Splunk has a predict command that can be used to predict a future value of a metric based on historical values. This is not a Machine Learning or an Artificial Intelligence functionality, but a plain-old-statistical analysis.
So if we have a single metric, based on historical results we can produce a nice prediction for the future (of definable span), but predicting multiple metrics in Splunk might not be as straightforward.
The XRP Ledger (XRPL) is a decentralized, public blockchain and rippled server software (rippled in future references) powers the blockchain. rippled follows the peer-to-peer network, processes transactions, and maintains some ledger history.
rippled is capable of sending its telemetry data using StatsD protocol to 3rd party systems like Splunk.
Splunk Connect for Kafka (aka SC4K) allows to collect events from Kafka platform and send them to Splunk. While the sending part (to Splunk) was pretty straight forward to me, the collection part (from Kafka) was very new, as I’ve had no experience with Kafka eco-system. So I guess will start with it.
When having an exam with Pearson VUE, you would only get pass/faill result, but what if you want to know which section of the exam you have scored low and you want to brush up on the relevant skills? Here is how to get score breakdown for Pearson VUE exam.
user != "-"
clientip != "IP_of_SH1" clientip != "IP_of_SH2" clientip != “IP_of_SH3”
| stats values(clientip) by user
The limitation is if the users are going via a Load Balancer, you will see Load Balancer’s IP as the clientip