How Unified Native Solutions and AI Change the Security Cloud Battleground
Posted: Thursday, Apr 04

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How Unified Native Solutions and AI Change the Security Cloud Battleground

An Overview

The rapid adoption of cloud computing has created a paradigm shift in cybersecurity. While the cloud offers numerous benefits, it also introduces new challenges and risks that require fundamentally rethinking our cybersecurity strategies.

The cloud’s appeal lies in its ability to democratise access to powerful computing resources, scalability, efficiency, innovation, and growth.

However, while major cloud service providers invest significantly in securing their infrastructure, the cloud introduces crucial changes, such as shared responsibility. This means that providers secure the infrastructure, but the responsibility for securing data, applications, and access lies with the users of these services, creating potential security gaps and failures.

The dynamic and distributed nature of cloud environments creates further difficulties. The transient nature of cloud resources, the proliferation of microservices and containers, and the increasing use of serverless computing expand the attack surface, making it difficult to monitor and protect using traditional security tools and processes.

The “zero trust” concept exemplifies another key difference between cloud and traditional security. In the conventional “castle and moat” model, businesses trust everything inside the network perimeter. For the cloud, the zero-trust approach defines that every user, device, and application must be authenticated and authorised before accessing resources.

A New Approach

Unified cloud-native platforms combined with Artificial intelligence (AI) and machine learning (ML) are becoming critical for addressing these new challenges. By leveraging vast amounts of cloud-generated data, AI and ML algorithms can identify patterns and anomalies that would be impossible for human analysts to detect.

Unified cloud-native security solutions leveraging AI and ML can continuously monitor cloud environments for signs of malicious activity, providing actionable insights to security teams for faster, more effective responses.

For example, AI-powered security solutions can establish a baseline of normal behaviour, making detecting deviations that may indicate a threat easier. This approach is particularly effective for identifying insider threats and compromised accounts.

Cloud-native security solutions and AI can also leverage the cloud platform’s inherent capabilities for granular, dynamic security controls. They can integrate and automate services like identity and access management, encryption, and network segmentation for security-focused development and deployment processes.

Cloud-native approaches also support compliance monitoring and reporting, enabling organisations to adhere to regulatory requirements and industry standards, reducing the risk of costly fines and reputational damage.

Unified security solutions also offer significant value as cybersecurity budgets come under increasing scrutiny. By consolidating security functions, organisations can achieve better outcomes with fewer resources, optimising spending while enhancing safety.

The cloud represents a new frontline in cybersecurity. To succeed, organisations must adopt cloud-native approaches that integrate security throughout their operations, leveraging the latest technologies and best practices. This allows them to reap the cloud’s benefits while minimising the risks and ensuring the protection and privacy of their critical assets.

Jay Parikh
Jay Parikh has been solving challenges at the cutting edge of scale computing for decades. He was at NetGravity, which would become DoubleClick and then Google Ads, figuring out how to scale and automate internet advertising during the earliest day of web commerce. In 1999, Jay ran engineering teams at Akamai, where the challenge was to serve the web’s increasing thirst for rich media content at scale. Most recently, Jay was VP of Engineering at Meta as it grew from a predominantly single application company with 300 engineers and 300 million users to a team managing multiple applications (, Instagram, WhatsApp, Messenger) with 30,000+ engineers, for 3.5+ billion users. Jay is currently the Co-CEO of Lacework, a role he took on in partnership with fellow Co-CEO David Hatfield. He joined the fast-growing cloud security startup last summer, just before the company raised another record-breaking round of funding.
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