feat: dev and prod observer configurations #631
Conversation
Introduce Docker Compose setups for Observer in both development and production environments. The configurations include services for Vector, Prometheus, and Grafana, with Prometheus scraping Vector metrics and Grafana set up for visualization. The dev environment uses a local Prometheus exporter, while the prod setup is configured to send metrics to Datadog.
Introduce Observer's configurations for both development and production. Development setup uses Docker Compose to run Vector, Prometheus, and Grafana, while production sends metrics directly to Datadog. Updated Taskfile to include a command for running the development setup.
WalkthroughA new task, Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Taskfile
participant DockerCompose
participant Vector
participant Prometheus
User->>Taskfile: Run observer-dev
Taskfile->>DockerCompose: Start services
DockerCompose->>Vector: Launch Vector service
DockerCompose->>Prometheus: Launch Prometheus service
Vector->>Prometheus: Export metrics
Assessment against linked issues
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Actionable comments posted: 7
Outside diff range and nitpick comments (10)
deployments/observer/vector-dev-destination.yml (1)
9-9: Add a newline at the end of the fileTo adhere to common coding standards and prevent potential issues with some tools, please add a newline character at the end of the file.
Apply this change to add a newline at the end of the file:
default_namespace: dev-observer flush_period_secs: 60 +Tools
yamllint
[error] 9-9: no new line character at the end of file
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deployments/observer/vector-prod-destination.yml (2)
1-9: Consider adding more detailed comments for each configuration option.While the current comment is good, adding more detailed comments for each configuration option would improve maintainability and make it easier for other team members to understand and modify the configuration if needed.
Here's a suggestion for more detailed comments:
# Production destination for Vector, sends metrics to Datadog sinks: datadog-destination: type: datadog_metrics # Specifies the sink type for Datadog metrics inputs: - hostmetrics # Source of the metrics to be sent to Datadog default_api_key: ${DATADOG_API_KEY} # API key for authenticating with Datadog default_namespace: ${DATADOG_NAMESPACE} # Namespace for organizing metrics in Datadog endpoint: ${DATADOG_ENDPOINT} # Datadog API endpoint for sending metrics
1-9: Consider implementing error handling and retry logic.Depending on the criticality of these metrics, you might want to implement error handling and retry logic to ensure data is not lost in case of temporary network issues or Datadog service disruptions.
Vector provides options for retry logic and error handling. Consider adding the following to your configuration:
sinks: datadog-destination: # ... existing configuration ... request: retry_attempts: 5 retry_initial_backoff_secs: 1 retry_max_duration_secs: 60 healthcheck: enabled: trueThis will attempt to retry failed requests up to 5 times with an initial backoff of 1 second, and enable healthchecks to ensure the sink is functioning correctly.
deployments/observer/vector-sources.yml (2)
4-6: LGTM: Appropriate source configuration for host metricsThe 'hostmetrics' source is correctly configured with the 'host_metrics' type, which aligns with Vector's documentation for collecting system-wide metrics. The included documentation link is helpful for future reference.
Consider adding a brief comment explaining the purpose of this specific source, e.g., "Collects various system-level metrics from the host machine."
7-14: LGTM: Comprehensive set of collectors enabledThe configuration enables a good set of essential system metric collectors (cpu, disk, filesystem, load, memory, and network). The exclusion of the 'cgroups' collector with an explanation shows thoughtful configuration.
Consider the following minor improvements:
- Update the comment on line 7 to explicitly list all default collectors for clarity.
- Add a brief explanation for why each collector is included, especially if this configuration differs from the default.
Example:
collectors: # defaults: [cpu, disk, filesystem, load, host, memory, network, cgroups] - cpu # CPU usage metrics - disk # Disk I/O metrics - filesystem # Filesystem usage metrics - load # System load metrics - memory # Memory usage metrics - network # Network traffic metrics # - cgroups # Excluded: not needed for discriminated metrics in this contextdeployments/observer/observer-compose.yml (1)
11-14: LGTM: Proper use of environment variables for Datadog integration.The environment variables are correctly defined for Datadog integration, and the use of the
${VAR?}syntax ensures that the compose will fail if these required variables are not set, which is a good practice.Consider adding documentation on how these environment variables should be managed securely. For example, you could create a
.env.examplefile with placeholder values and instructions on how to set up the actual.envfile:# Create a .env.example file cat << EOF > deployments/observer/.env.example DATADOG_API_KEY=your_datadog_api_key_here DATADOG_NAMESPACE=your_datadog_namespace_here DATADOG_ENDPOINT=https://api.datadoghq.com EOF echo "Created .env.example file with placeholder values."Then, update the README or a separate documentation file to explain how to use this example file to set up the actual environment variables securely.
deployments/observer/README.md (2)
1-25: LGTM! Consider adding a security note about changing the Grafana password.The introduction and development setup sections are well-structured and provide clear instructions. The information aligns with the PR objectives and includes essential details about components and ports.
Consider adding a note recommending users to change the default Grafana password after initial setup for improved security. You could add this after line 24:
- Grafana: 3000 (default admin password: `admin`) + +> **Note:** For security reasons, it's recommended to change the default Grafana password after initial setup.
