Integrate OpenTelemetry and OpenObserve Monitoring#291
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📝 WalkthroughWalkthroughAdds OpenTelemetry initialization early in application entry points, conditionally integrates an OTEL logging handler into Django settings, documents an OTEL endpoint in example.env, adds an example docker-compose override with observability settings, updates Changes
Sequence DiagramsequenceDiagram
participant Entry as Application Entry<br/>(manage.py / asgi.py)
participant Telemetry as OpenTelemetry Setup
participant Django as Django Settings & App
participant Logging as Django Logging Config
participant Collector as OTLP Collector
Entry->>Telemetry: setup_opentelemetry()
Telemetry->>Collector: configure exporter (OTEL_EXPORTER_OTLP_ENDPOINT)
Telemetry-->>Entry: telemetry initialized
Entry->>Django: set DJANGO_SETTINGS_MODULE / import settings
Django->>Logging: load LOGGING config
alt telemetry active
Logging->>Telemetry: add_otel_logging_handler(LOGGING)
Telemetry->>Collector: route logs/traces
end
Django-->>Entry: application ready
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~18 minutes Possibly related PRs
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Summary of ChangesHello @samuelvkwong, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the application's observability by integrating OpenTelemetry for automatic instrumentation and OpenObserve for centralized monitoring. It establishes a robust pipeline for collecting and visualizing traces, metrics, and logs, which will provide invaluable insights into application performance, aid in debugging, and facilitate proactive issue identification. Highlights
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Pull Request Review: OpenTelemetry and OpenObserve IntegrationGreat work integrating observability into ADIT! This is a solid foundation for monitoring production deployments. Here's my detailed review: ✅ Strengths
🔴 Critical Issues1. Security: Hardcoded Credentials in example.envLocation: The example file contains a hardcoded Basic Auth header with default credentials: OPENOBSERVE_AUTH_HEADER="Basic YWRtaW5AbG9jYWxob3N0LmNvbTphZG1pbg=="Issues:
Recommendation:
# OPENOBSERVE_AUTH_HEADER - Basic auth header for OpenObserve (base64 of "email:password")
# Generate with: echo -n "YOUR_EMAIL:YOUR_PASSWORD" | base64
# IMPORTANT: Change default credentials in production!
OPENOBSERVE_AUTH_HEADER="" # Set this after generating with command above2. Security: Docker Socket Access with Root PrivilegesLocation: The otel-collector runs as root ( user: "0:0" # Needed to read Docker container log files
volumes:
- /var/run/docker.sock:/var/run/docker.sock:roIssues:
Recommendations:
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Code Review
This pull request integrates OpenTelemetry for tracing and metrics, and OpenObserve for monitoring, setting up a new telemetry module and Docker services. While the Python instrumentation is well-structured, critical security vulnerabilities exist in the infrastructure configuration. The otel-collector runs as root with excessive privileges and mounts the host's Docker socket, creating a significant attack surface. Additionally, insecure: true in the OTLP exporter disables TLS verification, exposing sensitive telemetry data and credentials to Man-in-the-Middle attacks. It is imperative to address these security concerns. Further suggestions include making telemetry initialization thread-safe, simplifying log filters, and acknowledging the use of beta packages for improved robustness and maintainability.
| ENVIRONMENT: ${ENVIRONMENT:-development} | ||
| volumes: | ||
| - /var/lib/docker/containers:/var/lib/docker/containers:ro | ||
| - /var/run/docker.sock:/var/run/docker.sock:ro |
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Mounting the Docker socket (/var/run/docker.sock) into a container is a significant security risk. It allows the container to communicate with the Docker daemon, which can lead to full host compromise or privilege escalation, even when mounted as read-only. The current otel-collector-config.yaml does not appear to use any components (like the docker_observer extension) that require access to the Docker socket; it instead parses container IDs directly from log file paths. Following the principle of least privilege, this mount should be removed.
| otel-collector: | ||
| image: otel/opentelemetry-collector-contrib:0.115.1 | ||
| hostname: otel-collector.local | ||
| user: "0:0" # Needed to read Docker container log files |
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Running the otel-collector container as root (user: "0:0") significantly increases the attack surface and potential impact of a container breakout. While the comment suggests this is for reading Docker container logs, it is much safer to run the process as a non-root user and grant only the specific permissions required to read logs (e.g., by adding the user to the group that owns the log files). This avoids a privilege escalation vector if the collector is compromised.
