I’m sure many of you will have tried out the predictive features in ITSI, and you may even have a model or two running in production to predict potential outages before they occur. While we present a lot of useful metrics about the models’ performance at the time of training, how can you make sure that it is still generating accurate predictions? Inaccuracy in models as the underlying data or systems change over time is natural.
Welcome back to another day in paradise. Today we are announcing the release of Splunk Enterprise 8.2. Since our last release of Splunk Enterprise 8.1 at .conf20, we have continued development of new and enhanced capabilities for our twice a year release cadence. In Splunk Enterprise 8.2, we have focused our development offers across a number of themes: insights, admin productivity, data infrastructure, and performance.
Today’s software is incredibly complicated and creates tons of data. Metrics, logs, and traces are generated constantly by hundreds of services for even simple applications. Every transaction can generate on the order of kilobytes of metadata about the transaction — and multiplying that to account for even a small amount of concurrency can create a few megabytes a second (or ~300GB/day) of data that needs to be captured and analyzed for later use.
Every career has defining moments. Most are spread out over years or even decades, but the cybersecurity world has had two career-defining moments just in the past year. It started with the global shutdown due to the COVID-19 pandemic. Overnight, many organizations were forced to support employees working remotely. CISOs, like me, were expected to keep both our company and its employees safe in a completely unpredictable world.
Amazon Web Services (AWS) recently announced the launch of CloudWatch Metric Streams. Cloudwatch Streams can stream metrics from a number of different AWS resources using Amazon Kinesis Data Firehose to target destinations. The new service is different from the current architecture. Instead of polling, metrics are delivered via an Amazon Kinesis Data Firehose stream. This is a highly scalable and far more efficient way to retrieve AWS service metrics.
Despite the myriad pathways to initial access on our networks, phishing remains the single most popular technique for attackers. The open nature of email and our reliance on it for communication make it difficult for defenders to classify messages, so it is no surprise that suspicious email investigation is a top use case for automation. Today, we are releasing a new community playbook for Splunk SOAR (previously Splunk Phantom) to help enrich suspicious email events.
