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Monitor LangGraph in production with three distinct views: run-level traces to see what an agent did, online evaluations to flag output-quality problems, and runtime metrics to spot capacity pressure. For LangGraph Agent Server, LangChain documents LangSmith tracing and online evaluation; trace destinations vary by deployment type.
How do you monitor LangGraph runs in production?
Use traces, quality checks, and runtime signals together. They answer different questions: traces show execution flow and component behavior; online evaluations provide feedback on production outputs; runtime metrics show whether the deployment is under resource or queue pressure.
- Choose and verify the trace destination. Check the configuration for your Agent Server deployment before enabling tracing. LangChain’s Agent Server tracing documentation describes different options for Cloud, Hybrid, and Self-Hosted environments.
- Capture useful run context. Decide which graph runs, component details, tool calls, and metadata operators need to investigate. Stable, non-sensitive metadata can help target evaluator filters.
- Inspect traces during incidents. Use a run’s execution flow to investigate whether the issue involved an unexpected tool call, a slow or failing component, or an unsatisfactory result.
- Evaluate production outputs. Set up a small set of online evaluators tied to user outcomes, safety needs, or known failure modes. Filter the runs each evaluator handles where appropriate, then route concerning results for review.
- Keep offline regression checks. Before rollout, compare versions against curated examples. Add useful production findings to those examples so offline checks can cover failures observed in live traffic.
- Monitor runtime capacity separately. For Agent Server Production deployments, track CPU utilization, memory utilization, and pending runs alongside application-level quality and latency indicators.
How can you trace a LangGraph agent run?
A trace makes a run inspectable: it provides evidence about the execution path and the behavior of its components. When diagnosing a bad result, use that evidence to locate the step where behavior diverged—such as a tool call or a component failure—instead of treating the final answer as the only signal.
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LangChain’s Agent Server tracing configuration documentation lists these options by deployment type:
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- Adjustable Depth & 2 Set Rack Rails: Includes two sets of Rack Rails. Short Rack Rails: Fit 18.9"–23.6" (480-600mm) deep network racks (Note: check cable clearance for depths under 600mm). Long Rack Rails: Fit 23.6"–31.5" (600-800mm) deep standard racks. Measure your rack depth before purchase to ensure a perfect fit.
- External Monitor Support & Flexible Operation--Features an VGA console output for connecting an external monitor, allowing convenient server access without opening the rack. Supports front panel buttons, touchpad, hotkeys, and OSD menu control. Support password prodected: provides 2-level password security (administrator and user), up to 8 authorized users and an administrator view and control the computers.
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- Built for Professional Environments – Ideal for server rooms, data centers, industrial control systems, and security monitoring centers where multiple computers need centralized management or when technicians need direct access to connected systems without an external monitor.
| Deployment | Documented tracing options |
|---|---|
| Cloud | Traces to LangSmith SaaS |
| Hybrid | Disable tracing or trace to LangSmith SaaS |
| Self-Hosted | Disable tracing, trace to LangSmith SaaS, or trace to Self-Hosted LangSmith |
Confirm the applicable configuration and data-handling implications for your environment before turning tracing on. These options are specific to the documented Agent Server deployment models; do not assume that all deployments send traces to the same destination.
Make runs useful to investigate
Choose context that helps an operator answer concrete questions: which request or graph run is involved, which components ran, and which tools were called. Use metadata consistently if you want to target subsets of runs: LangSmith online-evaluator filters can select runs based on metadata or tool calls. Avoid putting sensitive information in metadata unless your own privacy and data-handling requirements permit it.
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- HASSLE-FREE ACCESS: The KVM console design provides an LCD monitor for all-in-one control with a space-saving design when you need to access your server, then easily tuck the rackmount console away, when not in use.
- LCD MONITOR: The KVM console features 19" LCD display and supports video resolutions up to 1280 x 1024
- GREAT COMPATIBILITY: The B021-000-19 is compatible with most PS/2 and USB KVM switches, making it easy to integrate with an existing system.
- USB PASS-THROUGH: The unit features a USB 2. 0 pass-through port for connection of a USB peripheral, such as a flash drive, CAC card reader, etc. .
