Key terms that you will encounter throughout the diagnostic and monitoring documentation include the following:
Any resulting physical entity, or data, generated and persisted to disk by the WebLogic Diagnostics Framework that can be used later for diagnostic analysis. For example, the diagnostic image file that is created when the server fails is an artifact. The diagnostic image artifact is provided to support personnel for analysis to determine why the server failed. The WebLogic Diagnostics Framework produces a number of different artifacts.
If diagnostic monitoring is enabled, a diagnostic context is created, initialized, and populated by WebLogic Server when a request enters the system. Upon request entry, WebLogic Server determines whether a diagnostic context is included in the request. If so, the request is propagated with the provided context. If not, WebLogic Server creates a new context with a specific name (weblogic.management.DiagnosticContext). The contextual data for the diagnostic context is stored in the diagnostic context payload. Thus, within the scope of a request execution, existence of the diagnostic context is guaranteed.
Data stores are a collection of data, or records, represented in a tabular format. Each record in the table represents a datum. Columns in the table describe various characteristics of the datum. Different data stores may have different columns; however, most data stores have some shared columns, such as the time when the data item was collected.
In WebLogic Server, information captured by WebLogic Diagnostics Framework is segregated into logical data stores, separated by the types of diagnostic data. For example, Server logs, HTTP logs, and harvested metrics are captured in separate data stores.
Business logic or diagnostic code that is executed when a joinpoint defined by a pointcut is reached. Diagnostic actions, which are associated with specific pointcuts, specify the code to execute at a joinpoint. Put another way, a pointcut declares the location and a diagnostic action declares what is to be done at the locations identified by the pointcut.
Diagnostic actions provide visibility into a running server and applications. Diagnostic actions specify the diagnostic activity that is to take place at locations, or pointcuts, defined by the monitor in which it is implemented. Without a defined action, a diagnostic monitor is useless.
Depending on the functionality of a diagnostic action, it may need a certain environment to do its job. Such an environment must be provided by the monitor to which the diagnostic action is attached; therefore, diagnostic actions can be used only with compatible monitors. Hence, diagnostic actions are classified by type so that their compatibility with monitors can be determined.
To facilitate the implementation of useful diagnostic monitors, a library of suitable diagnostic actions is provided with the WebLogic Server product.
The WebLogic Diagnostics Framework adds contextual information to all requests when they enter the system. You can use this contextual information, referred to as the diagnostic context, to reconstruct transactional events, as well correlate events based on the timing of the occurrence or logical relationships. Using diagnostic context you can reconstruct or piece together a thread of execution from request to response.
Various diagnostic components, for example, the logging services and diagnostic monitors, use the diagnostic context to tag generated data events. Using the tags, the diagnostic data can be collated, filtered and correlated by the WebLogic Diagnostics Framework and third-party tools.
The diagnostic context also makes it possible to generate diagnostic information only when contextual information in the diagnostic context satisfies certain criteria. This capability enables you to keep the volume of generated information to manageable levels and keep the overhead of generating such information relatively low. See also context creation, context payload, request dyeing.
An artifact containing key state from an instance of a server that is meant to serve as a server-level state dump for the purposes of diagnosing significant failures. This artifact can be used to diagnose and analyze problems even after the server has cycled.
A diagnostic module is the definition the configuration settings that are to be applied to the WebLogic Diagnostics Framework. The configuration settings determine the data that is to be collected and processed, how the data is to be analyzed and archived, the notifications and alarms that are to be fired, and the operating parameters of the Diagnostic Image Capture component. After a diagnostic module has been defined, or configured, it can be distributed to a running server where the data is collected.
A diagnostic monitor is a unit of diagnostic code that defines the following:
The locations in a program where the diagnostic code is added
The diagnostic actions that are executed at those locations
WebLogic Server provides a library of useful diagnostic monitors. You can integrate these monitors into server and application classes. Once integrated, the monitors take effect at server startup for server classes, and at application deployment and redeployment for application classes.
The action that occurs as a result of the successful evaluation of a watch rule. The WebLogic Diagnostics Framework supports these types of diagnostic notifications: Java Management Extensions (JMX), Java Message Service (JMS), Simple Mail Transfer Protocol (SMTP), Simple Network Management Protocol (SNMP), and WLDF Image Capture. See also diagnostic image.
The process of looking at the dye mask and making the decision as to whether or not a diagnostic monitor should execute an action so as to generate a data event. Dye filtering is dependent upon dye masks. You must define dye masks in order for dye filtering to take place. See also dye mask, request dyeing.
The entity that contains a predefined set of conditions that are used by dye filtering in diagnostic monitors to determine whether or not a data event should be generated. See also dye filtering, request dyeing.
A harvestable entity is any entity that is available for data consumption via the Harvester. Once an entity is identified as a harvestable resource, the Harvester can engage the entity in the data collection process.
Harvestable entities provide access to the following information: harvestable attributes, values of harvestable attributes, metadata for harvestable attributes, and the name of the harvestable entity. See also harvestable data, harvested data, Harvester's configuration data set, MBean type discovery.
Harvestable data (types, instances, attributes) is the set of data that potentially could be harvested when and if a harvestable entity is configured for harvesting. Therefore, the set of harvestable data exists independent of what data is configured for harvesting and of what data samples are taken.
