Claude-skill-registry duckdb-alb-log-analyzer
Analyze AWS Application Load Balancer (ALB) logs stored in S3 using DuckDB. Use when users request ALB log analysis, error investigation, performance analysis, traffic analysis, or need to query ALB access logs. Supports analyzing response times, status codes, error patterns, and traffic trends from S3-stored logs.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/duckdb-alb-log-analyzer" ~/.claude/skills/majiayu000-claude-skill-registry-duckdb-alb-log-analyzer && rm -rf "$T"
skills/data/duckdb-alb-log-analyzer/SKILL.mdALB Log Analyzer
Analyze AWS Application Load Balancer (ALB) logs using DuckDB for fast, flexible S3-based queries.
Quick Start
Secure Method (Recommended for Named Profiles)
For AWS named profiles, use these secure scripts that keep credentials private:
# One-time setup (credentials read from ~/.aws/credentials) ./scripts/setup_with_profile.sh your-profile-name # Load logs (profile name only, credentials stay secure) ./scripts/load_with_profile.sh your-profile-name 's3://bucket/path/**/*.log.gz' # Analyze ./scripts/analyze.sh errors ./scripts/analyze.sh performance
Security: Only profile names appear in commands and logs. Credentials are read internally from
~/.aws/credentials.
Standard Method
Basic workflow for ALB log analysis:
- Setup DuckDB with AWS extensions
- Load logs from S3 into a table
- Run analysis queries (errors, performance, traffic, etc.)
- Export results or create custom queries
Prerequisites
Ensure DuckDB is installed:
# Install DuckDB (if not already installed) brew install duckdb # macOS # or download from https://duckdb.org/docs/installation/
AWS credentials must be configured. See AWS Credentials Setup section below for details.
Database File Location
By default, the DuckDB database file is stored at:
/tmp/alb-log-analyzer-${USER}/alb_analysis.duckdb
Important: The database file is automatically deleted when you run
setup or load commands. This ensures:
- Clean start with each analysis
- No accumulation of old data in /tmp
- Reduced disk space usage
This temporary location also:
- Keeps your skill directory clean
- Prevents data from being packaged with the skill
- May be cleared on system restart
To use a custom location, set the
DB_FILE environment variable:
export DB_FILE=/path/to/custom/database.duckdb
Setup
Method 1: Using CREDENTIAL_CHAIN (Recommended)
This method automatically detects AWS credentials from environment variables, ~/.aws/credentials, or IAM roles:
./scripts/analyze.sh setup
Method 2: Using Environment Variables
If CREDENTIAL_CHAIN doesn't work, explicitly set environment variables.
For default profile:
# Set AWS credentials export AWS_ACCESS_KEY_ID=your_key_id export AWS_SECRET_ACCESS_KEY=your_secret_key export AWS_DEFAULT_REGION=ap-northeast-1 # Setup DuckDB ./scripts/analyze.sh setup-env
For named profile:
# Export credentials from your profile export AWS_PROFILE=your-profile-name export AWS_ACCESS_KEY_ID=$(aws configure get aws_access_key_id --profile your-profile-name) export AWS_SECRET_ACCESS_KEY=$(aws configure get aws_secret_access_key --profile your-profile-name) export AWS_DEFAULT_REGION=$(aws configure get region --profile your-profile-name) # Setup DuckDB ./scripts/analyze.sh setup-env
Method 3: Manual SQL
duckdb alb_analysis.duckdb < scripts/setup.sql # or duckdb alb_analysis.duckdb < scripts/setup_s3_env.sql
Verify Setup
Diagnose your AWS credentials configuration:
./scripts/analyze.sh diagnose
This will show:
- Extension installation status
- Environment variable configuration
- Configured secrets in DuckDB
AWS Credentials Setup
DuckDB needs AWS credentials to access S3. Choose one of these methods:
Option 1: AWS CLI Configuration (Recommended)
If you have AWS CLI configured, DuckDB can use those credentials:
# Check if AWS CLI is configured aws s3 ls # If not configured, run: aws configure
Option 2: Environment Variables
Export credentials in your shell:
export AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE export AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY export AWS_DEFAULT_REGION=ap-northeast-1
Option 3: AWS Credentials File
Create or edit
~/.aws/credentials:
[default] aws_access_key_id = AKIAIOSFODNN7EXAMPLE aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
And
~/.aws/config:
[default] region = ap-northeast-1
Option 4: AWS Profile (For Named Profiles)
If you're using a named AWS profile (not
[default]), you need to explicitly export the credentials.
