Data pipelines
In IBM® Cloud Logs, you can define the way logs are distributed across different data pipelines and balance cost in your environment.
About data pipelines
There are 3 data pipelines. Each pipeline has a different storage price.
- Priority insights pipeline
- Analyze and alert pipeline
- Store and search pipeline
Each pipeline offers different features that you can use to work with the data.
Feature | Priority insights | Analyze and alert | Store and search |
---|---|---|---|
Fast query | Yes | No | No |
High-speed search using hot storage | Yes | No | No |
Dashboards and analytics using hot storage | Yes | No | No |
Dashboards and analytics using IBM Cloud Object Storage | Yes | Yes | No |
Intelligent log analytics | Yes | Yes | No |
Alert on logs | Yes | Yes | No |
Metrics maintained on log data for up to 1 year | Yes | Yes | No |
Re-index logs for further analysis | Yes | Yes | Yes |
Search logs in IBM Cloud Object Storage | Yes | Yes | Yes |
Store logs in IBM Cloud Object Storage | Yes | Yes | Yes |
Using the TCO Optimizer
You use the TCO Optimizer to configure policies that define which data pipeline handles data after ingestion.
You can apply policies to data based on the application name, the subsystem name, and log severity. These 3 fields are metadata fields that all log data must have. For more information, see Metadata fields.
The TCO Optimizer can help you improve real-time analysis and alerting while managing costs.
You can exclude data by defining a TCO policy that is applied immediately after ingestion or by configuring a Block parsing rule. Data excluded by using the TCO policy is dropped. Data excluded by using a Block parsing rule offers 2 options: drop the data or allow the data to be available through live tail. When you configure the option to view data in live tail, data is also archived to the service instance's COS bucket.
When you configure parsing rules that add metadata, drop data, or replace data in a log record, or when you enrich log data, the log line that is archived is the log line modified.
The following table outlines core features by data pipeline for data ingested after TCO policies are applied:
Feature | Priority insights | Analyze and alert | Store and search |
---|---|---|---|
Parsing rules | Yes | Yes | Yes |
Custom data enrichment | Yes | Yes | Yes |
Schema store | Yes | Yes | Yes |
Events to Metrics | Yes | Yes | No |
Dynamic alerting | Yes | Yes | No |
Templating | Yes | Yes | No |
Anomaly detection | Yes | Yes | No |
Indexing | Yes | No | No |
IBM Cloud Object Storage requirement
You must have a IBM Cloud Object Storage bucket configured for your instance to archive data for long term storage from the Priority insights data pipeline, to archive data for the Analyze and alert and Store and search data pipelines, and if you configure parsing rules that block data with the option to see data through live tail.
Priority insights data pipeline
Use the Priority insights data pipeline for high priority logs that require the most immediate attention and intervention such as logs for troubleshooting problems or analyzing unexpected behaviour.
Features available for high prioirty logs are:
-
Serverless monitoring
-
Rapid query
-
Service Catalog
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Service Map
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Alerting
-
Events to Metrics
-
Query archive
-
Viewing traces in your explore screen
Analyze and alert data pipeline
Use the Analyze and alert data pipeline for medium priority logs that may require attention at some point, but do not require immediate attention.
Features available for medium priority logs are:
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Service Catalog
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Service Map
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Alerting
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Events to Metrics
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Query archive
-
Viewing traces in your explore screen
Store and search data pipeline
Use the Store and search data pipeline for logs that you must keep for compliance purposes but do not require action to be taken.
Features available for low priority logs include:
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Query archive
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Viewing traces in your explore screen