The WLDFHarvesterRuntimeMBean provides the set of harvestable data for users. For a description of the information about harvestable data provided by this MBean, see the description of the weblogic.management.runtime.WLDFHarvesterRuntimeMBean in the MBean Reference for Oracle WebLogic Server.
The WebLogic Diagnostics Framework only makes run-time MBeans available as harvestable. In order for an MBean to be harvestable, it must be registered in the local WebLogic Server run-time MBean server. See also harvestable entities, harvested data, Harvester's configuration data set, MBean type discovery.
A type, instance, or attribute is called harvested data if that data is currently being harvested. To meet these criteria the data must: 1) be configured to be harvested, 2) if applicable, it must have been discovered, and 3) it must not throw exceptions while being harvested.
The set of data to be harvested as defined by the Harvester's configuration. The configured data set can contain items that are not harvestable and items that are not currently being harvested.
A well defined point in the program flow where diagnostic code can be added. The Instrumentation component allows identification of such diagnostic joinpoints with an expression in a generic manner.
A well defined set of joinpoints, typically identified by some generic expression. Pointcuts identify joinpoints, which are well-defined points in the flow of execution, such as a method call or method execution site. The Instrumentation component provides a mechanism to allow execution of specific diagnostic code at such pointcuts. The Instrumentation component adds such diagnostic code to the server and application code.
A Java object that provides a management interface for an underlying resource. An MBean is part of Java Management Extensions (JMX).
In the WebLogic Diagnostics Framework, MBean classes are used to configure the service and to monitor its run-time state. MBeans are registered with the MBean server that runs inside WebLogic Server. MBeans are implemented as standard MBeans which means that each class implements its own MBean interface.
For WebLogic Server entities, the set of harvestable types is known at system startup, but not the complete set of harvestable instances. However, for user-defined MBeans, the set of types can grow dynamically as more MBeans appear at run time. The process of detecting a new type based on the registration of a new MBean is called type discovery. MBean type discovery is only applicable to user-defined MBeans.
The set of harvestable attributes for a type (and its instances) is defined by the metadata for the type. Since the WebLogic Server model is MBeans, the metadata is provided through MBeanInfos. Since WebLogic type information is always available, the set of harvestable attributes for WebLogic Server types (and existing and potential instances) is always available as well. However, for customer types, knowledge of the set of harvestable attributes is dependent on the existence of the type. And, the type does not exist until at least one instance is created. So the list of harvestable attributes on a user defined type is not known until at least one instance of the type is registered.
It is important to be aware of latencies in the availability of information for custom MBeans. Due to latencies, the Administration Console cannot provide complete lists of all harvestable data in its user selection lists for configuring the harvester. The set of harvestable data for WebLogic Server entities is always complete, but the set of harvestable data for customer entities (and even the set of entities itself) may not be complete.
Metadata is information that describes the information the WebLogic Diagnostics Framework collects. Because the service collects diagnostic information from different sources, the consumers of this information need to know what diagnostic information is collected and available. To satisfy this need, the Data Accessor provides functionality to programmatically obtain this metadata. The metadata made available by means of the Data Accessor includes:
A list of supported data store types. For example, SERVER_LOG, HTTP_LOG, and HARVESTED_DATA.
A list of available data stores.
The layout of each data store; that is, information about columns in the data store.
Monitoring system operation and diagnosing problems depends on having data from running systems. Metrics are measurements of system performance. From these measurements, support personnel can determine whether the system is in good working order or a problem is developing.
In general, metrics are exposed to the WebLogic Diagnostics Framework as attributes on qualified MBeans. In WebLogic Server, metrics include performance measurements for the operating system, the virtual machine, the system runtime, and applications running on the server.
Requests can be dyed, or specially marked, to indicate that they are of special interest. For example, in a running system, it may be desirable to send a specially marked test request, which can be conditionally traced by the tracing monitors. This allows creation of highly focused diagnostic information without slowing down other requests.
Requests are typically marked when they enter the system by setting flags in the diagnostic context. The diagnostic context provides a number of flags, 64 in all, that can be independently set or reset.
Whenever a system fails, there is need to know its state when it failed. Therefore, a means of capturing system state upon failure is critical to failure diagnosis. A system image capture does just that. It creates, in essence, a diagnostic snapshot, or dump, from the system for the express purpose of diagnosing significant failures.
In WebLogic Server, you can configure the WebLogic Diagnostics Framework provides the First-Failure Notification feature to trigger system image captures automatically when the server experiences an abnormal shutdown. You can also implement watches to automatically trigger diagnostic image captures when significant failures occur and you can manually initiate diagnostic image captures on demand.
A watch encapsulates all of the information for a watch rule. This includes the watch rule expression, the alarm settings for the watch, and the various notification handlers that will be fired once a watch rule expression evaluates to true.
The time it takes to inspect server and application classes and insert the diagnostic byte code at well-defined locations, if necessary at class load time. The diagnostic byte code enables the WebLogic Diagnostics Framework to take diagnostic actions. Weaving time affects both the load time for server-level instrumented classes and application deployment time for application-level classes.