Easy way (using helper script):
# List available profiles aws configure list-profiles # Load credentials from your profile source scripts/load_profile.sh your-profile-name # Setup and use ./scripts/analyze.sh setup-env ./scripts/analyze.sh load 's3://your-bucket/path/**/*.log.gz'
Manual way:
# Check your profiles aws configure list-profiles # Export credentials from your profile export AWS_PROFILE=your-profile-name export AWS_ACCESS_KEY_ID=$(aws configure get aws_access_key_id --profile your-profile-name) export AWS_SECRET_ACCESS_KEY=$(aws configure get aws_secret_access_key --profile your-profile-name) export AWS_DEFAULT_REGION=$(aws configure get region --profile your-profile-name) # Setup DuckDB with these credentials ./scripts/analyze.sh setup-env # Load logs ./scripts/analyze.sh load 's3://your-bucket/path/**/*.log.gz'
Why this is needed: DuckDB doesn't automatically read from named AWS profiles. It only supports environment variables or the
[default] profile. By exporting the profile's credentials as environment variables, DuckDB can access them.
Option 5: IAM Role (EC2/ECS)
If running on EC2 or ECS, DuckDB can use the instance's IAM role automatically.
Loading Logs
Load ALB logs from S3 into a DuckDB table.
Using the analyze.sh script
# Load logs from S3 ./scripts/analyze.sh load 's3://my-bucket/AWSLogs/123456789012/elasticloadbalancing/us-east-1/2024/11/**/*.log.gz'
Manual SQL approach
- Generate SQL from template:
# Replace placeholders sed -e "s|{{TABLE_NAME}}|alb_logs|g" \ -e "s|{{S3_PATH}}|s3://my-bucket/path/to/logs/**/*.log.gz|g" \ scripts/load_template.sql > load_logs.sql
- Execute:
duckdb alb_analysis.duckdb < load_logs.sql
S3 Path Patterns
Use glob patterns to load multiple files:
# Single month s3://bucket/AWSLogs/account-id/elasticloadbalancing/region/2024/11/**/*.log.gz # Multiple months s3://bucket/AWSLogs/account-id/elasticloadbalancing/region/2024/*/**/*.log.gz # Specific day s3://bucket/AWSLogs/account-id/elasticloadbalancing/region/2024/11/01/**/*.log.gz
Analysis Tasks
Error Analysis
Analyze HTTP errors, status code distributions, and error patterns:
./scripts/analyze.sh errors
This provides:
- Status code distribution
- Error details (non-200 responses)
- 5xx errors by hour
- Common error reasons
Performance Analysis
Analyze response times and latency:
./scripts/analyze.sh performance
This provides:
- Response time statistics (avg, p50, p95, p99)
- Slowest requests
- Response time trends by hour
- Slow request percentage
Custom Queries
Execute custom SQL queries:
# Using a custom SQL file ./scripts/analyze.sh query my_query.sql # Or directly with DuckDB duckdb alb_analysis.duckdb
Common Analysis Patterns
Find requests from specific IP
SELECT * FROM alb_logs WHERE client_ip_port LIKE '192.168.1.%' ORDER BY timestamp DESC;
Analyze specific URL path
SELECT elb_status_code, COUNT(*) as count, ROUND(AVG(target_processing_time), 3) as avg_time FROM alb_logs WHERE request LIKE '%/api/users%' GROUP BY elb_status_code;
Traffic by time of day
SELECT EXTRACT(HOUR FROM timestamp) as hour, COUNT(*) as request_count FROM alb_logs GROUP BY hour ORDER BY hour;
Filter by date range
SELECT * FROM alb_logs WHERE timestamp BETWEEN '2024-11-01' AND '2024-11-30' AND elb_status_code >= 500;
Advanced Usage
Create aggregated summaries
CREATE TABLE daily_summary AS SELECT DATE_TRUNC('day', timestamp) as day, COUNT(*) as total_requests, SUM(CASE WHEN elb_status_code >= 500 THEN 1 ELSE 0 END) as errors_5xx, ROUND(AVG(target_processing_time), 3) as avg_response_time FROM alb_logs GROUP BY day;
Export results
