endpoint as long as you include the required fields. Q: Is there an article for the webhook approach too? A: Yes. We do have documentation, although it probably needs to be updated because it does not clearly list the endpoint, which is likely the most helpful part. Right now it mostly covers the required fields, but we can make sure it gets updated so the endpoint is more obvious. Q: Could you tell us what’s behind the AI at LogicMonitor? What technologies, approaches, or architecture are used to build and operate this solution? A: It varies depending on the use case. Forecasting, for example, is best handled with a regression algorithm based on historical data. Edwin AI leverages both ML models and agentic frameworks to correlate alerts and fetch information from third-party sources. We try to match the type of AI we use to the particular use case we are solving for. Q: Why was the AI in LogicMonitor named Edwin? Is there a specific meaning or story behind that name? A: It was named after Edwin Hubble. The idea is that the Hubble telescope helped discover and reveal more of what is out there in space, and Edwin AI is meant to do something similar for your observability systems by combining information and giving you insights into your data. Customer Call-outs ⭐“Pushing the data into ITSM is necessary for sure. The additional functionality added to Edwin makes it compelling for SA's to use the Edwin UI.” What's Next ⚡Product Power Hour Smarter Alerting that Drives Faster Action April 23rd | 1pm CT The next Product Power Hour will focus on alerts, including alert tuning, management, routing, and upcoming alert-related features. This session is a strong follow-up for teams looking to improve signal quality and operational response workflows. 👉 Register here today 🪵Logs for Lunch More Value and Less Worry with Log Partitions April 8 | 12pm CT The next Logs for Lunch session will cover log partitions and will take place at 12:00 p.m. Central Time. This is a useful session for practitioners looking to deepen their log management strategy. 👉 Register here today 🍽️ User Group Dinners Join us as we head back on the road! Connect in person with other LM users in your city over dinner and real talk. Share wins, swap stories, and grow your network. San Francisco/Bay Area - April 28 Chicago - May 27 Resources and Review 🏅Want to upskill? Earn your Edwin AI badge ! 💻 Review the slide deck here 📹Watch the recording here or directly on the event page .