Packages
Provides in-process context propagation for OpenCensus, automatically managing thread-local and async context across Python execution flows.
Adds distributed tracing to Redis client calls by instrumenting the Redis library to emit OpenTelemetry spans for each request.
Integrates Apache Airflow with Snowflake, providing operators, hooks, and sensors to orchestrate Snowflake queries, data transfers, and warehouse operations within Airflow DAGs.
Install it if you use Airflow and need to orchestrate Snowflake workloads.
Integrates Apache Airflow with Databricks, providing operators and hooks to orchestrate Databricks jobs, SQL queries, and data workflows within Airflow DAGs.
Install only if you have an existing Airflow deployment and Databricks workspace to connect.
Records and sends trace data from Python applications to AWS X-Ray for distributed tracing and performance monitoring.
However, do not start new projects with it: AWS is transitioning to OpenTelemetry as the standard.
Provides HTTP operators, hooks, and sensors for Apache Airflow to make HTTP requests and integrate with HTTP-based services in data pipelines.
Install it if you need to make HTTP requests or call REST APIs from Airflow workflows.
Apache Airflow is a platform for programmatically authoring, scheduling, and monitoring workflows defined as code (DAGs), with a scheduler that executes tasks on workers while respecting dependencies.
Install it if you need to programmatically define, schedule, and monitor workflows at scale; avoid it if you need only simple cron-like scheduling or one-off task…
Integrates Apache Airflow with Google Cloud services (BigQuery, Cloud Storage, Pub/Sub, Dataflow, AI Platform, and others) and Google Workspace, Ads, Analytics, and Firebase through provider operators and hooks.
Bundles OpenTelemetry SDK and Azure Monitor exporters to instrument Python applications for automatic collection and reporting of traces, metrics, and logs to Azure Monitor with a single configuration call.
Provides logging integrations for spaCy model training, supporting Weights & Biases, MLflow, ClearML, PyTorch, and CuPy as alternate loggers decoupled from the core library.
Provides compatibility code and utilities for Apache Airflow to support code across multiple Airflow versions, abstracting version-specific API differences.
progressbar2 renders text-based progress bars in the terminal, handling custom widgets, concurrent bars, unknown-length progress, and clean output around logs and prints.
Adds automatic tracing and monitoring to gRPC Python client and server calls through OpenTelemetry interceptors, capturing request/response metadata and performance metrics.
Automatically detects and reports GCP resource metadata (GCE, GKE, etc.) to OpenTelemetry, enabling observability tools to understand the cloud environment where your application runs.
Manually creates traces for LLM applications using Aliyun's tracing infrastructure, integrating with OpenTelemetry for standardized observability.
However, the 420-day maintenance gap warrants checking that it remains compatible with your OpenTelemetry version and Aliyun ARMS API before committing to production…
Provides standardized semantic convention definitions for Aliyun tracing and observability, defining field names and types for structured logging and distributed tracing in Aliyun services.
However, verify that the semantic conventions it defines (last updated 519 days ago) match your target Aliyun specification version, as the long release gap suggests…
Provides SSH integration for Apache Airflow, enabling tasks to execute commands on remote servers over secure shell connections.
Install it if you run Apache Airflow and need to execute commands on remote servers via SSH.
Integrates Azure SDK clients with OpenTelemetry to emit distributed tracing spans for observability and monitoring of Azure service calls.
Adds Prometheus metrics collection and exposure to FastAPI applications with minimal setup, tracking HTTP request counts, sizes, durations, and custom metrics.
Provides OpenTelemetry resource detectors that automatically identify and tag telemetry data with Azure environment metadata from App Service, Functions, and Virtual Machines.
Integrates Apache Airflow with MySQL databases, providing operators, hooks, and sensors to query, execute, and monitor MySQL tasks within Airflow workflows.
Install it if you need to orchestrate MySQL tasks within Airflow.
Integrates IMAP email protocol support into Apache Airflow, enabling workflows to connect to and interact with IMAP mail servers.
Install only if you have Airflow >=2.11.0 already running and a genuine need for IMAP connectivity.
Provides FTP integration for Apache Airflow, enabling workflows to connect to and interact with FTP servers as part of data pipeline orchestration.
Install only if you have an existing Airflow deployment and require FTP operations; it is not a standalone tool.
Integrates SQLite databases with Apache Airflow as a provider package, enabling SQLite connection management and SQL task execution within Airflow workflows.
Install only if you have an existing Airflow deployment meeting version >=2.11.0.
Represents and manipulates IPv4, IPv6, MAC addresses and related network objects; supports CIDR notation, subnetting, set operations, IANA lookups, and DNS reverse generation.
Adds SMTP email sending capabilities to Apache Airflow workflows, enabling tasks to send messages through Simple Mail Transfer Protocol.
Install it if you need to send email from Airflow tasks and have an SMTP server available.
Integrates Apache Airflow with Kubernetes, enabling orchestration of containerized workloads and cluster operations through Airflow DAGs.
Install it if you run Airflow and need to orchestrate Kubernetes workloads.
Adds distributed tracing to AWS SDK calls made through botocore and aiobotocore, capturing request/response telemetry for services like DynamoDB, Lambda, SNS, SQS, and Bedrock Runtime.
Supervisor is a client/server system that monitors and controls multiple processes on UNIX-like operating systems, allowing you to start, stop, and restart them from a central management interface.
Collects system performance metrics (CPU, memory, disk, network) and exports them via OpenTelemetry for observability and monitoring.
RQ is a Python library for queueing jobs and processing them in the background with workers, backed by Redis or Valkey. It handles job scheduling, prioritization, retries, and webhooks with a simple API.
Injects and extracts AWS X-Ray tracing context into OpenTelemetry spans, enabling trace propagation across AWS services.
Install it if you are using OpenTelemetry in an AWS environment and need X-Ray trace propagation.
Exports OpenTelemetry traces to Google Cloud Trace for distributed tracing and observability in GCP environments.
Install it if you are already committed to this exporter or migrating gradually; for new projects, consider using standard OTLP exporters instead per the migration…
Exports logs, metrics, and traces from Python applications to Azure Monitor using the OpenCensus instrumentation framework.
Adds distributed tracing and observability to Celery task queues via OpenTelemetry, capturing task execution spans and metrics across your task processing pipeline.
Install it if you already use or plan to use OpenTelemetry for tracing; skip it if you have no tracing infrastructure in place or use a different observability tool…
A Python decorator that implements the Circuit Breaker pattern to prevent cascading failures in distributed systems by monitoring function calls, counting failures, and stopping execution after a threshold is reached.
Executes read-only queries against Azure Monitor's Logs data platform using the Kusto Query Language, supporting both synchronous and asynchronous clients.
Install it if you need to query Azure Monitor logs from Python.
Integrates Apache Airflow with Slack, enabling workflows to send messages and notifications to Slack channels via the Slack API and incoming webhooks.
Provides common I/O utilities and operators for Apache Airflow workflows, enabling standardized file and data handling across Airflow DAGs and provider integrations.
Sends telemetry events, metrics, and traces to Azure Application Insights for application monitoring and diagnostics.