Skylar One Juneau: More Speed. Better Maps. Smarter Topology. Happier Weekends.
When customers help guide the roadmap, the result looks a lot like Juneau (12.5.1). It’s practical, focused, and full of improvements you asked for. And while this version introduces new marquee features, Skylar One (SL1) customers are more likely to notice how it brings together hundreds of customer-driven engineering upgrades. The result is something admins, operators, and SREs will recognize instantly: a platform that runs faster, models the world more accurately, and fits easily into the rhythm of how you operate. With 700+ enhancements across ingestion, topology, eventing, collectors, HA, UX, and hardware support, Juneau is one of the most customer-driven releases we’ve delivered. These changes come straight from real deployments, break/fix pain points in the field, and hands-on sessions with SEs, Support, and Professional Services. And of course, huge thanks to the brilliant members of the Nexus User Community and all your contributions to the Nexus Idea Hub. Let’s dive into a few highlights from Juneau. A Platform That Feels Faster (Because It Is) Juneau’s performance improvements aren’t theoretical. The ingestion and data processing pipelines now move up to 60% more throughput, thanks to extensive tuning and backend re-architecture. In large environments, this directly translates into smoother dashboards, more up-to-date metrics, and fewer ingestion bottlenecks under unusually heavy load. Daily data maintenance was also rebuilt to use far less CPU and I/O, eliminating one of the most common sources of delay during maintenance windows. For large deployments, this means more predictable performance and smother scaling to peak load. In short: the system breathes easier. And as you already know, when goto ops tools run faster, the entire operational experience improves. Topology That Matches the Networks You Run Topology modeling has always been one of SL1’s superpowers and Juneau gives it a serious upgrade. LLDP and CDP relationship extraction got a ground-up refresh. One of the most impactful changes: LLDP now forms multiple valid relationships across interface pairs instead of aggregating them into one. Bonded links, trunk groups, and redundant uplinks now show up exactly as they exist in the environment. Similarly, topology can now form relationships even when only one side of the connection reports neighbors. For environments with asymmetric discovery policies, strict security controls, or devices that don’t speak every discovery protocol, this is a major practical improvement. You now get a more complete graph, even when the inputs are less than perfect. Add in new global controls for per-protocol behavior, and discovery becomes far more adaptable to the real world — not just an ideal one. Geographic Maps: A New Operational Lens Juneau introduces Geographic Maps as a new data & visualization type, and a new dimension to operational awareness. You can now visualize devices, services, and health states geographically across regions, campuses, data centers, cloud footprints, retail branches, or industrial sites. Here are just a few customer use cases: MSPs validating customer regions Retailers preventing brick-and-mortar outages Energy and utilities tracking state-level impact Distributed enterprises troubleshooting local vs. regional issues And many more… Skylar One Geographic Maps isn’t simply NOC bling — it’s a diagnostic tool. Geographic Maps surface real-world patterns that don’t always fit neatly into lists or dashboards. They make regional correlation simple. And even better, they turbocharge understanding for business services and synthetics. We can’t wait to see how you’ll take advantage of geo-aware data and visualization. And yes, automatically zooming, context-aware, full-screen Global Ops maps do make for sparkly NOC bling. Event Policy Editor: Redesigned by You Juneau includes a new Event Policy Editor that streamlines the configuration and optimization for event policies based on your feedback. The new UI is cleaner with an optimized layout and validates changes in real time. It’s easier to ensure accuracy, faster to build policies, and easy for new admins to learn. Business Service policy tuning also benefits from the same treatment, with clearer rule logic and intuitive metric selection. If you manage complex event pipelines or regularly onboard new operators, this is a quality-of-life upgrade you’ll notice immediately. AI Observability from Model to Metal (Now with AMD GPUs) Believe it or not, self-managed AI infrastructure isn’t niche anymore — it’s becoming core to how advanced operations teams ensure tight AI security and cut cloud opex. Juneau expands Skylar One’s existing NVIDIA GPU and LLM workload monitoring to include full AMD GPU visibility, completing true model-to-metal observability. You get insight into GPU temperature, utilization, memory pressure, power draw, error states, and other AMD-specific signals, all stitched into the same service context that already connects your models, inference endpoints, OS behavior, and chassis health. For teams managing AI platforms, this is welcome news. For example, you can now measure the relative efficiency of specific AI workloads across different combinations of datacenter components and recommend the most