Cloudflare Worker Logs

Cloudflare Worker Logs

Query historical logs from Cloudflare Workers using the Workers Observability API.

Requirements

Requires environment variables (should be defined in env already; if not, available via uv run poe init-secrets):

• CLOUDFLARE_ACCOUNT_ID
• CLOUDFLARE_API_TOKEN

Real-time Logs

For real-time log streaming (not historical queries), use wrangler tail instead:

cd terraform/cloudflare && wrangler tail llms --format pretty

This requires a terminal session that stays open.

Available Scripts

All scripts are in the scripts/ directory relative to this skill. Run them with:

uv run scripts/<script_name>.py [args]

cf_workers_list.py

List all Workers in the Cloudflare account. If you only need details of a single Worker, use cf_worker_get.py instead.

uv run scripts/cf_workers_list.py

No arguments required.

cf_worker_get.py

Get the details of a Cloudflare Worker.

uv run scripts/cf_worker_get.py <script_name>

Arguments:

• script_name (required): The name of the worker script to retrieve

cf_observability_keys.py

Find keys in the Workers Observability data.

Best Practices:

• Set a high limit (1000+) to ensure you see all available keys
• Add the $metadata.service filter to narrow results to a specific Worker

Troubleshooting:

• If expected fields are missing, verify the Worker is actively logging
• For empty results, try broadening your time range

uv run scripts/cf_observability_keys.py [options]

Options:

• --minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)
• --limit N: Max keys to return (default: 100, set high like 1000 for comprehensive list)
• --key-needle PATTERN: Pattern to match key names
• --key-needle-regex: Treat key-needle as regex
• --needle TEXT: General text search in log content
• --needle-regex: Treat needle as regex
• --filter KEY:OP:TYPE:VALUE: Filter (can be repeated)

Example:

uv run scripts/cf_observability_keys.py --limit 1000 --filter '$metadata.service:eq:string:llms'

cf_observability_values.py

Find values in the Workers Observability Data.

Troubleshooting:

• For no results, verify the field exists using cf_observability_keys.py first
• If expected values are missing, try broadening your time range

uv run scripts/cf_observability_values.py <key> [options]

Arguments:

• key (required): The key to get values for (e.g., $metadata.service, $metadata.level)

Options:

• --key-type {string,number,boolean}: Type of the key (default: string)
• --minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)
• --limit N: Max values to return (default: 50)
• --needle PATTERN: Pattern to match values
• --needle-regex: Treat needle as regex
• --filter KEY:OP:TYPE:VALUE: Filter (can be repeated)

Example:

uv run scripts/cf_observability_values.py '$metadata.service' --limit 100

cf_observability_query.py

Query the Workers Observability API to analyze logs and metrics from Cloudflare Workers.

Core Capabilities:

This script provides three primary views of your Worker data:

1. events (default): Browse individual request logs and errors
2. calculations: Compute statistics across requests (avg, p99, etc.)
3. invocations: Find specific request invocations matching criteria

Examples by View Type:

Events View:

• "Show all errors for worker llms in the last 30 minutes"
• "Show events where the path contains /api"

Calculation View:

• "What is the p99 wall time for worker llms?"
• "Count requests grouped by status code"

Invocation View:

• "Find a request that resulted in a 500 error"
• "List successful requests with status 200"

Filtering Best Practices:

• Before applying filters, use cf_observability_keys.py and cf_observability_values.py to confirm available fields and values
• Common filter fields: $metadata.service, $metadata.origin, $metadata.trigger, $metadata.message, $metadata.level, $metadata.requestId

Calculation Best Practices:

• Before applying calculations, use cf_observability_keys.py to confirm the key exists

Troubleshooting:

• If no results returned, try broadening the time range or relaxing filters
• For errors about invalid fields, use cf_observability_keys.py to see available options

uv run scripts/cf_observability_query.py [options]

Options:

• --view {events,calculations,invocations}: Query view type (default: events)
• --minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)
• --limit N: Max results to return (default: 10)
• --offset ID: Pagination offset (use $metadata.id from previous results)
• --offset-by N: Numeric offset for pagination
• --offset-direction {next,prev}: Pagination direction
• --dry: Dry run - validate query without executing
• --granularity N: Time bucket granularity for calculations
• --filter KEY:OP:TYPE:VALUE: Filter (can be repeated)
• --filter-combination {and,or}: How to combine filters (default: and)
• --calculation OPERATOR[:KEY[:TYPE[:ALIAS]]]: Calculation (can be repeated, for calculations view)
• --group-by VALUE[:TYPE]: Field to group by (can be repeated)
• --order-by ALIAS: Calculation alias to sort by
• --order {asc,desc}: Sort order (default: desc)
• --needle TEXT: Full-text search in log content
• --needle-regex: Treat needle as regex

