Operations | Monitoring | ITSM | DevOps | Cloud

In this blog post, we’ll demonstrate how to use Cribl Search for anomaly detection by finding statistical outliers in host CPU usage. By monitoring the “CPU Busy” metric, we can identify unusual spikes that may indicate malware penetration or high load/limiting conditions on customer-facing hosts. The best part? This simple but powerful analytic is easily adaptable to other metrics, making it a versatile tool for any data-driven organization.

2023 is well underway and now more than ever it’s important to stay ahead of data trends and security concerns that are ever mounting. With the cost of catastrophic cyber attacks estimated to be ten times that of all other disasters combined, businesses need to take proactive measures to implement a security data pipeline to protect their data and comply with security and retention requirements.

In the blog titled “Streamline Endpoint Data with Cribl Pack for SentinelOne Cloud Funnel” we dove into the Cloud Funnel data, its relevance in the modern SOC, and how Cribl Stream transforms the data while addressing visibility gaps. We left the AWS-specific details to this blog for those not yet familiar with configuring AWS S3 buckets, SQS Queues, and Identity and Access Management (IAM).

Cribl empowers you to take control of your observability, telemetry, and security data. Wherever your data originates from, wherever your data needs to go, and whatever format your data needs to be in, Cribl gives you the freedom and flexibility to make choices instead of compromises. Addressing visibility gaps by ingesting more data sources as the threat surface continues to expand has been a challenge.