cost-effective mix to maximize LLM performance for your operations. If you’re running LLM inference nodes, GPU training clusters, HPC pipelines, or any data-intensive workloads, this enhancement further extends the ScienceLogic AI Platform’s comprehensive observability. Skylar One now interprets the entire AI stack as a single, coherent system — from model behavior to GPU thermals to the infrastructure beneath it. It’s the same level of intelligent, correlated insight you expect for CPUs, networks, containers, storage, cloud, and more, now fluent in even more of the most performance-sensitive workloads you operate. Synthetics Become a First-Class Citizen in Juneau For a long time, synthetic tests in Skylar One were powerful but lived a little off to the side. They were easy enough to integrate but not fully woven into workflow. With Juneau, synthetics become a first-class citizen in Skylar One. Recording a synthetic transaction now feels familiar to anyone who’s used a modern DEM tool: record an application workflow in a browser via Playwright Codegen, drop the generated Playwright script into a Skylar One dynamic app, assign a credential, and you’re ready to test from multiple locations. Just record, point, click, run. But the real shift happens after you deploy synthetic tests. Because they’re now fully integrated into Skylar One, real-world application performance shows up everywhere operators already live — dashboards, business services, context panels, service health, and even Geographic Maps. Multi-location failures become much easier to troubleshoot when you have quantifiable experience data from an end-user perspective. And yes: Skylar One still works seamlessly with your existing DEM, RUM, and APM investments. If you rely on browser-based monitoring from Dynatrace, New Relic, AppDynamics, or others, Skylar One can continuously ingest and contextualize those signals too. But with the Juneau release, external tools are no longer required. Synthetic visibility is built in and part of the core platform experience. For teams who depend on predictable user journeys, distributed site uptime, or multi-step workflows, synthetics in Juneau aren’t just easier to run. They’re now part of the operational heartbeat of Skylar One. High Availability, Low Maintenance Some improvements don’t need a spotlight — they just work the way you expect. Improvements to High Availability is a perfect example. If you’ve ever stared at any application during failover and quietly wondered, “Is it switching… or just thinking about it?”, you’ll appreciate Juneau’s enhancements to Skylar One’s High Availability. This release tightens the entire HA failover path. Link-state detection is faster and more accurate (especially in environments without crossover links). Heartbeat monitoring is more responsive. Cluster state transitions settle quickly. And the updated logic avoids unnecessary retries that slowed down election decisions in some configurations. The result is HA that kicks in quickly, transitions reliably, and behaves with the no-fuss confidence you expect from tier-1 enterprise platforms. Python 3 Everywhere: Faster, Safer, and Ready for What’s Next The Juneau release completes Skylar One’s transition to a pure Python 3 platform. Collectors, platform services, dynamic apps, extensions — everything now runs on a single, modern runtime with no legacy paths or dual execution. Python 3 is industry standard for good reasons. It’s faster, more secure, and far better supported by modern libraries and tooling. Moving to a single runtime improves workload performance, strengthens security posture across the platform, and simplifies everything from dynamic app development to upgrades and long-term maintenance. Deprecated Python 2 powerpacks are clearly indicated in the admin UI so teams can identify and update any remaining artifacts with ease. Skylar One Juneau — Ready for You, Ready for Anything Juneau brings meaningful improvements across the features of Skylar One that operators depend on most. Faster ingestion, sharper topology, integrated synthetics, Geographic Maps, streamlined HA, full-stack AI observability, and a fully modern Python foundation come together in a release that’s more capable, more responsive, and more aligned with how your team works. It was engineered with customer input at its core, RC tested in user environments, and ready to support the next wave of your AIOps workflows. Check out the Getting Started Guide for more details and documentation links. We can’t wait to get your feedback on the latest release from ScienceLogic.Looking Back – ScienceLogic’s Top Five Moments of 2024
