ls-infra 0.1.1

Infrastructure management tool

ls-infra

ls-infra is a framework for collecting cloud infrastructure information and transforming it into useful formats. Its extensible design allows users to easily add support for new cloud providers and output formats.

Core Concepts

ls-infra operates in three distinct stages:

1. Collection Each collector must implement two methods to standardize how data is gathered:

fetch_raw_data: Retrieves raw data from the provider serialize: Transforms the raw data into the standardized format required by the formatter

2. Pipeline Processing Services that process the standardized data:

Run sequentially in the order defined Can target specific provider data or all data using the target property Transform, filter, or enrich the data

3. Formatting Takes all processed data and generates the final output. The formatter effectively dictates the required data format that collectors must serialize to. Flow Definition A flow is defined in YAML and describes the complete data processing pipeline: yamlCopyversion: "1.0" metadata: name: example_flow description: "Flow description"

collect: aws: service: aws_instance_collector enabled: true config: regions: ["us-east-1"]

alicloud: service: alicloud_instance_collector enabled: true config: regions: ["cn-beijing"]

pipelines:

• service: filter_terminated target: all config: states: ["terminated"]

• service: filter_vpc target: aws config: vpc_ids: ["vpc-123"]

format: service: generate_inventory_ansible config: group_by: ["Environment"] Flow Execution

Collection Phase (Parallel):

Collectors run in parallel Each collector:

Fetches raw data Transforms to standard format

Results are aggregated

Pipeline Phase (Sequential):

Services run in defined order Each service processes based on target:

target: all - processes all data target: provider - processes specific provider data

Format Phase:

Takes all processed data Generates final output

Key Design Points

Collection Standardization:

Collectors handle both fetching and transformation Raw provider data is immediately standardized Format is dictated by formatter needs

Pipeline Flexibility:

Services can target all or specific data Sequential processing ensures data consistency Common operations can be applied to all data

Extensibility:

New collectors can be added for different providers Pipeline services can be created for custom needs Formatters can be developed for different outputs

Development Guidelines Collectors Must implement:

fetch_raw_data: Provider-specific retrieval serialize: Standardization to formatter requirements

Pipeline Services Should:

Accept standardized data format Clearly define their target scope Maintain data format compatibility

Formatters Should:

Define their expected data format Provide clear configuration options Handle partial or failed data gracefully

CLI Usage bashCopy# Run a flow ls-infra run -f flow.yml

Validate flow

ls-infra validate -f flow.yml

List available services

ls-infra list-services

Initialize new flow

ls-infra init Environment Variables The framework supports environment variable substitution:

${VAR_NAME}: Simple substitution ${VAR_NAME:-default}: With default value

Security Considerations

Credential Management:

Use environment variables for sensitive data Support cloud provider credential chains Never log sensitive information

Input Validation:

Validate all configuration Sanitize input data Verify service permissions

Error Handling

Collection Errors:

Failed collectors don't halt entire process Proper error reporting Retry mechanisms for transient failures

Pipeline Errors:

Configurable failure behavior (fail/warn) Clear error messages Data validation between services

Formatter Errors:

Validate input data Clear error reporting Partial output on failures when possible

Future Plans

• Implement plugin system architecture
• Move default plugins to separate repository for better maintainability
• Allow third-party plugin development and integration