A usage-based model, with Log - Retain and Log - Query charged separately.
Retain with Included Queries.
Usage-based model
In the usage-based model, Log - Retain and Log - Query are charged separately.
In this case, you pay for each query.
This is ideal if you have historical data that you do not access frequently.
Log - Ingest & Process feature overview
What's included with the Ingest & Process data-usage dimension?
Concept
Explanation
Data delivery
Delivery of log data via OneAgent or Log ingestion API (via ActiveGate)
Topology enrichment
Enrichment of log events with data source and topology metadata
Data transformation
- Add, edit, or drop any log attribute - Perform mathematical transformations on numerical values (for example, creating new attributes based on calculations of existing attributes) - Mask sensitive data by replacing either the whole log record, one specific log record attribute, or certain text with a masked string - Extract business, infrastructure, application, or other data from raw logs. This can be a single character, string, number, array of values, or other. Extracted data can be turned into a new attribute allowing additional querying and filtering. Metrics can be created from newly extracted attributes (see Conversion to time series below)
Data-retention control
- Filter and exclude incoming logs based on content, topology, or metadata (filtering generates usage for Ingest & Process, but not for Retain) - Manage data retention periods of incoming logs based on data-retention rules
Conversion to time series
Create metrics from log records or attributes (note that creating custom metrics generates additional consumption as described here)
Apply the following calculation to determine your consumption for the Ingest & Process data-usage dimension:
consumption = (number of GiBs ingested) × (GiB price as per your rate card)
Data enrichment and processing can increase your data volume significantly.
Depending on the source of the data, the technology, the attributes, and metadata added during processing, the total data volume after processing can increase by a factor of 2 or more.
Dynatrace reserves the right to work with customers to adjust or disable parsing rules, processors, or pipelines that are experiencing service degradation.
Log - Retain feature overview
Here's what's included with the Retain data-usage dimension:
Concept
Explanation
Data availability
Retained data is accessible for analysis and querying until the end of the retention period.
Retention periods
Choose a desired retention period. For log buckets, the available retention period ranges from 1 day to 10 years.
Metrics retention is defined at the bucket level, ensuring tailored retention periods for specific metrics.
Log - Query feature overview
Query data usage occurs when:
Executing DQL queries in Notebooks, Workflows, Custom Apps and via API
Dashboard tiles that are based on log data trigger the execution of DQL queries on refresh and include sampled data
Submitting DQL queries by clicking the ‘Run query’ button (for example, in the Logs & Events viewer in simple and advanced mode or on unified analysis pages)
What's included with the Query data-usage dimension?
Concept
Explanation
On-read parsing
Use DQL to query historical logs in storage and extract business, infrastructure, or other data across any timeframe, and use extracted data for follow-up analysis
Aggregation
Perform aggregation, summarization, or statistical analysis of data in logs across specific timeframes or time patterns (for example, data occurrences in 30-second or 10-minute intervals)
Reporting
Create reports or summaries with customized fields (columns) by adding, modifying, or dropping existing log attributes
Context
Use DQL to analyze log data in context with relevant data on the Dynatrace platform, for example, user sessions or distributed traces
Log - Retain with Included Queries feature overview
Dynatrace version 1.316+
In the Retain with Included Queries model, retained log data within a configured time period can be queried free of charge, as often as you want.
This is ideal if you frequently access recent data.
Customers can split a log bucket’s retention period into two parts:
An Included Queries retention period (ranging from 10 to 35 days of data retention).
The overall retention period (up to 10 years) that follows the standard usage-based Retain and Query model.
With the Retain with Included Queries model, Log - Ingest & Process consumption continues to be calculated separately.
Customers who select the Retain with Included Queries option in the bucket configuration are not charged for those queries executed the during the Included Queries retention period on a log bucket within the Dynatrace Platform.
In any 24-hour period, customers with this pricing option are entitled to run queries with an aggregate scanned-GiB volume up to 15 times the volume of log data that is retained within the Included Queries timeframe at that time.
In the event that usage exceeds the included volume of queries, Dynatrace reserves the right to throttle query throughput.
However, your access to logs will not be restricted. Our team will proactively reach out to help you optimize your usage.