As we close the chapter on 2024, we want to extend our heartfelt gratitude to you—our customers and partners—for inspiring and driving us forward. The holiday season offers a unique moment to celebrate shared achievements, reflect on milestones, and set the stage for an even brighter future. This year has been one of growth, innovation, and collaboration, and we are thrilled to share ScienceLogic’s Top Five Moments of 2024 with you. #1: Launching Nexus – Your Gateway to the Future of Collaboration. One of our proudest moments this year was the unveiling of Nexus, ScienceLogic’s cutting-edge customer community. Nexus isn’t just a platform; it’s a dynamic ecosystem where ideas flourish, connections strengthen, and innovation takes flight. With access to expert guidance, peer insights, and a wealth of resources, Nexus empowers you to thrive in the ever-changing IT landscape. This community is your space to lead, learn, and shape the future. If you haven’t already, we invite you to register to unlock the power of community and be part of this transformative journey. Register on Nexus Today #2: Celebrating Excellence – The 2024 Innovators Award Winners This year, we celebrated the visionaries driving groundbreaking AIOps transformations with our 2024 Innovators Awards. These trailblazers have leveraged the ScienceLogic AI Platform to create meaningful, lasting impacts in their organizations and industries. Their stories inspire us to continue delivering solutions that empower our customers to achieve their boldest goals. Meet the Innovators #3: SL1 Earns FedRAMP Certification – A Milestone in Public Sector Excellence A defining moment this year was achieving “In Process” status with FedRAMP for our Government Cloud platform, now listed in the FedRAMP Marketplace. Building on our decade-long DoDIN APL certification for on-premise solutions, this step underscores our commitment to delivering secure, unified IT management for the public sector. With dual certifications and an ongoing pursuit of FedRAMP Moderate authorization, ScienceLogic continues to set the standard for compliance, security, and innovation. Learn More #4: PowerHour – Delivering Expertise at Your Fingertips This year, PowerHour became the go-to resource for hands-on learning and actionable insights. Designed to help you unlock the full potential of our solutions, this program empowers you to stay ahead in a fast-paced industry. Whether live or on-demand, each session delivers practical strategies and expert guidance. As we gear up for 2025, we remain committed to creating even more opportunities to equip you for success. Access 2024 On-Demand Sessions #5: Redefining Innovation with Skylar AI This year marked the debut of Skylar AI, our latest platform enhancement designed to push the boundaries of Autonomic IT. With Skylar RCA and Analytics now generally available, the platform empowers teams to make data-driven decisions, automate complex workflows, and deliver measurable business outcomes. Looking ahead to 2025, we’re thrilled to bring Skylar Advisor to life—a groundbreaking addition that will revolutionize the IT landscape. Discover the Skylar Roadmap As we reflect on 2024, we’re reminded that every milestone is a shared victory. Your trust, partnership, and commitment inspire us to aim higher, innovate further, and deliver even greater value. Here’s to another year of bold advancements, stronger relationships, and unparalleled success. Stay tuned—2025 promises to be our most transformative year yet. Wishing you a joyful holiday season and a prosperous New Year!Remediation with Restorepoint (Part I)
The Basics It’s important to understand that remediation options are part of the compliance rule definition, not the policy. That means a single policy can contain rules with different remediation options. To see the remediation options, go to Compliance --> Device Policies, open up a policy, and bring up the rule editor by either creating a new rule or selecting an existing one. You will see the “Remediation” drop-down menu: 1 - Remediation Type "Manual" The first and simplest remediation type is “Manual”. This is simply a text string providing instructions to an operator who is responding to a compliance alert. For example, a simple rule that checks for the existence of a default “public” SNMP community on a Cisco IOS device could have these very simple instructions: When a device is in violation of this rule, the remediation text will be included in the alert that gets generated. Here, in an email alert: 2 - Remediation Type "Automatic" The second remediation type, “Automatic”, lets you specify a series of commands to execute on the device. For example, to enable auto-remediation of our example “No Public SNMP Community” rule, you could run the “no snmp-server community public” IOS command: When a device is in violation of this rule, the specified commands are automatically executed on the device, bringing it back into compliance. 3 - Remediation Type "Command" The final remediation type, “Command”, is similar to “Automatic” except that, instead of entering the commands to run on the device, you can specify a previously saved Device Control script to run. In our example: Here, the "Remove Public SNMP Community" script has previously been saved and contains the same commands we used in the "automatic" example: Since device controls can be created as Lua scripts instead of simple lists of commands, using the “command” remediation type allows for more complex actions. Summary The goal of this article was to introduce the different Remediation options in Restorepoint. Remember: You don't have to add remediation steps to every rule in a policy -- and the ones you do add don't have to be of the same type. Even if you are not ready to enable automatic reconfiguration of devices in your environment, don’t be afraid to add a “manual” Remediation action to your compliance rules. Coming soon, I’ll post a follow-up article about using variables and Lua scripting to improve on the simple remediations we used today.
