Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

One of the core value propositions of AIOps platforms is to increase IT efficiency & productivity by applying AI & ML techniques to perform Alert Noise Reduction. This in turn translates to direct cost reduction due to savings in IT man-hours. In this approach, the AIOps platform kind of becomes like a gatekeeper for all the IT alerts/events, and it can help effectively, reduce and correlate such events, so as to send meaningful incidents to NOC or Service Desk.

Over the past two years that we have lived with the pandemic, the world has changed dramatically. Those changes provided financial criminals with great opportunities to take advantage of many businesses when they were at their most vulnerable, trying to adjust to a new reality. Remote working environments, the ongoing digitization of services, COVID-19 restrictions – all have contributed to the development of new cyber threats and techniques.

Securing modern-day production systems is expensive and complex. Teams often need to implement extensive measures, such as secure coding practices, security testing, periodic vulnerability scans and penetration tests, and protections at the network edge. Even when organizations have the resources to deploy these solutions, they still struggle to keep pace with software teams, especially as they accelerate their release cycles and migrate to distributed systems and microservices.

The security stack is a crucial part of any company’s IT infrastructure. However, Security teams increasingly report that traditional SIEM solution approaches are “costly, complex, and resource-consuming,” according to a recent ESG survey. Fortunately, there has been significant innovation in how firms approach cybersecurity with new cloud-native technologies stack and breaking free from vendor lock-in and giving themselves more flexibility, cost advantage, and future-proofing.

A core challenge for threat detection engineering is reproducing common attacker behavior. Several open source and commercial projects exist for traditional endpoint and on-premise security, but there is a clear need for a cloud-native tool built with cloud providers and infrastructure in mind. To meet this growing demand, we’re happy to announce Stratus Red Team, an open source project created to emulate common attack techniques directly in your cloud environment.

Wachy is a new Linux performance debugging tool that Rubrik recently released as open source. It enables interesting new ways of understanding performance by tracing arbitrary compiled binaries and functions with no code changes. This blog post briefly outlines various performance debugging tools that we commonly use, and the advantages and disadvantages of each. Then, we discuss why and how we built wachy.