| headers: | ||
| Authorization: ${env:OPENOBSERVE_AUTH_HEADER} | ||
| tls: | ||
| insecure: true |
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Setting insecure: true in the TLS configuration for the OTLP exporter disables certificate verification. This is a critical vulnerability that exposes telemetry data and sensitive Authorization headers to Man-in-the-Middle (MITM) attacks, especially if OPENOBSERVE_ENDPOINT uses HTTPS. It is strongly recommended to use secure connections (HTTPS) with proper certificate verification, particularly when transmitting authentication credentials, rather than relying on insecure: true even for local development.
| """ | ||
| global _telemetry_initialized | ||
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||
| if _telemetry_initialized: |
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The current implementation to ensure setup_opentelemetry runs only once is not thread-safe. While this is unlikely to be an issue in the current Django startup process, it could lead to race conditions if the application startup becomes multi-threaded in the future. A double-checked locking pattern using threading.Lock would make this more robust.
For example:
import threading
_telemetry_lock = threading.Lock()
_telemetry_initialized = False
def setup_opentelemetry():
global _telemetry_initialized
if _telemetry_initialized:
return
with _telemetry_lock:
if _telemetry_initialized:
return
# ... initialization logic ...
_telemetry_initialized = True| "opentelemetry-instrumentation-django>=0.60b0", | ||
| "opentelemetry-instrumentation-psycopg>=0.60b0", |
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The OpenTelemetry instrumentation packages for Django and Psycopg are specified as beta versions (>=0.60b0). While this might be necessary to get the latest features, using beta software in production can be risky due to potential bugs or breaking changes in future releases. It would be beneficial to monitor these packages for stable releases and plan to upgrade when they become available.
…ocker logs not as clean, requires json output formatting and filter workaround to link logs to traces/spans.
Pull Request Review: OpenTelemetry and OpenObserve IntegrationThank you for implementing observability infrastructure for ADIT! This is a valuable addition that will help with monitoring and debugging. Here's my comprehensive review: ✅ Strengths
🔍 Issues & RecommendationsCritical Issues1. Private API Usage (adit/telemetry.py:42)```python Problem: Importing from `_logs` and `_log_exporter` (private modules with leading underscores) is not guaranteed to be stable across OpenTelemetry versions. Recommendation: Check if there's a public API alternative. If not, add a comment explaining why private APIs are necessary and pin OpenTelemetry versions more strictly. 2. Hardcoded Default Credentials in example.env (example.env:113, 125)```env Problem: While this is an example file for development, having `admin`/`admin` credentials could lead to:
Recommendations:
3. Missing Graceful Shutdown (adit/telemetry.py)Problem: OpenTelemetry providers should be shut down gracefully to flush pending telemetry data. Currently, there's no shutdown hook. Recommendation: Add shutdown logic, possibly using Django's `django.core.signals.request_finished` or ASGI lifespan events: High Priority Issues4. Debug Log Level for Production (adit/settings/base.py:36)```python Problem: DEBUG level in production will create excessive log volume and performance overhead. Recommendation: Make log level configurable: 5. Insecure TLS Configuration (otel-collector-config.yaml:40-41)```yaml Problem: This disables TLS certificate verification, making the connection vulnerable to MITM attacks. Recommendation:
6. No Error Handling in setup_opentelemetry() (adit/telemetry.py:19-89)Problem: If OpenTelemetry initialization fails (network issues, invalid config, etc.), the entire application startup could fail. Recommendation: Wrap the setup in try/except and log errors without crashing: Medium Priority Issues7. No TestsProblem: No test coverage for the new telemetry module. Recommendation: Add tests to verify:
8. Hard-Coded Metric Export Interval (adit/telemetry.py:72)```python Recommendation: Make this configurable via environment variable: 9. Docker Compose Service Dependencies (docker-compose.base.yml:198-204)Observation: The app services don't explicitly depend on `otel-collector` or `openobserve`. Impact: If otel-collector isn't ready when the app starts, telemetry data may be lost during startup. Recommendation: Add `depends_on` with health checks: And add a health check to otel-collector service (it already has health_check endpoint on 13133). 10. Whitespace Change in manage.py (manage.py:9)Observation: Line 264 removes a blank line after the docstring. Recommendation: This is cosmetic but inconsistent with the rest of the file. Consider keeping the original formatting. Low Priority / Suggestions11. Missing OTEL_SERVICE_NAME DocumentationThe code uses `OTEL_SERVICE_NAME` (telemetry.py:55) but it's not documented in `example.env` or CLAUDE.md. Recommendation: Add to `example.env`: Optional: Override service name in telemetry (defaults to hostname)OTEL_SERVICE_NAME=adit-web``` 12. OpenObserve Image Version Not Pinned (docker-compose.base.yml:185)```yaml Recommendation: Pin to a specific version for reproducibility: 📊 Performance Considerations
