Red Hat announced the latest release of Red Hat Process Automation, which delivers new developer tooling, extended support for eventing and streaming for event-driven architectures (EDA) through integration with Apache Kafka, and new monitoring capabilities through heatmap dashboards.
Traceable, a new end-to-end application security monitoring platform, launched from stealth today with $20M in series A funding from Unusual Ventures and BIG Labs.
Jyoti Bansal, the founder and former CEO of AppDynamics, heads the company as CEO and co-founder after selling AppDynamics to Cisco for $3.7 billion. Bansal is joined by Sanjay Nagaraj, former VP Engineering at AppDynamics, as CTO and co-founder. Traceable was spun out of BIG Labs, Bansal's startup studio.
"The broad use of APIs in cloud-native applications has greatly expanded the attack surface for enterprises, and until now, there hasn't been a solution that adequately addresses this growing issue," said Gerhard Eschelbeck, former Google CISO and Traceable advisor. "Traceable solves one of the biggest problem security teams face, which is distinguishing between valid and malicious use of an application's APIs."
Bansal and Nagaraj saw the massive adoption of cloud-native architectures firsthand while working with thousands of AppDynamics customers. At the same time, high profile businesses such as Uber and Facebook were making news as they became victims of new business logic attacks due to vulnerabilities in microservice APIs. With cloud-native architecture adoption skyrocketing, Bansal and Nagaraj founded Traceable to protect applications from next-generation attacks.
"It became clear to us that a drastically new approach to application security was needed to protect businesses as they deploy their applications in cloud-native architectures," said Bansal. "Existing solutions were designed to protect traditional monolithic web apps with well-understood protocols. They aren't capable of understanding distributed applications using thousands of custom APIs."
Traceable traces end-to-end application activity from the user and session all the way through the application code. TraceAI, the platform's machine learning technology, analyzes this data to learn normal application behavior and to detect activity that deviates from the norm. Businesses use Traceable's rich forensic data and insights to easily analyze attack attempts and perform root cause analysis.
Bansal and Nagaraj have made Traceable's underlying distributed tracing platform available as an open source project named Hypertrace. By deploying Hypertrace, DevOps teams observe and monitor production applications with the same comprehensive distributed tracing and observability capabilities powering Traceable.
"While we were building Traceable, we realized that every business and every application should have access to a robust distributed tracing system. Highly distributed cloud-native applications are almost impossible to operate and troubleshoot without distributed tracing," said Nagaraj. "So we decided to make this core part of our platform, open source and freely available. We hope the community not only adopts Hypertrace but feels empowered to contribute to the project to make it even better."