Overview of IBM Operations Analytics - Log Analysis extension options

This section describes how data is ingested by IBM® Operations Analytics - Log Analysis, the processes that are used to ingest the data, and the aspects of those processes that can be customized to create an Insight Pack.

Figure 1 illustrates the flow of data in IBM Operations Analytics - Log Analysis and outlines the extension interfaces that you can use to develop an Insight Pack.
Note: The WebSpere Insight Pack, which installed as part of IBM Operations Analytics - Log Analysis is used to illustrate the topics in this guide.
Figure 1. Overview of Insight Pack extension options
Illustration of the flow of data in IBM Operations Analytics - Log Analysis and shows the extension interfaces that you can use to develop an Insight Pack
Note: As an alternative to the Log File Agent, which is shown in figure 1, logstash can be used to acquire log data, parse it, and send it on to the EIF Receiver.

Data collection

There are three ways in which data can be consumed by IBM Operations Analytics - Log Analysis:
Data collector
Use the Data Collector to ingest data in batch mode. This is the easiest method to ingest a small number of log files or to test your IBM Operations Analytics - Log Analysis configuration.
For a video that demonstrates how to batch upload a WebSphere® Application Server or DB2 file using the Data Collector client, see https://www.ibm.com/developerworks/community/wikis/home?lang=en#!/wiki/IBM Log Analytics Beta/page/Videos. For information about batch uploading alternative log file types such as Oracle alert logs, see https://www.ibm.com/developerworks/community/wikis/home?lang=en#!/wiki/IBM%20Log%20Analytics%20Beta/page/Batch%20uploading%20Oracle%20Alert%20logs.
IBM Tivoli® Monitoring Log File Agent
Use the IBM Tivoli Monitoring Log File Agent to batch load larger numbers of log files and for scenarios where you want to stream log data from your production environment.
For a video that demonstrates how to batch upload a WebSphere Application Server or DB2 file using the IBM Tivoli Monitoring Log File Agent, see https://www.ibm.com/developerworks/community/wikis/home?lang=en#!/wiki/IBM Log Analytics Beta/page/Videos.
logstash
Use logstash, which is an open source tool for managing events and logs, to collect logs, parse them, and send them to IBM Operations Analytics - Log Analysis. For more information about configuring data collection, see the logstash Integration Toolkit topic in the Configuring IBM Operations Analytics - Log Analysis section of the Information Center.

Annotation

Annotation is the extraction of key pieces of data from unstructured or semi-structured input text. When you develop annotations for IBM Operations Analytics - Log Analysis, you can use Annotation Query Language (AQL) rules, or custom Java or Python logic.
Split/Annotate
There are two steps to the annotation process, split and annotate. During the split stage, specific logic, that is composed of rules or custom logic, is started to determine the logical beginning and end of an input data record. For example, if the logic is written to split log records by timestamp, then all physical records without a timestamp that follow the first physical record with a timestamp are considered part of the current logical record until the presence of the next timestamp is detected. After a complete logical record is established, it is forwarded on to the annotate stage where more logic is executed. This additional logic annotates or extracts the key pieces of information that are to be indexed. The fields that are annotated and then indexed are those that provide the most insight for searches or other higher-level operations that are performed on the indexed data.
AQL
Annotation Query Language (AQL) rules can be used to split input data records based on some known boundary and also used to annotate data from each record so that the records can be indexed. AQL rules included in an Insight Pack are installed into the IBM Operations Analytics - Log Analysis server when the Insight Pack is installed. Tools are provided to assist you with the development of AQL rules.
Custom
You can write custom logic, in Java or Python script, to perform the split and annotate functions. This is useful when you do not want to use or write AQL rules. You can include custom logic in an Insight Pack.
none
You can choose to exclude split and annotation logic from your Insight Pack. If you choose this option, any data records processed by Collections that are defined in the Insight Pack are indexed based on the indexing configuration only. In this case, only free form searches can be performed on the indexed data records.

Index configuration

To allow the fields that are extracted by the annotation logic to be indexed by IBM Operations Analytics - Log Analysis, you must supply an indexing configuration. The index configuration determines what is indexed, and how indexed data can be used in subsequent retrievals. After the data is indexed, you can perform searches and other higher-level operations to gain greater insight into the data for better problem determination. Tools are provided to enable you to develop an indexing configuration.

Administrative configuration

IBM Operations Analytics - Log Analysis provides a REST API to enable you to create configuration artifacts. As an Insight Pack developer, you can include definitions for various configuration artifacts such as Source Types, Collections, and Rule Sets. These artifacts are created when the content Insight Pack is installed. Tools are available to assist you with creating the configuration artifacts.