🔐 Security Summary
📝 Documentation NeedsThe PR description mentions TODO items:
Recommendations:
✅ Testing ChecklistBefore merging, please verify:
🎯 RecommendationThis is a solid foundation for observability in ADIT. The architecture is sound and follows OpenTelemetry best practices. However, there are several critical security and stability issues that should be addressed before merging: Must Fix Before Merge:
Should Fix Before Merge: Can Address in Follow-up PRs:
Overall: Request Changes - The implementation is good but needs security and error handling improvements before production use. |
Code Review: OpenTelemetry and OpenObserve IntegrationThank you for this comprehensive telemetry implementation! This is a well-structured addition that integrates OpenTelemetry instrumentation with OpenObserve observability. Below is my detailed review: ✅ Strengths
🔴 Critical Issues1. Potential Circular Import / Initialization Timing Issue (
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Pull Request Review: OpenTelemetry and OpenObserve IntegrationThanks for adding observability to ADIT! This is a valuable addition for monitoring production systems. Here's my detailed feedback: 🎯 Overall AssessmentSummary: This PR adds comprehensive OpenTelemetry instrumentation with traces, metrics, and logs exported to OpenObserve via an otel-collector. The implementation is well-structured and follows good practices for optional telemetry. Status: ✅ Good foundation with some recommendations for improvement ✅ Strengths
🔍 Code Quality Issues1. Security: Hardcoded credentials in example.env
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Replace the local adit/telemetry.py module with the shared telemetry module from adit-radis-shared. Remove the direct opentelemetry-* dependencies from pyproject.toml since they are now provided transitively via adit-radis-shared. Update the adit-radis-shared dependency to point to the openobserve branch. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
PR Review: OpenTelemetry and OpenObserve IntegrationThanks for working on this observability integration! The overall implementation looks solid and follows a clean architecture. Here's my detailed feedback: Strengths
Code Quality & Best PracticesGood:
Consider:
Potential Issues
Security Concerns
Performance Considerations
Test CoverageMissing:
Recommendations:
Documentation Gaps
Actionable RecommendationsBefore merge:
Can be addressed in follow-up: SummaryThis is a well-structured implementation that brings valuable observability to ADIT. The main blocker is the branch dependency in pyproject.toml. Security and testing gaps can be addressed in follow-up work, but should be prioritized before production use. Great work overall! |
Pull Request Review: OpenTelemetry and OpenObserve IntegrationThis PR adds comprehensive observability to ADIT using OpenTelemetry and OpenObserve. Overall, the implementation is solid and follows good practices, but there are several areas that need attention before merging. ✅ Strengths
🔴 Critical Issues1. Dependency on Unmerged BranchLocation: Issue: The dependency points to a feature branch (
Recommendation:
2. Missing Required Environment Variable ValidationLocation: Issue: Recommendation: Use 3. Security: Hardcoded Credentials in Example FileLocation: Issue: The base64-encoded auth header Recommendation: Add prominent security warnings emphasizing these are ONLY for local development and MUST be changed for production.
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Pull Request Review: OpenTelemetry and OpenObserve IntegrationSummaryThis PR adds comprehensive observability to ADIT by integrating OpenTelemetry instrumentation with OpenObserve as the backend. The implementation follows a standard OTLP collector pattern with Django/psycopg instrumentation. Code QualityPositive Aspects ✅
Issues and Concerns
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| Issue | Severity | Status |
|---|---|---|
| Weak default credentials | High | Needs documentation |
| TLS disabled | Medium | Acceptable for dev |
| No credential validation | Medium | Should add |
| Unversioned dependency | High | Blocks merge |
Verdict
This is a solid foundation for observability, but has blocking issues that must be addressed before merge:
Must Fix Before Merge 🚫
- Pin adit-radis-shared to a released version
- Add error handling around telemetry initialization
- Add basic integration tests
- Document security considerations for production use
- Resolve or document TODOs in PR description
Should Fix (Nice to Have) 💡
- Add resource limits to services
- Improve log filter regex efficiency
- Add OpenObserve data retention configuration
- Create follow-up issue for TLS in production
Testing Checklist
- uv run cli compose-up -- --watch starts all services
- Application remains functional if OpenObserve is down
- OpenObserve UI is accessible and receiving telemetry
- Health checks and static files are not traced
- No PII/sensitive data in logs
- Tests pass: uv run cli test
Great work on adding observability! The architecture is sound. Once the blocking issues are resolved, this will be a valuable addition to ADIT.
