infinity-observability-sdk 0.5.2

Unified observability SDK for Infinity Constellation services — tracing, structured logging, error tracking.

Infinity Observability SDK

Unified observability for Infinity Constellation services — OTel tracing, structured logging, and optional error tracking in a single configure_observability() call.

Installation

pip install infinity-observability-sdk

Optional extras:

pip install infinity-observability-sdk[sentry]    # Sentry error tracking
pip install infinity-observability-sdk[logfire]   # pydantic-ai / httpx auto-instrumentation
pip install infinity-observability-sdk[django]    # Django OTel auto-instrumentation

Quick start

from infinity_observability_sdk import configure_observability, ObservabilityConfig

configure_observability(ObservabilityConfig(
    business_unit_name="my_bu",
    service_name="my_service",
))

Set the required environment variables before calling configure_observability:

Variable	Description
INFINITY_OBSERVABILITY_ENDPOINT	OTLP collector endpoint (e.g. https://collector.example.com)
INFINITY_OBSERVABILITY_API_KEY	API key for collector authentication
ENVIRONMENT	Deployment environment — controls log format. development → human-readable console output; anything else → JSON. Defaults to production.

Configuration

ObservabilityConfig(
    business_unit_name="my_bu",       # required
    service_name="my_service",        # required

    # Integrations
    instrument_pydantic_ai=True,      # default: True
    instrument_httpx=True,            # default: True
    sentry_dsn=None,                  # optional — enables Sentry if set
    sentry_environment=None,          # falls back to ENVIRONMENT env var
    sentry_traces_sample_rate=0.0,    # 0.0–1.0, default: 0.0

    # Logging
    log_level="INFO",                 # DEBUG | INFO | WARNING | ERROR | CRITICAL

    # Advanced
    additional_resource_attributes={},  # extra OTel resource attributes
)

configure_observability() is idempotent — safe to call multiple times; subsequent calls are no-ops.

Agent context

Wrap AI agent runs to emit a structured span with cost and identity metadata:

from infinity_observability_sdk import agent_context

with agent_context(
    agent_employee_equivalent="data_engineer",
    hourly_rate=75.0,
    agent_name="my_agent",
    task_description="summarise quarterly report",
    task_instance_identifier="run-abc-123",
    approximate_person_hours=2.0,
    business_unit_name="my_bu",
    service_name="my_service",
) as span:
    # your agent logic here
    ...

Extra keyword arguments are forwarded as span attributes.

Django integration

Call instrument_django() before the ASGI/WSGI app is loaded — typically at the top of core/asgi.py:

from infinity_observability_sdk import configure_observability, ObservabilityConfig, instrument_django

configure_observability(ObservabilityConfig(
    business_unit_name="my_bu",
    service_name="my_api",
))
instrument_django()

Requires infinity-observability-sdk[django].

Standalone logging

For services that only need structured logging without full OTel tracing:

from infinity_observability_sdk import configure_logging

configure_logging(service_name="my_bu.my_service", log_level="INFO")

Development

uv sync --dev   # install all dependencies
make test       # run tests
make lint       # ruff lint
make ci         # full CI suite (lint, format check, tests, build, package check)

Release cycle

Releases are fully automated via python-semantic-release on every merge to main. No manual version bumps or GitHub Releases are needed.

How it works

1. Every merge to main triggers the release workflow, which first runs the full CI suite (lint, format, tests, build).
2. python-semantic-release analyses commit messages since the last release using Conventional Commits to determine whether a release is warranted and what the version bump should be.
3. If a release is warranted, it updates the version in pyproject.toml, creates a vX.Y.Z tag, and publishes a GitHub Release with generated release notes.
4. The GitHub Release triggers the deploy workflow, which builds the package and publishes to PyPI via OIDC (no stored secrets).

Version bump rules

Commit type	Example	Bump
fix:, perf:	fix(sdk): handle missing env var	patch
feat:	feat(sdk): add configure_metrics()	minor
feat!: or BREAKING CHANGE: footer	feat(sdk)!: remove logfire hard dep	major
docs:, chore:, refactor:, etc.	docs: update README	none

While the version is 0.x, breaking changes produce a minor bump rather than jumping to 1.0.0.

Commit message format

<type>(<scope>): <short summary>

[optional body]

[optional footer]

All commit messages merged to main should follow this format. PR titles are used as the squash-merge commit message and must follow the same convention.