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NetBrain currently does not support capturing command output from Intent execution within the Document Node of a Runbook, leaving generated documents without a record of the commands that were run. This enhancement would add an option to the Document Node allowing command output from Intent execution to be included in the generated document. Customers who must retain execution evidence for change records or ticketing systems would benefit from having a complete, exportable record of commands executed and their results.
NetBrain's discovery and path analysis capabilities currently do not extend beyond the internal network to cover internet segments, public cloud providers, or SaaS applications, limiting end-to-end visibility for hybrid environments. This enhancement would introduce an API-based integration with a third-party internet and cloud monitoring service to extend path analysis and diagnostics to internet-facing destinations, public cloud services, and SaaS applications, along with cross-domain visibility across underlay and overlay network infrastructure and cloud topology. Customers operating hybrid network and cloud environments would gain unified, end-to-end path and topology visibility, reducing the need to correlate data manually across separate monitoring tools.
NetBrain does not currently provide a way to acknowledge an active alert and temporarily suppress it from reappearing while a known issue is being addressed. Once an alert condition is detected, it continues to be reported on the dashboard until the underlying condition is resolved, with no mechanism to pause notifications for issues already being worked on. This enhancement would introduce an alert acknowledgement action that allows a user to mark an alert as acknowledged and suppress it for a configurable time period. Once the suppression period expires, the alert would resume normal reporting if the condition still exists. This capability would reduce alert noise for issues already in progress, allowing teams to focus dashboard attention on new or unresolved conditions.
In distributed deployments with multiple worker servers updating dashboards in parallel, the current update mechanism relies on incrementing and decrementing shared counters based on timestamp heuristics. This approach is susceptible to race conditions, which can produce inconsistent or negative values on dashboard widgets. This enhancement would make the dashboard update mechanism idempotent and safe for concurrent, multi-worker execution, ensuring counter updates are applied consistently regardless of timing or ordering. Reliable, consistent dashboard values are essential for customers operating large, multi-server environments who depend on dashboards for accurate operational visibility and trust in the platform.
NetBrain currently does not show users how many login attempts remain after an incorrect password entry, nor does it display the cooldown period or next allowed login time once an account becomes locked. Failed login entries also require manual deletion from the database rather than being cleared automatically after a defined interval. This enhancement would add visible attempt-remaining and lockout-countdown information to the login workflow, and would introduce an automatic cleanup mechanism for failed login records after a configurable interval. Customers would benefit from clearer account status feedback and reduced administrative overhead in managing lockout data, helping to minimize unnecessary lockouts and improve the overall login experience.
The current Start Menu icon does not follow standard app launcher conventions found in modern UI design, which can make navigation less intuitive for users. This enhancement proposes replacing the existing icon with a standard app launcher icon consistent with common UI patterns. Adopting a familiar icon design would improve usability and reduce the learning curve for new users navigating the interface.
NetBrain currently requires users to add a Runbook node to the Favorites panel by opening the hamburger menu on that node and selecting the appropriate option, which adds extra steps to a routine workflow. This enhancement would allow users to drag and drop a Runbook node directly onto the Favorites panel to mark it as a favorite. Customers who frequently reuse specific nodes across Runbooks would benefit from a faster, more intuitive way to manage their favorites without navigating through menus.
NetBrain currently organizes Runbook node types into tabs within the node selection panel, but the Free Text and Favorites sections are not grouped under the Essential tab alongside commonly used node types. This enhancement would relocate the Free Text and Favorites sections into the Essential tab, consolidating frequently accessed node categories in a single location. Customers building Runbooks would benefit from a more intuitive node selection experience and reduced time spent navigating between tabs to locate commonly used node types.
The Runbook editor currently does not provide a way to reorder nodes within a Runbook by dragging them into a new position. Users who need to adjust the sequence of steps must rely on manual reconnection or recreation of nodes, which is time-consuming and prone to error. This enhancement would introduce drag-and-drop functionality that allows users to reposition nodes directly within the Runbook canvas, automatically updating the connections to reflect the new order. Customers building or maintaining complex Runbooks would benefit from a more intuitive editing workflow and reduced effort when adjusting the logical flow of a Runbook.
NetBrain currently places the 'Run All' option for Runbooks within a hamburger menu, requiring users to open a secondary menu to locate and trigger it. This enhancement would surface the 'Run All' option directly within the primary Runbook interface, making it immediately visible without additional navigation. Improved discoverability of this control would reduce the time and effort required for users to execute a full Runbook, particularly for those less familiar with the current menu structure.
The option to create a support ticket is not currently located in the top navigation bar, reducing its visibility to users during daily workflows. This enhancement would relocate the Create Support Ticket action back to the top bar so it remains readily accessible. Increasing visibility of this frequently used feature would help customers initiate support requests more efficiently.
NetBrain currently does not support receiving or processing NetFlow data when devices are configured to export their flow records directly to NetBrain. This limits visibility for customers who rely on flow-based traffic analysis as part of their network monitoring strategy. This enhancement would add native NetFlow collector functionality, allowing NetBrain to receive, parse, and process flow records sent from network devices. Customers would benefit from consolidated flow-based traffic insight within the same platform used for device and path visibility, reducing the need for a separate flow collection tool.
