SecOps & Security | Resource Center

Learn how to build the modern SOC with Cloud SOAR and Cloud SIEM.

Machine data analytics is the process of parsing data generated by software from a wide variety of sources including servers, networks, applications and financial records. These, and many other similar sources, produce massive amounts of data including from local operating systems, identity/access management tools, cloud consoles and their associated log files, alerts, scripts and profiles. The goal of machine data analytics is to make this data more understandable by converting it into useful insights to monitor security events.

Managing the security of your Amazon Web Services (AWS) environment requires constant vigilance. Your strategy should include identifying potential threats to your environment and proactively monitoring for vulnerabilities and system weaknesses that malicious actors might exploit. In a complex environment – such as your AWS account with a multitude of services, coupled with various architectures and applications – the ideal solution should be both comprehensive and straightforward.

Sumo Logic SpecOps Situational Brief on the Log4Shell CVE-2021-44228 vulnerability and attempted exploitation observations.

While we are a long way from implementing Skynet, using machine learning combined with automation to make real-time decisions is here. In a recent talk at Sumo Logic Illuminate, Dave Frampton, General Manager of Cloud SIEM and Security Analytics, discusses the future of security with Vijaya Kaza, Head of Engineering and Data Science for Trust & Safety and Chief Security Officer at Airbnb. Kaza describes how automation, machine learning and AI can strengthen a company's overall security posture.

We’re excited to announce updates to Sumo Logic AWS Quick Start Integrations that enable customers to automate the integration of AWS Security Reference Architecture within Sumo Logic Cloud SIEM powered by AWS. The new integrations automate the collection, ingestion, and analysis of applications, infrastructure, security, and IoT data to derive actionable insights for security engineering teams.