Abstract: Key name synthesis is disclosed. A metrics data point is received. Based at least in part on a translation statement, at least a portion of the received metrics data point is associated with a key specified by the translation statement such that the specified key and the associated at least portion of the received metrics data point form a key-value pair. The key-value pair is associated with the received metrics data point.

Abstract: Logs to metrics synthesis includes receiving a log message. It further includes translating the log message into a metrics data point comprising a timestamp, a metric name, a metric value, and a set of metadata key-value pairs. It further includes determining a time series in which to insert the metrics data point into which the log message was translated. It further includes inserting the metrics data point into the determined time series. It further includes updating a metadata catalog based at least in part on the metrics data point.

Abstract: Key name synthesis is disclosed. A metrics data point is received. Based at least in part on a translation statement, at least a portion of the received metrics data point is associated with a key specified by the translation statement such that the specified key and the associated at least portion of the received metrics data point form a key-value pair. The key-value pair is associated with the received metrics data point.

Abstract: Key name synthesis is disclosed. A metrics data point is received. Based at least in part on a translation statement, at least a portion of the received metrics data point is associated with a key specified by the translation statement such that the specified key and the associated at least portion of the received metrics data point form a key-value pair. The key-value pair is associated with the received metrics data point.

Abstract: Data enrichment and augmentation is disclosed. Machine data comprising at least one of a log message and a metrics data point is received. The received machine data comprises an identifier of an instance of a virtual machine. Based at least in part on the identifier of the instance of the virtual machine, a query for tags associated with the instance of the virtual machine is performed. At least one key-value pair is generated based at least in part on tags received in response to the query performed based at least in part on the identifier of the instance of the virtual machine. The received machine data is augmented with the at least one key-value pair generated based at least in part on the tags received in response to the query based at least in part on the identifier of the instance of the virtual machine.

Abstract: Data enrichment and augmentation is disclosed. Machine data comprising at least one of a log message and a metrics data point is received. The received machine data comprises an identifier of an instance of a virtual machine. Based at least in part on the identifier of the instance of the virtual machine, a query for tags associated with the instance of the virtual machine is performed. At least one key-value pair is generated based at least in part on tags received in response to the query performed based at least in part on the identifier of the instance of the virtual machine. The received machine data is augmented with the at least one key-value pair generated based at least in part on the tags received in response to the query based at least in part on the identifier of the instance of the virtual machine.

Abstract: A technique for logs to metrics synthesis is disclosed. A log message is received. It is determined that the received log message should be translated into a metrics data point. In response to determining that the received log message should be translated into a metrics data point, the metrics data point is generated using the received log message, the generated metrics data point comprising a timestamp, a metric name, a metric value, and a set of metadata key-value pairs. A time series in which to insert the metrics data point generated using the received log message is identified. The generated metrics data point is inserted into the identified time series.

Abstract: Obfuscating data is disclosed. A processor identifies structured information in log data. The structured information is transformed in a manner that preserves the structure to form transformed raw data. The transformed raw data is sent to a remote analysis engine. The remote analysis engine receives a query and responds to the query by providing as results at least a portion of the transformed raw data. A processor is configured to de-transform the transformed raw data.

Abstract: Logs to metrics synthesis includes receiving a log message. It further includes translating the log message into a metrics data point comprising a timestamp, a metric name, a metric value, and a set of metadata key-value pairs. It further includes determining a time series in which to insert the metrics data point into which the log message was translated. It further includes inserting the metrics data point into the determined time series. It further includes updating a metadata catalog based at least in part on the metrics data point.

Abstract: Obfuscating data is disclosed. A processor identifies structured information in log data. The structured information is transformed in a manner that preserves the structure to form transformed raw data. The transformed raw data is sent to a remote analysis engine. The remote analysis engine receives a query and responds to the query by providing as results at least a portion of the transformed raw data. A processor is configured to de-transform the transformed raw data.

Abstract: Obfuscating data is disclosed. A processor identifies structured information in log data. The structured information is transformed in a manner that preserves the structure to form transformed raw data. The transformed raw data is sent to a remote analysis engine. The remote analysis engine receives a query and responds to the query by providing as results at least a portion of the transformed raw data. A processor is configured to de-transform the transformed raw data.

Abstract: Obfuscating data is disclosed. A processor identifies structured information in log data. The structured information is transformed in a manner that preserves the structure to form transformed raw data. The transformed raw data is sent to a remote analysis engine. The remote analysis engine receives a query and responds to the query by providing as results at least a portion of the transformed raw data. A processor is configured to de-transform the transformed raw data.