26-34: LGTM! Consider adding instructions for production setup.The production setup section provides essential information about using Vector with Datadog and lists the required environment variables. This aligns well with the PR objectives and the linked issue #572.
To improve the documentation, consider adding instructions on how to set up and run the production configuration. You could add this after line 34:
### Setup 1. Ensure the required environment variables are set. 2. Run the following command to start the production Observer: ```bash task observer-prod(Replace
observer-prodwith the actual task name if different)
- Verify that metrics are being sent to Datadog by checking your Datadog dashboard.
This addition would provide users with a clear path to setting up the production environment. <details> <summary>Tools</summary> <details> <summary>LanguageTool</summary><blockquote> [uncategorized] ~32-~32: Loose punctuation mark. Context: ...vironment Variables - `DATADOG_API_KEY`: Datadog API key - `DATADOG_NAMESPACE`: ... (UNLIKELY_OPENING_PUNCTUATION) </blockquote></details> </details> </blockquote></details> <details> <summary>deployments/observer/dev-observer-compose.yml (2)</summary><blockquote> `1-4`: **Add Docker Compose version and consider adding a newline at the end of the file** The overall structure of the Docker Compose file is correct and the comments provide clear context. However, consider the following improvements: 1. Add a version specification at the beginning of the file. This is recommended for Docker Compose files to ensure compatibility. For example: ```yaml version: '3.8'
- Add a newline character at the end of the file to comply with YAML best practices.
Also applies to: 30-31
5-10: Consider using a specific version tag for the Vector imageThe Vector service configuration looks good overall. The configuration files are correctly mounted, and the command is set up properly. However, there's one suggestion for improvement:
Instead of using the
latest-alpinetag for the Vector image, consider using a specific version tag. This ensures consistency across different environments and makes it easier to track and reproduce builds. For example:image: timberio/vector:0.22.0-alpineReplace
0.22.0with the desired version number.
Review details
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Review profile: CHILL
Files selected for processing (8)
- Taskfile.yml (1 hunks)
- deployments/observer/README.md (1 hunks)
- deployments/observer/dev-observer-compose.yml (1 hunks)
- deployments/observer/dev-prometheus.yml (1 hunks)
- deployments/observer/observer-compose.yml (1 hunks)
- deployments/observer/vector-dev-destination.yml (1 hunks)
- deployments/observer/vector-prod-destination.yml (1 hunks)
- deployments/observer/vector-sources.yml (1 hunks)
Additional context used
LanguageTool
deployments/observer/README.md
[uncategorized] ~32-~32: Loose punctuation mark.
Context: ...vironment Variables -DATADOG_API_KEY: Datadog API key -DATADOG_NAMESPACE: ...(UNLIKELY_OPENING_PUNCTUATION)
yamllint
deployments/observer/dev-observer-compose.yml
[error] 31-31: no new line character at the end of file
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deployments/observer/dev-prometheus.yml
[error] 8-8: no new line character at the end of file
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deployments/observer/vector-dev-destination.yml
[error] 9-9: no new line character at the end of file
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Additional comments not posted (15)
deployments/observer/dev-prometheus.yml (2)
1-8: LGTM! The Prometheus configuration looks good.The configuration is well-structured and correctly set up to scrape metrics from the vector service. The global scrape interval of 15 seconds is a reasonable default, and the job configuration for the vector service is appropriately defined.
Tools
yamllint
[error] 8-8: no new line character at the end of file
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1-8: Verify complete observability setup, including Vector configuration.While this Prometheus configuration is correct and necessary for the observability stack, it doesn't directly address the Vector setup for host log collection mentioned in the PR objectives (issue #572). Ensure that the Vector configuration for collecting and tagging host logs from multiple hosts is also included in this PR or a separate one.
To verify the complete observability setup:
Check for Vector configuration files:
If Vector configuration files exist, verify they include host log collection setup:
Confirm the presence of Grafana configuration:
Please ensure all components (Prometheus, Vector, and Grafana) are properly configured to achieve the complete observability setup as outlined in the PR objectives.
Tools
yamllint
[error] 8-8: no new line character at the end of file
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deployments/observer/vector-dev-destination.yml (3)
1-9: LGTM: Well-structured configuration fileThe overall structure of the configuration file is clear and well-organized. The comment at the beginning provides useful context for the purpose of this file.
Tools
yamllint
[error] 9-9: no new line character at the end of file
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2-6: Verify the input source for the Prometheus sinkThe sink configuration for Prometheus looks good. However, please confirm that
hostmetricsis the correct and intended input source for this sink. If there are other metrics you want to export to Prometheus, you may need to add them to theinputsarray.