Remove OpenObserve and OTel collector services from ADIT's Docker Compose stack. Telemetry is now sent directly to the centralized collector via OTEL_EXPORTER_OTLP_ENDPOINT. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove the OTLP endpoint mapping from docker-compose.base.yml since the observability stack is now centralized in openradx-observability. Add docker-compose.observability.yml.example as an opt-in overlay and ignore the active copy in .gitignore. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Use ${OTEL_EXPORTER_OTLP_ENDPOINT} from .env instead of hardcoding
the collector address in the compose overlay.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Point OTEL_EXPORTER_OTLP_ENDPOINT to the collector on the shared openradx-observability network instead of host.docker.internal. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Actionable comments posted: 1
🧹 Nitpick comments (2)
pyproject.toml (1)
10-10: Consider pinningadit-radis-sharedto an immutable ref inpyproject.tomlfor clarity.The
pyproject.tomlcurrently references the moving branch@openobserve, but theuv.lockfile already pins the dependency to commita945c9d93841fc6c376df7aec78550fec1715b93, so builds are currently reproducible. However, regenerating the lockfile could resolve to a different commit if the branch advances. For better clarity and to prevent unexpected updates, consider pinning to a specific commit SHA or release tag directly inpyproject.toml.🔧 Suggested change
- "adit-radis-shared @ git+https://github.com/openradx/adit-radis-shared.git@openobserve", + "adit-radis-shared @ git+https://github.com/openradx/adit-radis-shared.git@a945c9d93841fc6c376df7aec78550fec1715b93",🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@pyproject.toml` at line 10, The dependency line "adit-radis-shared @ git+https://github.com/openradx/adit-radis-shared.git@openobserve" references a moving branch; pin it to the immutable commit SHA present in uv.lock (a945c9d93841fc6c376df7aec78550fec1715b93) or to a release tag instead. Edit the pyproject.toml entry for adit-radis-shared to use the commit SHA (or tag) after the @, so the declared VCS dependency matches the locked commit and prevents unexpected updates; then regenerate and verify the lockfile if needed.docker-compose.observability.yml.example (1)
8-10: Document the external network prerequisite for the observability overlay.The
openradx-observabilitynetwork at lines 9-10 is defined withexternal: true, requiring it to already exist on the Docker host. This prerequisite is not documented in the repository. Whileexample.envreferences setup instructions via an external GitHub repository link, the docker-compose file itself contains no inline documentation or comments explaining this dependency. First-time users attempting to usedocker-compose.observability.yml.examplewill encounter a failure without pre-creating this network. Add a comment to the file or update documentation to clarify the required setup step.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@docker-compose.observability.yml.example` around lines 8 - 10, The observability compose defines an external network `openradx-observability` which must be created on the Docker host beforehand; update `docker-compose.observability.yml.example` to add an inline comment immediately above the `networks: openradx-observability:` block explaining this prerequisite and include the exact command to create it (e.g., `docker network create openradx-observability`), or alternatively add the same note and command to the repository README or docs so first-time users know to pre-create the `openradx-observability` network before running the compose file.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@docker-compose.observability.yml.example`:
- Line 6: The environment variable OTEL_EXPORTER_OTLP_ENDPOINT is being set with
an explicit empty default using ${OTEL_EXPORTER_OTLP_ENDPOINT:-}, which forces
an empty string and overrides OTEL SDK defaults; change the docker-compose
variable to use the uninterpolated form ${OTEL_EXPORTER_OTLP_ENDPOINT} so the
variable stays unset when not provided, allowing the OTEL SDK to apply its own
defaults or fail as intended—update the OTEL_EXPORTER_OTLP_ENDPOINT entry
accordingly.
---
Nitpick comments:
In `@docker-compose.observability.yml.example`:
- Around line 8-10: The observability compose defines an external network
`openradx-observability` which must be created on the Docker host beforehand;
update `docker-compose.observability.yml.example` to add an inline comment
immediately above the `networks: openradx-observability:` block explaining this
prerequisite and include the exact command to create it (e.g., `docker network
create openradx-observability`), or alternatively add the same note and command
to the repository README or docs so first-time users know to pre-create the
`openradx-observability` network before running the compose file.
