Blackhole
Send observability events nowhere, which can be useful for debugging purposes. Equivalent to Linux /dev/null. This destination can be used to create artificial backpressure.
Purpose
The Observo AI Blackhole destination discards observability events without storing or forwarding them, functioning as a data sink equivalent to Linux `/dev/null`. This destination is useful for debugging data pipelines by simulating event flow without persistence. It can also create artificial backpressure to test pipeline performance under constrained conditions.
Prerequisites
Before configuring the Amazon Security Lake Destination in Observo AI, ensure the following requirements are met to facilitate seamless data ingestion:
Observo AI Platform Setup:
The Observo AI Site must be installed and available.
Verify the instance has sufficient CPU and memory resources to handle event processing for the Blackhole destination.
Data Pipeline Configuration:
Identify the observability events or data streams to be discarded by the Blackhole destination for debugging or testing purposes.
Ensure the pipeline is set up to route specific events to the Blackhole destination.
Logging (Optional):
Enable logging in Observo AI to capture metadata of discarded events for debugging, if needed.
Configure log storage to a local file system, as the Blackhole destination does not require external network access.
Data Pipeline Configuration
Defines events to discard
Specify events for Blackhole routing
Logging
Captures discarded event metadata
Optional, for debugging pipeline behavior.
Integration
The Integration section outlines the default configurations for the Blackhole destination in Observo AI. The Blackhole destination discards observability events without storage or external forwarding, making it ideal for debugging pipelines or simulating backpressure. To configure the Blackhole destination, follow these steps:
Log in to Observo AI:
Navigate to the Destinations tab.
Click the "Add Destinations" button and select "Create New".
Choose "Blackhole" from the list of available destinations to begin configuration.
General Settings:
Name: Add a unique identifier such as blackhole-debug-1.
Description (Optional): Add a description for the destination.
Buffering Configuration:
Buffer Type (Empty): Specifies the buffering mechanism for event delivery.
OptionsDescriptionMemory
High-Performance, in-memory buffering Max Events: The maximum number of events allowed in the buffer. Default: 500 When Full: Event handling behavior when a buffer is full. Default: Block - Block: Wait for free space in the buffer.This applies backpressure up the topology, signalling that sources should slow down the acceptance/consumption of events. This means that while no data is lost, data will pile up at the edge. - Drop Newest: Drop the event instead of waiting for free space in the buffer. The event will be intentionally dropped. This mode is typically used when performance is the highest priority, and it is preferable to temporarily lose events rather than cause a slowdown in the acceptance/consumption of events.
Disk
Lower-Performance, Less-costly, on disk buffering Max Bytes Size: The maximum number of bytes size allowed in the buffer. Must be at-least 268435488 When Full: Event handling behavior when a buffer is full. Default: Block - Block: Wait for free space in the buffer. This applies backpressure up the topology, signalling that sources should slow down the acceptance/consumption of events. This means that while no data is lost, data will pile up at the edge. - Drop Newest: Drop the event instead of waiting for free space in the buffer. The event will be intentionally dropped. This mode is typically used when performance is the highest priority, and it is preferable to temporarily lose events rather than cause a slowdown in the acceptance/consumption of events.
Note: Send sample data and verify that it reaches the specified Security Lake S3 bucket and is queryable via Athena.
Advanced Settings (Optional):
Rate: The number of events, per second, that the sink is allowed to consume. By default, there is no limit.
Logging Interval Secs: The interval(in seconds) between reporting a summary of activity in logs. Set to 0 (default) to disable logging.
Save and Test:
Save the configuration settings.
Send sample data and verify that it reaches the specified Blackhole destination..
Example Scenarios
CyberSafe Inc., a fictitious technology enterprise, wants to integrate Observo with their Security SIEM solution to centralize security telemetry data for analysis. They have a target set of data that they would like to discard before sending to their SIEM destination.The target data to be discarded will be filtered out from the SIEM pipeline, and sent to a Blackhole destination.
Standard Blackhole Destination Setup
Here is a standard Blackhole Destination configuration example. Only the required sections and their associated field updates are displayed in the table below:
General Settings
Name
blackhole-1
Unique identifier for the destination.
Description
Blackhole with logging enabled.
Provides context for the destination's purpose.
Advance Settings: Rate
10
The number of events, per second, that the sink is allowed to consume.
Advance Settings: Logging Interval Secs
5
The interval (in seconds) between reporting a summary of activity in logs.
Troubleshooting
If issues arise with the Blackhole Destination in Observo AI, use the following steps to diagnose and resolve them:
Verify Configuration Settings:
Ensure the destination name and pipeline routing are correctly configured in Observo AI.
Confirm that the pipeline routes the intended observability events to the Blackhole destination.
Check Observo AI Logs:
Enable logging by setting Logging Interval Secs > 0 to capture metadata of discarded events.
Review Observo AI logs for errors or warnings related to event discarding.
Validate Pipeline Data Flow:
Use the Analytics tab in the Observo AI UI to monitor data volume and confirm events are routed to the Blackhole destination.
Check pipeline filters to ensure no critical data is accidentally discarded.
Monitor Resource Usage:
Verify the Observo AI instance has sufficient CPU and memory to handle event processing.
If resource usage is high, adjust instance resources to prevent bottlenecks.
Test Data Discarding:
Send sample observability data through the pipeline and verify in Observo AI logs that events are discarded without errors.
If Logging Interval Secs is set, check for metadata of discarded events to confirm pipeline behavior.
Data not discarded
Incorrect pipeline routing
Verify pipeline configuration in Observo AI
No discarded event logs
Logging Interval Secs set to 0
Set Logging Interval Secs > 0
High resource usage
Insufficient CPU/memory
Adjust instance resources
Pipeline processing errors
Buffer full with Block backpressure
Switch to Drop Newest or adjust buffer settings
Resources
For additional guidance and detailed information, refer to the following resources:
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