Filter Format:

Filters use format key:operation:type:value where:

• key: Field name (e.g., $metadata.service)
• operation: One of includes, not_includes, starts_with, regex, exists, is_null, in, not_in, eq, neq, gt, gte, lt, lte
• type: One of string, number, boolean
• value: Comparison value

Calculation Format:

Calculations use format operator[:key[:key_type[:alias]]] where:

• operator: One of uniq, count, max, min, sum, avg, median, p001, p01, p05, p10, p25, p75, p90, p95, p99, p999, stddev, variance
• key: Field to calculate on (optional for count)
• key_type: Type of the key (default: number)
• alias: Name for this calculation in results

Examples:

Show recent errors for the llms worker:

uv run scripts/cf_observability_query.py --filter '$metadata.service:eq:string:llms' --filter '$metadata.level:eq:string:error' --limit 20

Get p99 wall time grouped by service:

uv run scripts/cf_observability_query.py --view calculations --calculation 'p99:wallTime:number:p99_wall' --group-by '$metadata.service'

Count requests by status code:

uv run scripts/cf_observability_query.py --view calculations --calculation 'count' --group-by 'response.status:number'

Search for specific text in logs:

uv run scripts/cf_observability_query.py --needle 'timeout' --minutes 120

cf_analytics_query.py

Query Workers Analytics Engine datasets using the SQL API. This is for custom metrics written via writeDataPoint(), not request logs (use cf_observability_query.py for logs).

Key Features:

• Automatic semantic aliases for known datasets (e.g., blob1 → path, double1 → latency_ms)
• Built-in sampling-aware aggregation helpers
• Raw SQL mode for complex queries

Schema for llms_usage dataset:

uv run scripts/cf_analytics_query.py [options]

Options:

• --dataset NAME: Analytics Engine dataset (default: llms_usage)
• --minutes N: Time range in minutes (default: 60)
• --limit N: Max results (default: 20)
• --field FIELD: Field to select (can be repeated). Omit for default fields with aliases.
• --agg EXPR: Aggregation expression (e.g., SUM(_sample_interval) AS count). Can be repeated.
• --group-by FIELD: Field to group by (can be repeated). Use with --agg.
• --where CONDITION: WHERE clause condition (can be repeated). E.g., "blob2 = '401'"
• --order-by FIELD: Field or alias to order by
• --order {asc,desc}: Sort order (default: desc)
• --raw QUERY: Execute raw SQL (ignores other query options)
• --format {json,jsonl,tsv}: Output format (default: json)
• --show-query: Print generated SQL
• --show-schema: Show schema mapping for dataset
• --list-datasets: List available datasets

Examples:

Show recent events with semantic field names:

uv run scripts/cf_analytics_query.py --limit 10

Request counts by path and status (last 24 hours):

uv run scripts/cf_analytics_query.py --agg 'SUM(_sample_interval) AS request_count' --group-by blob1 --group-by blob2 --minutes 1440

Average latency by method:

uv run scripts/cf_analytics_query.py --agg 'SUM(_sample_interval * double1) / SUM(_sample_interval) AS avg_latency_ms' --group-by index1

Filter by status code (show 401 errors):

uv run scripts/cf_analytics_query.py --where "blob2 = '401'" --minutes 1440

Raw SQL query:

uv run scripts/cf_analytics_query.py --raw "SELECT blob1, SUM(_sample_interval) AS count FROM llms_usage GROUP BY blob1 ORDER BY count DESC LIMIT 10"

Sampling Notes:

Analytics Engine may sample high-volume data. Always use _sample_interval for accurate counts:

• Count: SUM(_sample_interval) instead of COUNT()
• Sum: SUM(_sample_interval * field) instead of SUM(field)
• Average: SUM(_sample_interval * field) / SUM(_sample_interval) instead of AVG(field)

Preferred Filter Keys

These keys are faster and always available:

• $metadata.service: Worker name
• $metadata.origin: Trigger type (fetch, scheduled, queue, etc.)
• $metadata.trigger: Request method and path (e.g., GET /users)
• $metadata.message: Log message text
• $metadata.error: Error message (when applicable)
• $metadata.level: Log level (log, warn, error)
• $metadata.requestId: Unique request identifier

Regex Notes

For regex operations, Cloudflare uses ClickHouse RE2 syntax (not PCRE/JavaScript):

• No lookaheads/lookbehinds
• Escape backslashes with double backslash