Release Notes October 20, 2023

Live Mode - Metrics Explorer

Click Live Mode when viewing Metrics and watch your Metrics stream into Observe. Filter your Metrics and generate visualizations that continuously update with new data. As soon as you click Live Mode, ingest and transform pipelines run at the highest possible rate. As new data arrives, the data transforms, and the query reruns.

See Metrics Explorer for more details.

Live Mode

Figure 1 - Enabling Live Mode

Extracting a String from a Dataset Column

When you click on the Column Menu icon, and select Extract String, the Extract String dialogue now appears to the right of the Dataset.

Extracting a String Dialogue

Figure 2 - Extracting a String Dialogue

OPAL Language Updates


Type of operation: Filter


Exclude rows from the input dataset that do not match the given predicate expression.

filter_last behaves identically to the verb filter except when the input is a Resource dataset. See the documentation for filter for more details.

When the input is a Resource dataset, cell values may change over time for a given row. In this case, filter_last filters the rows based on their last value. When the input consists of a Resource dataset and the filter predicate refers to a column which is time-mutable, then filter_last is not accelerable. See verb set_col_immutable for more information on time-mutable and time-immutable columns. To make filter_last accelerable on a Resource dataset, consider instead using ever with a frame or first using set_col_immutable. Consider also first converting the Resource to an Event or Interval dataset using make_event or make_interval, upon which filter_last is accelerable.


filter_last predicate









Only one



filter_last is sometimes accelerable, depending on options used. A dataset that only uses accelerable verbs can be accelerated, making queries on the dataset respond faster.


filter_last string(status_code) ~ /^5.*/

Keep only rows where the status_code column, converted to string, starts with “5”. For more simple examples, see the filter verb.

filter_last status="ON"

Where the input is a Resource dataset with a time-mutable column “status”, select the Resources whose last status during the query window was “ON”. This example is not accelerable.

filter_last server_id>100

Suppose the input is a Resource dataset describing many servers and how their statuses change over time. In this example, the primary key of the input Resource is the column “server_id”, and this column is time-immutable. This example selects the servers with a server_id greater than 100. This example is accelerable because for a given server, the server_id cannot change over time.