- TAA-Compliant for GSA Schedule Purchases and 1-Year
The cited documentation does not establish a universal trace-retention period or a standard redaction configuration. Set retention and redaction practices to suit your application’s privacy obligations and operational needs.
How do you catch agent quality regressions in production?
Use online evaluation to assess production traces, not just availability. LangChain describes online evaluations as real-time feedback on production traces; evaluators can flag unusual behavior and help surface cases for human review. Choose checks that correspond to a meaningful user outcome, safety requirement, or known failure mode, and narrow their scope with filters when that makes the results more relevant.
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- Compatible to: This Mounting Bracket is designed for the TAA compliant Universal VESA LCD Monitor in 19-inch network cabinet or server rack.
- Sturdy Structure: The LCD mounting bracket is made of cold rolled steel and supports 100mm & 75mm VESA mounted LCD panels.
- Adjustable Depth: This adjustable depth design enables an LCD panel to be mounted into the AV rack cabinet at various depths; allowing the rack or cabinet door to be closed.
- Multi-use: Besides using in 19" network cabinet or server rack, the LCD monitor can be mounted onto wall by adding this bracket onto a wall mount bracket or rack.
Online checks and offline regression evaluation serve different purposes. Production evaluation gives feedback on live runs; offline evaluation compares application versions against curated examples before deployment. A production failure can become a new offline test case, helping the pre-release set reflect problems the application has actually encountered. For setup details, see LangSmith’s online evaluation documentation and its evaluation concepts.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should you monitor for a LangGraph deployment?
Keep application behavior and deployment capacity distinct in dashboards and incident reviews. A deployment can have healthy resource use while producing poor answers, or show resource pressure without a demonstrated quality regression.
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- 8 Port Rackmount KVM Console, is integrated 8 port kvm switch, touchpad, keyboard and 17.3'' LCD monitor, ideal to manage up to 8 computer/servers. Fits 1U 19'' rack. Come with a USB 2.0 Port for external Mice or keyboard.
- Product Dimension (W×D×H):18.9×23.6×1.77 inches [480x600x45mm]. [Mount depth]: 23.6- 31.8" [60-81cm]，Mounts into 19”-wide rack. The monitor is adjustable, the max angle is 110°
- External Monitor Support & Flexible Operation--Features an HDMI console output for connecting an external monitor, allowing convenient server access without opening the rack. This Rack KVM Switch support Three Switching Ways: OSD menu + Keyboard Hotkey+ Button. There are 2 OSD menu: Screen OSD and KVM OSD, also supports external USB mouse.
- Come with Handle & Lock. [All-IN-ONE Design] You just need to place the KVM directly into 1U rackmount and tighten the screws. Designed for data centers, enterprise IT, government, and educational institutions, delivering a secure, scalable, and efficient server management solution.
- [Security & Durability] 2 Level Password Security, only authorised users can view and control computers; This KVM console is upgraded with alumium for less wight, and the draw shell is made by steel for sturdy. Compatible with Dos/Windows, Linux, Unix, Mac OS8.6/9/10, Unix and SUN Solaris 8/9.
Application behavior and quality
- Run traces for execution flow, component behavior, and tool calls.
- Online evaluator results for production output quality and unusual behavior.
- Application-level latency and other user-outcome indicators chosen for your workload.
Agent Server capacity signals
For Production autoscaling, LangChain’s documentation specifies targets of 75% CPU utilization, 75% memory utilization, and 10 pending runs per container. It also says scale-down waits 30 minutes before recomputing metrics and acting. These are documented deployment autoscaling parameters, not universal application SLOs or independently measured benchmarks. Establish alert thresholds and service objectives for your own workload rather than treating the targets as guaranteed performance standards. See the Agent Server deployment documentation.
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LangSmith is directly documented for Agent Server tracing and production online evaluation. Teams already using MLflow may also consider the LangChain MLflow integration, which documents tracing, experiment tracking, model management, and evaluation. The available documentation does not establish a full feature or cost comparison, so choose based on your deployment’s trace destination and control requirements, need for run-level inspection, online and offline evaluation workflow, and integration with your runtime.
Quick Recap
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