-- Export to CSV COPY (SELECT * FROM alb_logs WHERE elb_status_code >= 500) TO 'errors.csv' (HEADER, DELIMITER ','); -- Export to Parquet COPY alb_logs TO 'alb_logs.parquet' (FORMAT PARQUET);
Multiple table analysis
Load logs into separate tables for comparison:
# Load last week's logs sed -e "s|{{TABLE_NAME}}|alb_logs_last_week|g" \ -e "s|{{S3_PATH}}|s3://bucket/logs/2024/10/**/*.log.gz|g" \ scripts/load_template.sql | duckdb alb_analysis.duckdb # Compare with this week SELECT 'last_week' as period, COUNT(*) as requests, AVG(target_processing_time) as avg_time FROM alb_logs_last_week UNION ALL SELECT 'this_week' as period, COUNT(*) as requests, AVG(target_processing_time) as avg_time FROM alb_logs;
Troubleshooting
S3 Access Issues
If you get "Access Denied" or credential errors when loading from S3:
Step 1: Diagnose the issue
./scripts/analyze.sh diagnose
This shows your AWS credential configuration status.
Step 2: Verify AWS credentials work
Test with AWS CLI:
aws s3 ls s3://your-bucket/path/to/logs/
If this fails, fix your AWS credentials first.
Step 3: Try different setup methods
3a. If using default AWS profile:
# Set credentials export AWS_ACCESS_KEY_ID=$(aws configure get aws_access_key_id) export AWS_SECRET_ACCESS_KEY=$(aws configure get aws_secret_access_key) export AWS_DEFAULT_REGION=$(aws configure get region) # Setup DuckDB with environment variables ./scripts/analyze.sh setup-env # Try loading again ./scripts/analyze.sh load 's3://your-bucket/path/**/*.log.gz'
3b. If using a named AWS profile:
# Check which profile you're using aws configure list-profiles # Replace 'your-profile-name' with your actual profile export AWS_PROFILE=your-profile-name export AWS_ACCESS_KEY_ID=$(aws configure get aws_access_key_id --profile your-profile-name) export AWS_SECRET_ACCESS_KEY=$(aws configure get aws_secret_access_key --profile your-profile-name) export AWS_DEFAULT_REGION=$(aws configure get region --profile your-profile-name) # Setup DuckDB with environment variables ./scripts/analyze.sh setup-env # Try loading again ./scripts/analyze.sh load 's3://your-bucket/path/**/*.log.gz'
Step 4: Alternative - Load from local files
If S3 access still doesn't work, download logs locally:
# Download logs from S3 aws s3 sync s3://your-bucket/path/to/logs/ ./local-logs/ # Modify load_template.sql to use local path sed -e "s|{{TABLE_NAME}}|alb_logs|g" \ -e "s|{{S3_PATH}}|./local-logs/**/*.log.gz|g" \ scripts/load_template.sql | duckdb alb_analysis.duckdb
"Extension aws not found"
Run setup script first:
./scripts/analyze.sh setup
Or manually:
duckdb alb_analysis.duckdb < scripts/setup.sql
"Invalid Input Error" when loading
This usually means the S3 path pattern doesn't match any files:
# Check if files exist aws s3 ls --recursive s3://your-bucket/path/to/logs/ | head # Verify the path pattern matches your bucket structure # ALB logs are typically at: # s3://bucket/AWSLogs/{account-id}/elasticloadbalancing/{region}/{year}/{month}/{day}/*.log.gz
Empty results after loading
# Check table contents duckdb alb_analysis.duckdb -c "SELECT COUNT(*) FROM alb_logs" # If 0, verify S3 path and try loading again
Out of memory
Use persistent database instead of
:memory::
# Already using persistent storage by default # alb_analysis.duckdb is a file-based database
Permission errors on scripts
chmod +x scripts/analyze.sh
Region-specific issues
Ensure the region matches your S3 bucket:
export AWS_DEFAULT_REGION=ap-northeast-1 # Change to your region ./scripts/analyze.sh setup-env
References
ALB Log Schema
See references/alb_schema.md for complete field definitions and data types.
