gogllocator.blogg.se - Splunk tstats

| eval datamodel=mvappend(datamodel, datamodel2) | eval datamodel2=case(match(search, "src_dest_tstats"), mvappend("Network_Traffic", "Intrusion_Detection", "Web"), match(search, "(access_tracker|inactive_account_usage)"), "Authentication", match(search, "malware_operations_tracker"), "Malware", match(search, "(primary_functions|listeningports|localprocesses|services)_tracker"), "Application_State", match(search, "useraccounts_tracker"), "Compute_Inventory") | rex max_match=0 field=search "tstats.*?from datamodel=(?\w+)" | rex max_match=0 field=search "datamodel\W(?\w+)" | fields + title,rule_name,dispatch.earliest_time,dispatch.latest_time [| rest splunk_server=local /servicesNS/-/-/configs/conf-savedsearches | eval datamodel=if(datamodel="Endpoint.Filesystem","Endpoint",datamodel)] | table datamodel,complete(%),size(MB),access_time | `drop_dm_object_name("Datamodel_Acceleration")` [| `datamodel("Splunk_Audit", "Datamodel_Acceleration")` | fillnull acceleration_earliest value="N/A" | rex field=acceleration "\"earliest_time\":\"(?+)" | rex field=acceleration "\"enabled\":(?+)" [| rest /servicesNS/nobody/-/datamodel/model splunk_server=local Thanks to Ted Waddell and Cameron Schmidt from our team for their work to develop this search.Ĭopy to Clipboard | rest /servicesNS/-/-/admin/macros splunk_server=local To make this easier, we’ve developed a datamodel acceleration audit search which you can run in your environment to identify opportunities for improvement. Reviewing the settings for each datamodel in the Splunk UI can be a time-consuming task.

Configure the indexes’ whitelist to use the indexes that are identified.

Identify the index containing data with these tags.

Run searches to identify data that has these tags set.

For example, the Network Traffic data model uses the network and communicate tags. Data model acceleration works on the tags defined in the data model documentation.

Reference the documentation for each data model.

Here are a few steps to identity indexes for a data model and configure the settings in the CIM setup screen: However, if you’re reading this, you’re probably past that point and dealing with a Splunk environment that already has data, and now you’re trying to make these searches more efficient. The best time to identify where to apply DMA index constraints is when the data is first onboarded. To check the status of your accelerated data models, navigate to Settings -> Data models on your ES search head: Here are four ways you can streamline your environment to improve your DMA search efficiency. This is because correlation searches will be running against a data model that doesn’t yet contain data for the timeframe where the correlation search is running.

If DMA summarization falls behind, it can result in missed security alerts.

Data model summary searches will run continuously to build the data models, and correlation searches will run on a regular schedule (as often as every 5 minutes) to minimize the amount of time between when an event occurs and when an alert fires. In a Splunk ES environment, there are searches running constantly. Correlation searches within ES will typically run against accelerated data models in order to return results quickly. This is important for products such as Splunk Enterprise Security (ES), which rely on constantly running searches across significant volumes of data in order to identify anomalies or security-actionable events. Splunk uses Data Model Acceleration (DMA) to allow searches to run faster than they would against the raw data. This tutorial will walk you through the process of auditing your DMA searches so they’re running as efficiently as possible. Data Model Acceleration (DMA) is critical to proper alerting in the Splunk Enterprise Security Suite.