Packages
Adds distributed tracing to AWS SDK (Boto) calls by instrumenting requests with OpenTelemetry, capturing spans for observability.
Integrates Apache Kafka with Apache Airflow, providing operators and hooks to produce and consume messages from Kafka topics as part of Airflow workflows.
Install it if you need to integrate Kafka into Airflow DAGs.
Collects and exports Prometheus metrics for Starlette and FastAPI applications, tracking request counts, response times, and concurrent request volumes with configurable labels and histogram buckets.
Install it if you run Starlette and need Prometheus metrics without writing custom instrumentation.
Automatically traces and logs OpenAI API calls (and compatible platforms like Azure OpenAI, Gemini, Groq) with OpenTelemetry, capturing request spans, token counts, and operation duration.
Integrates Apache Airflow with Oracle databases, providing operators, hooks, and sensors to orchestrate Oracle database tasks within Airflow workflows.
Install it if you need to orchestrate Oracle database work within Airflow; it is the standard integration for that use case.
Integrates Celery distributed task execution with Apache Airflow, enabling workers to process DAG tasks across a cluster using Celery as the task queue backend.
Install only if you have a Celery broker already running or planned; it is not useful without one.
Provides a Python client for querying Azure Log Analytics workspaces, though the package is no longer maintained and has been superseded by azure-monitor-query.
Detects and populates OpenTelemetry Resource attributes specific to Kubernetes pods, including container ID, pod UID, and namespace/pod name via the Kubernetes Downward API.
A lightweight Python wrapper around the Linux inotify API for monitoring file system events, implemented in pure Python with ctypes and minimal code.
Generates CloudWatch metrics embedded within structured log events, allowing you to visualize and alarm on custom metrics while preserving detailed event context for querying.
Install it if you need to publish CloudWatch metrics from Lambda or other AWS compute environments.
Provides Apache Airflow integration for executing queries and operations against JDBC-compatible databases through jaydebeapi and jpype1 bridges to Java.
The main gotcha is jpype1's platform-specific constraints; verify those match your deployment environment before committing.
Extracts Docker container metadata and populates OpenTelemetry Resource attributes automatically, enabling telemetry systems to identify and tag traces and metrics with container-specific information.
Sends telemetry data from OpenVINO toolkit components to Google Analytics with user consent, using category, action, and label parameters to structure event data.
Install only if you intend to integrate it into an OpenVINO-based tool; it is not a general-purpose analytics library.
Adds OpenTelemetry instrumentation to the Google GenAI SDK, automatically emitting trace spans, events, and metrics for GenAI operations like generate_content, embed_content, and interactions.create.
However, be aware it is experimental with known blockers to stability—review TODOS.md before production use and expect potential API or behavior changes in future…
Integrates MongoDB with Apache Airflow as a provider package, enabling DAG tasks to connect to, query, and manage MongoDB databases.
Provides a Python client library to manage SAP HANA on Azure resources through the Azure Resource Manager API.
However, verify the license terms in the repository first, since the metadata does not clarify the license treatment.
Propagates trace context in Google Cloud's X-Cloud-Trace-Context format for OpenTelemetry, enabling distributed tracing integration with Google Cloud services.
Integrates dbt Cloud with Apache Airflow, enabling orchestration of dbt Cloud jobs and data transformation workflows within Airflow DAGs.
Install it if you use both Airflow and dbt Cloud and need to orchestrate dbt jobs within Airflow workflows.
Provides a Python client library for querying Azure Application Insights data, though the package is no longer maintained and has been superseded by azure-monitor-query.
Install only if you are maintaining legacy code that cannot yet be refactored; otherwise use azure-monitor-query.
Displays nested progress bars with optional live plotting for Jupyter notebooks and console output, useful for tracking multi-level loops and training workflows.
Integrates Apache Iceberg table format with Apache Airflow, providing operators and hooks to orchestrate Iceberg data operations within Airflow workflows.
Connects OpenTelemetry tracing with Pyroscope continuous profiling, attaching profile identifiers to spans and adding trace context to profile samples.
Provides Django management commands and utilities to view, filter, cancel, and terminate active PostgreSQL queries, plus middleware for annotating queries with application context.
Integrates Apache Airflow with Datadog for monitoring, alerting, and observability of Airflow workflows and tasks.
Install it if you run Airflow and use Datadog for observability and need to integrate the two platforms.
Converts tqdm progress bars to logging-friendly messages in headless environments, automatically switching from interactive terminal output to structured log lines when stdout is unavailable.
Adds distributed tracing to aiohttp server applications by instrumenting HTTP requests with OpenTelemetry, capturing request/response metadata for observability.
Exports metrics from OpenTelemetry Python SDK directly to Prometheus Remote Write backends without running a Prometheus server.
Adds distributed tracing instrumentation to the click CLI library, automatically capturing command execution as spans in OpenTelemetry traces.
Perfetto is a Python binding for Perfetto's trace processor, allowing programmatic access to system and application traces via SQL queries and trace analysis APIs.
Extracts process-level metadata and populates OpenTelemetry Resource objects with process attributes for use in tracing and observability pipelines.
Provides an OpenTelemetry distribution that automatically detects and configures container environment attributes for Docker and Kubernetes deployments.
Sends exceptions, errors, and log messages to Rollbar's error monitoring platform for real-time tracking and aggregation.
Install it if you want centralized error tracking and real-time alerting; skip it if you prefer self-hosted or alternative error monitoring solutions.
Measures GIL contention within a specific code block by spawning a monitoring thread that periodically attempts to re-acquire the GIL and records acquisition latency as a contention metric.
However, verify the license status before use in proprietary projects, and be aware that the project is aging (300 days since last release) with modest maintenance…
Luigi is a Python workflow orchestration framework that builds and manages complex pipelines of batch jobs, handling dependency resolution, task scheduling, failure recovery, and visualization.
Install it if you need workflow orchestration; skip it if your tasks are simple, one-off scripts.
Provides Redis integration for Apache Airflow, enabling workflows to interact with Redis for caching, messaging, and state management through Airflow operators and hooks.
Install it if you need to integrate Airflow workflows with Redis for caching, messaging, or state management.
Integrates Apache Spark with Apache Airflow, enabling you to orchestrate and monitor Spark jobs as part of Airflow workflows.
Install it if you run Airflow and need to orchestrate Spark jobs as part of your DAGs.
Integrates PagerDuty incident management with Apache Airflow workflows, enabling DAGs to trigger alerts, create incidents, and manage on-call notifications.
Install it if you run Airflow and need to route alerts or incidents to PagerDuty; skip it if you don't use PagerDuty or don't need Airflow-to-PagerDuty automation.
Phoenix Client provides a Python interface to the Phoenix observability platform's REST API, enabling programmatic management of datasets, experiments, traces, prompts, and feedback for LLM applications.
Install it if you are already running a Phoenix instance and need programmatic access to its API from Python; it is purpose-built for that workflow.
Manhole installs an in-process debugging service that listens on a Unix domain socket, allowing you to connect and inspect thread stacktraces or drop into an interactive Python shell within a running process.
Displays real-time NVIDIA GPU status, memory usage, temperature, and running processes in a command-line interface, similar to nvidia-smi but with a simpler output format.