Log Exports
DeepIntShield Enterprise provides comprehensive log export capabilities, allowing you to automatically export request logs, traces, and telemetry data to various storage systems and data lakes on configurable schedules.
Log exports are managed entirely from the DeepIntShield Workspace under Analytics → Exports. Each export is created as a job with a destination, a data configuration, and an optional schedule.
Overview
Section titled “Overview”The log export system enables:
- Scheduled Exports: Daily, weekly, or monthly automated exports
- Multiple Destinations: Object stores, data warehouses, and data lakes
- Format Flexibility: JSON or CSV, with optional gzip compression
- Filtering & Transformation: Export specific data subsets with custom transformations
- Compliance: Meet data retention and audit requirements
Creating an Export Job
Section titled “Creating an Export Job”From Analytics → Exports in the DeepIntShield dashboard:
- Click New Export and give the job a descriptive Name.
- Choose a Destination and fill in its connection fields (see Supported Export Destinations).
- Configure the Data to export - the format, compression, which datasets to include, and any filters or transformations.
- (Optional) Set a Schedule to run the export automatically, or leave it off to run on demand.
- Save the job, then use Run now to export immediately. Completed exports appear in the Exports list, where you can download the produced artifacts.
The sections below describe the destination, data, schedule, and transformation options you configure on this page.
Supported Export Destinations
Section titled “Supported Export Destinations”Each destination is configured with a type and a set of credentials and location fields entered in the export form.
Local download
Section titled “Local download”Choose Local to keep the artifact on the gateway and download it from the Exports list - useful for one-off audits before wiring a remote destination.
Object Storage
Section titled “Object Storage”Amazon S3
Section titled “Amazon S3”| Field | Example |
|---|---|
| Bucket | deepintshield-logs |
| Region | us-west-2 |
| Prefix | logs/{year}/{month}/{day}/ |
| Access Key ID | ${AWS_ACCESS_KEY_ID} |
| Secret Access Key | ${AWS_SECRET_ACCESS_KEY} |
Google Cloud Storage
Section titled “Google Cloud Storage”| Field | Example |
|---|---|
| Bucket | deepintshield-logs |
| Prefix | logs/{year}/{month}/{day}/ |
| Service Account Key | ${GCP_SERVICE_ACCOUNT_KEY} |
Azure Blob Storage
Section titled “Azure Blob Storage”| Field | Example |
|---|---|
| Container | deepintshield-logs |
| Account Name | ${AZURE_ACCOUNT_NAME} |
| Account Key | ${AZURE_ACCOUNT_KEY} |
| Prefix | logs/{year}/{month}/{day}/ |
Data Warehouses & Lakes
Section titled “Data Warehouses & Lakes”Snowflake
Section titled “Snowflake”| Field | Example |
|---|---|
| Account | your-account.snowflakecomputing.com |
| Database | DEEPINTSHIELD_LOGS |
| Schema | PUBLIC |
| Table | request_logs |
| Warehouse | COMPUTE_WH |
| Username | ${SNOWFLAKE_USERNAME} |
| Password | ${SNOWFLAKE_PASSWORD} |
Amazon Redshift
Section titled “Amazon Redshift”| Field | Example |
|---|---|
| Host | deepintshield-cluster.xxxxxx.us-west-2.redshift.amazonaws.com:5439 |
| Database | deepintshield_logs |
| Schema | public |
| Table | request_logs |
| Username | ${REDSHIFT_USERNAME} |
| Password | ${REDSHIFT_PASSWORD} |
Google BigQuery
Section titled “Google BigQuery”| Field | Example |
|---|---|
| Project ID | your-project-id |
| Dataset | deepintshield_logs |
| Table | request_logs |
| Service Account Key | ${GCP_SERVICE_ACCOUNT_KEY} |
Export Schedules
Section titled “Export Schedules”Enable a schedule on the export to run it automatically. Set the frequency, time, timezone, and (for weekly/monthly) the day. Leave the schedule off to run the export on demand.
| Frequency | Settings |
|---|---|
| Daily | Time (e.g. 02:00) and timezone (e.g. UTC). |
| Weekly | Day of week (e.g. sunday), time, and timezone. |
| Monthly | Day of month (e.g. 1), time, and timezone. |
Data Formats
Section titled “Data Formats”Choose JSON or CSV as the output format and, optionally, gzip compression. Each export can include request logs, response logs, error logs, traces, metrics, and MCP tool logs.
JSON Format
Section titled “JSON Format”{ "timestamp": "2024-01-15T10:30:00Z", "request_id": "req_123456789", "customer_id": "cust_abc123", "provider": "openai", "model": "gpt-4", "endpoint": "/v1/chat/completions", "method": "POST", "status_code": 200, "latency_ms": 1250, "input_tokens": 100, "output_tokens": 150, "cost_usd": 0.0045}CSV Format
Section titled “CSV Format”timestamp,request_id,customer_id,provider,model,endpoint,method,status_code,latency_ms,input_tokens,output_tokens,cost_usd2024-01-15T10:30:00Z,req_123456789,cust_abc123,openai,gpt-4,/v1/chat/completions,POST,200,1250,100,150,0.0045Data Filtering & Transformation
Section titled “Data Filtering & Transformation”Narrow the exported data and reshape it directly in the export’s Data configuration.
Filtering Options
Section titled “Filtering Options”Restrict the export to a subset of logs by date range, provider, model, status code, customer, latency bounds, or error state:
{ "filters": { "date_range": { "start": "2024-01-01T00:00:00Z", "end": "2024-01-31T23:59:59Z" }, "providers": ["openai", "anthropic", "azure"], "models": ["gpt-4", "claude-3-sonnet"], "status_codes": [200, 201, 400, 401, 403, 404, 500], "customers": ["cust_123", "cust_456"], "min_latency_ms": 100, "max_latency_ms": 10000, "has_errors": true }}Transformation Options
Section titled “Transformation Options”Aggregate, anonymize, or enrich records before they leave DeepIntShield:
{ "transformations": [ { "type": "aggregate", "group_by": ["provider", "model", "date"], "metrics": [ "count", "avg_latency", "p95_latency", "total_tokens", "total_cost", "error_rate" ] }, { "type": "anonymize", "fields": ["customer_id", "request_id"], "method": "hash" }, { "type": "enrich", "add_fields": { "export_timestamp": "${EXPORT_TIMESTAMP}", "export_version": "${EXPORT_VERSION}" } } ]}