Log Analytics
- Latest Dynatrace
- Explanation
- 6-min read
Log Management and Analytics powered by Grail provides a unified approach to unlocking the value of log data in the Dynatrace platform.
Hassle-free management of your log data lets you ingest petabytes of data without schemas, indexing, or rehydration. All of that data is usable at any time for any analytics task. Thanks to schema on-read and the Dynatrace Query Language (DQL), there's no need to decide what you want to query during data ingestion. Select the retention period for your data that suits your business and compliance needs, whether for debugging or audit purposes.
Put Dynatrace Log Management and Analytics into use:
- Enhance unified observability: Integrate logs with traces and metrics for comprehensive observability in Kubernetes and cloud. Use Grail, DQL, and
Notebooks for unified exploration and visualization with dashboards. - Accelerate problem resolution: Utilize logs for detailed troubleshooting, leveraging Davis AI to pinpoint relevant logs and reduce mean time to repair. Perform instant queries with Grail and DQL for rapid issue resolution.
- Close monitoring gaps: Track metrics, health, performance, and business indicators from hybrid cloud and mainframe deployments. Automate log collection with OneAgent, parse and process logs at scale with OpenPipeline, and transform logs into metrics with Grail and DQL.
Get started
Quick start guide
Take the first steps to onboard and explore your logs.
Ingest logs
Set up log collection to automatically bring logs from different sources.
Set up buckets and permissions
Configure storage and define retention and access controls.
Configure processing in OpenPipeline
Define how ingested logs are processed and stored.
Log analytics
Explore available apps and their use cases.
Alerting, Problems, and automations
Create anomaly detection and alerts, as well as automate the detection process.
Log data can come from diverse sources, including Kubernetes, technology stacks, cloud services, hyperscalers, custom API integrations, or Dynatrace extensions. Dynatrace employs OneAgent and API as key methods for ingesting logs from these sources.
The ingested logs are channeled to Dynatrace OpenPipeline for processing, analysis, and storage.
The Grail data lakehouse serves as a single unified storage solution where log data is interconnected within a real-time model that reflects the topology and dependencies within a monitored environment.
You can analyze the ingested data in 
Logs, run queries in Notebooks to gather a comprehensive understanding of your log data, or use 
Dashboards for real-time visualization and monitoring.
Consumption model
The consumption model for Log Management and Analytics is based on three dimensions of data usage (Ingest & Process, Retain, and Query). The unit of measure for consumed data volume is gibibytes (GiB). In addition, Retain with Included queries is an available option combining the dimensions of Query and Retention. For details, see Log Analytics (DPS).
Availability and previous versions
Log Management and Analytics is the latest log offering available in Dynatrace SaaS with Grail.