System Management currently does not provide administrators with a way to unlock a user account that has been locked due to exceeding the maximum number of failed login attempts. This enhancement would add an unlock action within System Management, allowing an authorized administrator to manually restore access to a locked account without requiring a password reset or backend intervention. Customers would benefit from faster resolution of account lockouts and reduced dependency on external support channels for routine access issues.
NetBrain's AI Companion and Deep Diagnosis currently process runbook logic and commands as provided, and will reflect errors present in a runbook's underlying logic or commands rather than identifying them as mistakes. This enhancement would enable the AI to cross-reference runbook logic and commands against correlated network engineering knowledge, using retrieval-augmented techniques, to detect and flag likely human-made errors instead of simply reporting flawed output as valid. Customers relying on AI-driven diagnosis would benefit from improved output accuracy and increased confidence that runbook-driven results reflect sound network engineering practice rather than propagating undetected mistakes.
Golden Assessment dashboards are currently organized by zone and display results for all supported protocols, including those a customer does not use, such as ISIS or EIGRP alongside BGP or OSPF. This structure limits the ability to present results in a way that aligns with business priorities or operational relevance, and reduces clarity for teams reviewing assessment data. This enhancement would introduce dashboard views that can be organized around business-relevant groupings rather than zone alone, and that are context-aware based on the protocols and features actually in use within a customer's environment. Customers would benefit from clearer, more relevant assessment views that reduce noise and better reflect their specific network operations.
NetBrain currently allows a Network Intent to be saved even when its diagnosis logic contains an incomplete conditional statement, such as a where condition that has not been fully defined. This can result in intents that fail to evaluate correctly during execution without any indication at the time of authoring. This enhancement would introduce validation that detects incomplete conditional logic when a user attempts to save a Network Intent, displaying an alert and preventing the save until the condition is completed. This capability would help customers catch configuration errors earlier, reducing troubleshooting effort and preventing faulty diagnosis outcomes caused by incomplete intent logic.
The Configlet node in Runbook currently does not provide inline guidance to distinguish between the config parser and golden config options, which can lead to confusion about their intended use. This enhancement would add tooltips or contextual hints within the Configlet node interface to clarify the purpose and difference between these two options. Providing this guidance would help users configure the node correctly on the first attempt and reduce setup errors during Runbook design.
NetBrain's chatbot default node output currently surfaces only intent-level Msg/Status Code information. When an intent's status code level changes to device level, chatbot flows built against the prior intent-level output no longer display any result. This enhancement would update the chatbot default node output to include both intent-level and device-level status codes, or default to device-level status code, and would apply equivalent handling to existing chatbot definitions that reference only intent-level status codes. Customers would benefit from consistent chatbot behavior across product versions, avoiding silent result gaps when underlying status code levels change.
New users currently have no guided starting point when they first access the product, and the interface offers no contextual explanation of available features, which forces reliance on external documentation or training to become productive. This enhancement would introduce an onboarding wizard for first-time users along with contextual help bubbles placed throughout the interface, providing brief in-product explanations of key features and workflows as users encounter them. Customers new to the platform would be able to orient themselves and begin working more quickly, reducing the learning curve and dependence on formal training resources.
Path-Based Automation currently operates separately from the Golden Automation List (GAL) and requires use of the path browser, making it less accessible than other automation features. Publishing path intents to NB Insight also relies on a workflow that is difficult to locate, and there is no integrated way to manage path intents alongside other automation workflows or share and execute them without sending individual paths to dashboards. This enhancement would integrate path-based automation into GAL and streamline the publishing process for path intents to NB Insight. Customers would benefit from a more consistent automation experience and reduced effort when managing and sharing path-based diagnostics.
NetBrain currently does not provide contextual guidance to help users transition between related features, such as moving from chatbot interactions to change template workflows. Given the density of the interface, users can find it difficult to understand how these features connect or what steps to take next. This enhancement would introduce integrated in-app guidance, such as contextual tooltips, workflow prompts, or a guided walkthrough, to orient users as they move between related capabilities. Providing this guidance would reduce confusion, shorten the learning curve, and help customers navigate the platform's features more efficiently.
Manual input editing controls in the chatbot interface, such as the icon used to modify an existing input value, are not visually discoverable to users today, which can make it difficult for users to realize that editing is possible. This enhancement would redesign the manual input editing affordance to be more visible and intuitive, such as through clearer iconography, labeling, or persistent visibility rather than a hidden control. Improving discoverability of this function would reduce user confusion and support a more efficient, self-explanatory experience when building or adjusting chatbot automation inputs.
NetBrain currently does not offer a self-service chatbot capability to guide users through pre- and post-validation steps during a network change. Validation today relies on manual execution or fully separate automation flows, without an interactive, transparent assistant to walk a user through each check. This enhancement would introduce a chatbot-driven validation flow that guides users step by step through pre-check and post-check tasks tied to a change, keeping each action visible and confirmable rather than relying on fully autonomous AI decision-making. Customers would benefit from faster, more consistent change validation while retaining the transparency and control needed to trust the automated process.
NetBrain currently applies self-healing remediation actions without distinguishing between edge devices and core infrastructure, so automated changes carry the same risk profile regardless of the affected device's role in the network. This enhancement would introduce configurable scope controls that let administrators limit fully automated self-healing to lower-risk, edge-level devices while requiring additional review, approval, or exclusion for core infrastructure changes. Customers would benefit from faster automated resolution of isolated, low-impact issues while reducing the risk of unintended, broad-impact changes to critical network infrastructure.
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