Today’s businesses collect an enormous amount of telemetry data from their cloud deployments, applications, networks, and security infrastructure. Converting this information into intelligence is becoming more and more important for companies that are leveraging AI and bolstering their cybersecurity and observability capabilities.
In today’s episode of the Analytics Insight Podcast, host Priya Dialani speaks with Soumyran Dasgupta, Founder and CEO of Blue, about telemetry intelligence, its role in cybersecurity, and how AI is reshaping enterprise decision-making.
Soumyran examines how the skillset for threat detection that Blue has built upon has expanded to solve data problems within enterprises. Soumyran highlights how telemetry intelligence can aid organizations in obtaining useful information from large amounts of data in a way that cuts down the cost of gathering and storing it.
The discussion examines the need to correlate security and observability data, how AI can correlate security signals in order to detect possible attacks and why existing monitoring systems cannot cope with more complicated digital environments.
Soumyran also provides insight into creating scalable telemetry strategies that will be ready for AI and the role of continuous high-fidelity data in aiding AI investigation and decision-making processes.
What is telemetry intelligence, and why is it important for enterprises?
Telemetry intelligence entails making telemetry data available and deriving valuable information out of it. It assists companies in enhancing their cybersecurity, system behavior, business intelligence, and decision-making processes while overcoming difficulties associated with data gathering and storing.
How does telemetry data help organizations strengthen cybersecurity?
Telemetry tracks digital activities through users, applications, devices, and networks. Analyzing such data can assist security teams to detect suspicious activity, correlate incidents, perform investigations, and obtain greater visibility within enterprise environments.
Why should enterprises integrate cybersecurity and observability data?
Bringing together such datasets can break down information silos and provide a more holistic understanding of issues surrounding the system incidents. This can assist security teams, infrastructure teams, cloud teams, and application teams to better understand issues and solve them faster.
How can AI improve security alert investigation?
AI is capable of correlating related alerts, identifying patterns, and exploring possible attack patterns that go beyond pre-set rules. This makes it easier for the security team to differentiate between related and unrelated incidents and investigate them thoroughly.
What do enterprises need to build an AI-ready telemetry strategy?
Enterprises require telemetry data with high fidelity and an effective mechanism to gather and store it. According to Soumyran, the AI algorithms perform well when provided with constant and detailed data, even the small events which would have been filtered out earlier.