In `@pyproject.toml`:
- Line 10: The dependency line "adit-radis-shared @
git+https://github.com/openradx/adit-radis-shared.git@openobserve" references a
moving branch; pin it to the immutable commit SHA present in uv.lock
(a945c9d93841fc6c376df7aec78550fec1715b93) or to a release tag instead. Edit the
pyproject.toml entry for adit-radis-shared to use the commit SHA (or tag) after
the @, so the declared VCS dependency matches the locked commit and prevents
unexpected updates; then regenerate and verify the lockfile if needed.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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Review profile: CHILL
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uv.lockis excluded by!**/*.lock
📒 Files selected for processing (9)
.gitignoreadit/asgi.pyadit/settings/base.pydocker-compose.base.ymldocker-compose.dev.ymldocker-compose.observability.yml.exampleexample.envmanage.pypyproject.toml
| - default | ||
| - openradx-observability | ||
| environment: | ||
| OTEL_EXPORTER_OTLP_ENDPOINT: ${OTEL_EXPORTER_OTLP_ENDPOINT:-} |
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🧩 Analysis chain
🌐 Web query:
In Docker Compose variable interpolation, does ${VAR:-} set an empty string value when VAR is unset, and can that override application defaults compared to leaving VAR unset?
💡 Result:
Yes, in Docker Compose variable interpolation, ${VAR:-} sets an empty string value when VAR is unset (or empty). This explicitly passes an empty string to the container environment if used in the environment: section (e.g., environment: MY_VAR: ${MY_VAR:-}), which overrides any application defaults inside the container that might otherwise apply if the variable were truly unset. Leaving VAR unset in the Compose file (e.g., environment: - MY_VAR without interpolation or no entry) results in the variable not being set in the container environment at all, preserving application defaults.
Citations:
- 1: https://compose-spec.github.io/compose-spec/12-interpolation.html
- 2: https://docs.docker.com/compose/how-tos/environment-variables/variable-interpolation/
- 3: https://stackoverflow.com/questions/76976352/how-to-unset-environment-variable-for-a-container-if-its-not-set-on-host-with-d
- 4: https://docs.docker.com/compose/environment-variables/variable-interpolation/
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Use uninterpolated variable syntax to preserve OTEL SDK defaults when endpoint is not configured.
At line 6, ${OTEL_EXPORTER_OTLP_ENDPOINT:-} explicitly sets an empty string when the variable is unset, which overrides any OTEL SDK defaults and can result in the exporter being silently disabled. Since this is an example file that users customize via environment variables, use ${OTEL_EXPORTER_OTLP_ENDPOINT} instead to leave the variable unset when not configured, allowing the SDK to apply its defaults or fail fast if the variable is required.
Proposed fix
- OTEL_EXPORTER_OTLP_ENDPOINT: ${OTEL_EXPORTER_OTLP_ENDPOINT:-}
+ OTEL_EXPORTER_OTLP_ENDPOINT: ${OTEL_EXPORTER_OTLP_ENDPOINT}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| OTEL_EXPORTER_OTLP_ENDPOINT: ${OTEL_EXPORTER_OTLP_ENDPOINT:-} | |
| OTEL_EXPORTER_OTLP_ENDPOINT: ${OTEL_EXPORTER_OTLP_ENDPOINT} |
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@docker-compose.observability.yml.example` at line 6, The environment variable
OTEL_EXPORTER_OTLP_ENDPOINT is being set with an explicit empty default using
${OTEL_EXPORTER_OTLP_ENDPOINT:-}, which forces an empty string and overrides
OTEL SDK defaults; change the docker-compose variable to use the uninterpolated
form ${OTEL_EXPORTER_OTLP_ENDPOINT} so the variable stays unset when not
provided, allowing the OTEL SDK to apply its own defaults or fail as
intended—update the OTEL_EXPORTER_OTLP_ENDPOINT entry accordingly.
This setting only matters when telemetry is active, so it belongs with the rest of the observability config rather than in base compose. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1 participant
Instrument with OpenTelemetry and observe telemetry with OpenObserve.
TODO: Format logs for better viewing in OpenObserve and hide OpenObserve logs
Summary by CodeRabbit
New Features
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