Key fields:
: Request timestamptimestamp
: HTTP status from ALBelb_status_code
: HTTP status from targettarget_status_code
: Full HTTP request linerequest
: Response time from targettarget_processing_time
: Client address and portclient_ip_port
: Target address and porttarget_ip_port
: Error details if applicableerror_reason
,transformed_host
,transformed_uri
: Request transformation fieldsrequest_transform_status
Query Examples
See references/query_examples.md for comprehensive query examples including:
- Error analysis queries
- Performance metrics
- Traffic analysis
- SSL/TLS analysis
- Data export patterns
Scripts Reference
analyze.sh
Main analysis script with subcommands:
# Setup (uses CREDENTIAL_CHAIN) ./scripts/analyze.sh setup # Setup with environment variables (if CREDENTIAL_CHAIN doesn't work) ./scripts/analyze.sh setup-env # Diagnose S3 access and credentials ./scripts/analyze.sh diagnose # Load logs ./scripts/analyze.sh load '<s3_path>' # Analyze errors ./scripts/analyze.sh errors # Analyze performance ./scripts/analyze.sh performance # Custom query ./scripts/analyze.sh query <sql_file> # Options --db <file> # Database file (default: alb_analysis.duckdb) --table <name> # Table name (default: alb_logs)
setup_with_profile.sh (Secure - Recommended)
Securely setup DuckDB with AWS profile. Credentials are read internally and never exposed in commands:
# Usage ./scripts/setup_with_profile.sh your-profile-name # Security: Only profile name is visible, credentials read from ~/.aws/credentials
Security advantage: Credentials stay private. Only profile names appear in command history and logs.
load_with_profile.sh (Secure - Recommended)
Securely load logs with AWS profile. Credentials are read internally and never exposed in commands:
# Usage ./scripts/load_with_profile.sh your-profile-name 's3://bucket/path/**/*.log.gz' [table_name] # Security: Only profile name and S3 path are visible
Security advantage: Credentials stay private. Only profile names appear in command history and logs.
load_profile.sh (Legacy - For Manual Setup)
Helper script to load AWS credentials from a named profile into environment variables:
# Usage source scripts/load_profile.sh your-profile-name # This exports: # - AWS_PROFILE # - AWS_ACCESS_KEY_ID # - AWS_SECRET_ACCESS_KEY # - AWS_DEFAULT_REGION
Note: Must be sourced (not executed) to export variables to your current shell.
Security consideration: This exports credentials to environment variables, which may be visible in process listings. Use
setup_with_profile.sh and load_with_profile.sh for better security.
SQL Files
: Initialize DuckDB extensions with CREDENTIAL_CHAINsetup.sql
: Initialize DuckDB extensions with environment variablessetup_s3_env.sql
: Diagnose AWS credentials and S3 accessdiagnose_s3.sql
: Template for loading logs (requires variable substitution)load_template.sql
: Error analysis queriesanalyze_errors.sql
: Performance analysis queriesanalyze_performance.sql