7-9: Review Prometheus exporter settings for security and performanceThe Prometheus exporter settings look generally good, but consider the following points:
Security: The exporter is set to listen on all interfaces (
0.0.0.0). For a development environment, this might be fine, but ensure that appropriate network security measures are in place.Performance: The
flush_period_secsis set to 60 seconds. Depending on your monitoring requirements, you might want to adjust this value. A shorter period will provide more frequent updates but increase network traffic and load on Prometheus.Namespace: The
default_namespaceis set to "dev-observer", which is good for distinguishing metrics in a development environment. Ensure this aligns with your naming conventions and monitoring strategy.To verify the security of the exporter configuration, you can run the following command to check if the port is accessible only from the intended networks:
If the port is accessible, consider restricting it to specific IP ranges or using a reverse proxy for added security.
Tools
yamllint
[error] 9-9: no new line character at the end of file
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deployments/observer/vector-prod-destination.yml (1)
1-9: LGTM! The Vector configuration for Datadog metrics looks good.The sink configuration for sending metrics to Datadog is correctly structured and follows best practices by using environment variables for sensitive information.
deployments/observer/vector-sources.yml (2)
1-16: LGTM: Well-structured YAML configurationThe overall structure and syntax of the YAML file are correct. The comments at the beginning provide useful context about the file's purpose and intended usage for both development and production environments.
1-16: Verify alignment with PR objectives and linked issueThe current configuration sets up host metrics collection, which aligns with the PR summary's goal of making metrics accessible in Grafana. However, there seems to be a discrepancy with the linked issue #572, which mentions setting up Vector for collecting host logs from multiple hosts.
Please clarify:
- Is log collection intended to be part of this PR, or will it be addressed separately?
- If log collection is part of this PR, consider adding a log collection source to this configuration file.
Example log collection source (if needed):
host_logs: type: file include: - /var/log/**/*.log exclude: - /var/log/excluded_directory/**/*.logIf log collection is to be implemented:
- Ensure proper tagging of logs for identification across multiple hosts.
- Consider separating metrics and logs configurations if they become too complex to manage in a single file.
deployments/observer/observer-compose.yml (3)
1-3: LGTM: Clear file header and purpose.The file header and comment effectively communicate the purpose of this configuration file for the production Observer service.
8-10: LGTM: Proper volume mounts for configuration files.The volume mounts correctly map the local configuration files to their expected locations in the container. The separation of destination and source configurations is a good practice.
To ensure the referenced configuration files exist and are properly formatted, you can run the following commands:
#!/bin/bash # Check if the configuration files exist and are valid YAML for file in deployments/observer/vector-prod-destination.yml deployments/observer/vector-sources.yml; do if [ -f "$file" ]; then echo "File $file exists." if yamllint "$file"; then echo "File $file is valid YAML." else echo "File $file is not valid YAML." fi else echo "File $file does not exist." fi done
7-7: LGTM: Flexible configuration setup, but be cautious with wildcards.The command configuration allows for multiple configuration files, which provides flexibility. However, be aware that using wildcards could potentially lead to unexpected configurations if unintended files are present in the directory.
To ensure only intended configuration files are present, you can run the following command:
deployments/observer/README.md (1)
1-34: Great job on the README! It effectively covers the Observer setup.This README file successfully addresses the PR objectives by providing clear instructions for both development and production environments. It aligns well with the goal of establishing initial configurations for observability and addresses the setup of Vector for collecting logs, as mentioned in the linked issue #572.
The document is well-structured, concise, and informative. It covers the essential components (Vector, Prometheus, Grafana) and provides necessary details for setup and configuration.
With the suggested minor improvements (security note for Grafana password and additional production setup instructions), this README will serve as an excellent guide for users setting up the Observer in both development and production environments.
Tools
LanguageTool
[uncategorized] ~32-~32: Loose punctuation mark.
Context: ...vironment Variables -DATADOG_API_KEY: Datadog API key -DATADOG_NAMESPACE: ...(UNLIKELY_OPENING_PUNCTUATION)
deployments/observer/dev-observer-compose.yml (2)
12-19: Prometheus service configuration looks goodThe Prometheus service is well-configured:
- A specific version tag (v2.30.3) is used for the image, which is a good practice.
- The configuration file is correctly mounted.
- The command for specifying the config file is correct.
- The port mapping (9090) is properly set up.
21-28: Grafana service configuration is good, but consider password securityThe Grafana service configuration looks good overall:
- A specific version tag (8.2.2) is used for the image.
- The port mapping (3000) is correctly set up.
- A named volume is used for persistent storage, which is a good practice.
However, note that setting the admin password via an environment variable is not secure for production environments. For the development environment, it's acceptable, but consider using a more secure method (like secrets management) when moving to production.
To ensure this is indeed a development-only configuration, let's check for any production configurations:
Taskfile.yml (1)
53-56: Overall approval of Taskfile changesThe addition of the
observer-devtask to the Taskfile is well-structured and consistent with the existing task definitions. Its placement in the file is logical, and it doesn't introduce any conflicts with other tasks.The changes to the Taskfile are approved, pending the clarifications and improvements suggested in the previous comments.
Description
Related Problem
How Has This Been Tested?
Advanced visualization will be handled with monitoring tools; for this PR having the metrics in Grafana is enough
Summary by CodeRabbit
Summary by CodeRabbit
New Features
observer-devtask for setting up development services using Docker Compose.Documentation
Configuration