This topic introduces Claude observability, an LLM observability log application available in TLS application marketplace.

Overview

The Claude observation log observability in TLS offers services such as a Claude observability dashboard, Trace Call Chain, session analysis, and Token analysis.

By integrating the Claude Observability log application, TLS automatically creates a dedicated Trace log topic for Claude, generates visual charts, and displays session, Trace, token, and tool invocation data, enabling traceability and observability. Applicable scenarios include the following:

Observability	Description
Performance analysis	Model invocation latency distribution Tool execution time ranking Token consumption trends
Error tracking	View the complete call chain Locate the error point Analyze the cause of the error
Cost optimization	Identify high-consumption conversations Optimize prompts to reduce tokens Select a more cost-effective model

Prerequisites

Category	Description
Software limits	To deploy Claude, the server must have NPM and Node.js version 22 or later installed.
Region restriction	The server deploying Claude and TLS must be in the same region to ensure network connectivity.
Authentication method	Obtain the user's Access Key ID, Secret Access Key, or APIKey according to the authentication method. AK/SK: AccessKey ID and AccessKey Secret for Volcano Engine accounts. Obtain them on the Volcano Engine console Key Management page. We recommend using IAM user keys. Ensure this user has the required permissions. For details, see IAM overview. Supports automatic creation of TLS resources (project/app/topic) and auto-generates log topic IDs. API Key: A key credential for requesting Volcano TLS. It is used only for reporting Log, Metric, and Trace data. Enforces strict permissions and does not support auto creation of TLS resources. It is suitable for multi-data center environments and strict permission management scenarios. Notice API Key is in closed beta. If needed, contact your account manager for access to the allowlist.

1 Integrate the Claude log application

Log in to TLS console.

Select the region where log service is located from the top navigation bar.

In the left navigation bar, select AgentLoop > AI Observability.

On the AI Observability page, click Integrate AI Observability.

On the Integrate AI Observability page, create an application.

Click the Claude icon and select the Claude application.

Configure the integration parameters, then click Create Application.

Parameters	Description
Region	The region where the log application data is stored.
Log project	Select the project where the log application data is stored. Notice After the log application is created successfully, a log topic with the CLAUDE tag will be automatically created in the project to store trace data. Details of the log topic are as follows: Log topic name: application name_trace Number of shards: 2 Log storage period: Standard storage for 90 days Index: Key-value index configured automatically.
Application name	Enter the name of the Claude log application. Length must be between 3 and 64 characters. Only supports Chinese, lowercase letters, numbers, underscores (_), and hyphens (-). Can not start or end with a hyphen (-) or underscore (_). Cannot start with tls_, tos_, or certain reserved keywords.
Description	Description of the log application. Length limit is 0–128 characters.

After creating the application, proceed to the next step to obtain the usage guide and integrate the log application.

2 Integrate Claude application data

Obtain the usage guide for integrating Claude application data.

Go to the Integration Configuration page.

When integrating the log application
After integrating the log application
When creating a Claude log application in AgentLoop, follow the on-screen instructions to obtain the corresponding usage guide.
Refer to 1 Integrate the Claude log application to integrate the Claude log application.
On the Integrate AI Observability page, in Integration configuration, configure the following information to obtain the usage guide.
Log in to TLS console.
Select the region where log service is located from the top navigation bar.
In the left navigation bar, select AgentLoop > AI Observability.
On the AI Observability page, use the following methods to access the usage guide page.
Click the access configuration icon in the Operations column of the target log application.
Click the target log application's name, and then click Access management.

On the Integration Configuration page, select the authentication method, configure the following information, and obtain the usage guide.

AK/SK access
API Key access
For Access method, select AK SK access.
For Connection method, select Public network or Volcano Engine internal network based on actual requirements.
In Usage guide, copy the auto-generated usage guide.
For Access method, select API Key access.
For Connection method, select Public network or Volcano Engine internal network based on actual requirements.
For API Key, select the API Key that has been created.
In Usage guide, copy the auto-generated usage guide.

Usage guide example (AK/SK integration method):

Public network
Volcano Engine internal network

npm exec -y
--registry=https://registry.npmjs.org/
--package=@volcengine/tls-observer-claude-code-install@latest --
tls-observer-claude-code-install
--non-interactive
--force
--region The system autopopulates the current region.
--trace-topic-id The system autopopulates trace-topic-id
--ak <Requires manual replace of the actual tls-ak>
--sk <Requires manual replace of the actual tls-sk>

(AK/SK method only) Modify the authentication information in the usage guide.

