Log Analytics gives you the analytical power of BigQuery directly in Cloud Logging with a new user interface that's optimized for analyzing logs data. With Log Analytics, you can use SQL to perform advanced logs analysis. To help break down data silos, Log Analytics also makes your logs data available directly in BigQuery. You can correlate your logs with other business data that's stored in BigQuery, giving you broader insights into your Google Cloud services.
Log Analytics features
- Bucket-level configuration: Easily configure your Logging buckets to apply Log Analytics to your ingested logs data.
- A new user interface: Query your logs data in a new Log Analytics UI using the BigQuery standard SQL. Your query results are displayed in a layout optimized for viewing logs data.
- Easy storage: Your logs data is stored in a BigQuery dataset that's managed by Logging.
- Access from BigQuery: Easily access your logs data in BigQuery using a new bucket configuration option.
How Log Analytics works
When you create a log bucket and enable Log Analytics on it, Cloud Logging makes the logs data available in the Log Analytics interface in Logging. By enabling Log Analytics, you don't have to route and manage a separate copy of the data in BigQuery. Log Analytics lets you analyze your logs data using the same standard SQL that BigQuery supports. You can still query and examine the data as usual using the Logging features you're familiar with.
If you want to combine and use your logs data with other data in BigQuery, you can configure a view of the data in the Logs Analytics-enabled bucket directly in BigQuery. The same query that you use in Log Analytics also works in BigQuery.
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