Enter the obtained Access Key ID and Secret Access Key into the AK and SK fields in the usage guide, respectively.

Integrate the Claude Observability logs into the log application.

Log in to the server where Claude is deployed.

Execute the instructions from the usage guide to install the TLS plugin.

After the plugin is installed, restart the Claude service.

Return to the TLS console to view the observability chart data.

Monitoring chart details

The monitoring chart details of the Claude observability application in TLS are as follows:

Type	Chart
Homepage	Request overview: Number of sessions, number of conversations, model request count, tool invocation count, and request trend. Cost overview: Total Tokens, Input Tokens, Output Tokens, Cache Read Tokens, Reasoning Tokens, Token consumption trend, and model invocation trend Tool overview Successful invocation count, failed invocation count, tool invocation latency P90, tool invocation Top 10, tool invocation failure Top 10, and tool invocation trend Model performance overview Model invocation distribution Top 10, model invocation latency P90, Provider invocation distribution, and Provider invocation latency P90
Trace analysis	Homepage Total trace count, total token consumption, average tokens, P90 duration Trace call chain analysis Display Input, Output, Trace ID, total Tokens, InputTokens, OutputTokens, latency (s), start time, end time, and more for the specified call chain.
Session analysis	Homepage Session count, total token consumption, model request count, average session tokens Session analysis Display First Input, Last Output, Session ID, total Tokens, call chain count, latency (s), model, start time, end time, and more for the specified session.
Token analysis	Homepage Total Tokens, Input Tokens, Output Tokens, Cache Read Tokens, Reasoning Tokens, InputTokens (excluding Cache), session Token consumption Top 10, model Token consumption Top 10, and Token category proportion
Topic list	Display the log types, projects, log topics, and description information generated by the current log application.

Manage my applications

After the log application is successfully connected, you can manage connected log applications as follows:

AgentLoop

Application marketplace

Log in to TLS console.

Select the region where log service is located from the top navigation bar.

In the left navigation bar, select AgentLoop > AI observation.

On the AI observation page, in the Operations column of the corresponding log application, the following management actions are supported:

Edit application information: Click the edit icon to modify the application name and description information.

Obtain usage guide: Click the access configuration icon to open the access configuration popup, where you can obtain sample information for the usage guide.

Delete my application: Click the delete icon to remove this log application.

ApplicationName_trace (log topic) log fields

Field	Type	Description
Attributes	json	Custom key-value pairs attached to the Span, recording business-related information.
Duration	long	Duration of the Span (End - Start), measuring the time consumed by the operation.
End	long	Span end time.
Events	text	Events that occur during the Span lifecycle.
Host	text	The host running the service.
Kind	text	Type of the Span.
Links	text	References to other Spans (used for cross-Trace associations, such as asynchronous task scenarios).
Name	text	Name of the Span, usually describing the operation.
OTLPName	text	Original name when reported via the OTLP protocol (OTLP = OpenTelemetry Protocol).
OTLPVersion	text	Version number of the OTLP protocol used.
ParentSpanID	text	ID of the parent Span, indicating which operation triggered the current operation. This field is empty for the root node.
Resource	json	A set of attributes describing the service itself (more comprehensive than ServiceName), such as service name, version, runtime environment, and so on.
ServiceName	text	Name of the service that generated this Span.
SpanID	text	Unique ID of the current Span.
Start	long	Span start time.
StatusCode	text	Execution result of the Span.
StatusDescription	text	Supplementary description of the Span's execution result.
TracelD	text	TraceID for the entire call chain. All Spans for the same request share the same TraceID.
TraceState	text	Custom trace context metadata.

Attributes

Field	Type	Description
gen_ai.input.messages	text	Complete list of input messages sent to the model.
gen_ai.provider.name	text	Name of the model provider.
gen_ai.request.model	text	Name of the model specified in the request.
gen_ai.tool.name	text	Name of the tool involved in this invocation.
gen_ai.usage.cache_read.input_tokens	long	Number of input tokens that hit the KV cache.
gen_ai.usage.input_tokens	long	Number of input tokens consumed by this request.
gen_ai.usage.output_tokens	long	Number of output tokens consumed by this request.
gen_ai.usage.reasoning.output_tokens	long	Number of output tokens consumed by reasoning.
gen_ai.usage.total_tokens	long	Total number of tokens.
session.id	text	ID of the current Session.
session.name	text	Name of the current Session.
tls.app.type	text	Application type identifier, indicating which log application form this Span belongs to.
tls.plugin.version	text	Version number of the observability plugin.
tool.error	text	Error message when tool execution fails.

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