Multi-cloud and cybersecurity: Ensuring data integrity across cloud platforms and data centres
By Ranjit Metrani, President – Managed Services, CtrlS Datacenters
In the current digital era, businesses increasingly rely on multi-cloud strategies to optimise flexibility, mitigate vendor lock-in, and enhance cost efficiency. With this shift, data centres play a critical role in supporting the infrastructure that powers multi-cloud environments, offering scalable storage, computing, and networking solutions. However, with the rising adoption of multi-cloud architectures, data centres face significant cybersecurity challenges, particularly in ensuring the integrity and protection of data across multiple cloud platforms. The global average cost of a data breach in a multi-cloud environment is $4.88 million, according to 2024 IBM data breach report, highlighting the risks involved in managing data across multiple cloud platforms
Data centres are the backbone of multi-cloud strategies, housing critical infrastructure that connects cloud service providers (CSPs) like AWS, Microsoft Azure, and Google Cloud. As businesses increasingly rely on these distributed environments, data centres must ensure seamless data flow while upholding stringent security standards. However, with data residing in multiple locations and traversing different cloud platforms, data centres are tasked with managing diverse security controls, regulatory requirements, and compliance across multiple geographies. This complexity underscores the need for robust security measures that can provide consistent oversight across all platforms while safeguarding data integrity.
Cybersecurity challenges in multi-cloud environments
One of the key challenges data centres face in a multi-cloud environment is the need to protect data as it moves between private and public clouds. Data travelling between on-premises infrastructure and various cloud platforms is often subject to different encryption standards and network protocols. Ensuring end-to-end encryption for both data at rest and in transit is essential for preventing breaches during this exchange. Additionally, data centres must implement strong key management solutions to ensure encryption keys are secure and not susceptible to unauthorised access, especially across platforms that may have differing encryption protocols.
Ensuring compliance in a multi-cloud world
The need for regulatory compliance adds further complexity for data centres. With businesses storing and processing data in multiple cloud platforms, data centres must ensure adherence to data sovereignty laws, including regulations such as the General Data Protection Regulation (GDPR). For example, data centres handling multi-cloud infrastructures must be capable of enforcing compliance measures that address where data can be stored and who can access it, ensuring that data privacy regulations are upheld. Failing to comply with these regulations can lead to significant legal consequences and reputational damage, especially as regulators increase scrutiny on cross-border data storage and sharing.
From an operational perspective, automation has become indispensable for data centres managing multi-cloud environments. As the scale of multi-cloud operations grows, data centres face the daunting task of continuously monitoring for potential security breaches and compliance issues. Automation tools such as Cloud Security Posture Management (CSPM) and Cloud Access Security Brokers (CASB) can help streamline these processes by providing continuous visibility, risk assessment, and real-time threat detection. These tools allow data centres to monitor the security postures of multiple cloud environments, ensuring that any misconfigurations, vulnerabilities, or policy violations are quickly identified and addressed.
Emerging technologies like artificial intelligence (AI) and machine learning (ML) are also making their mark in data centre operations. By integrating AI-powered security solutions, data centres can enhance their ability to detect anomalies and predict potential vulnerabilities before they become full-scale security incidents. For instance, AI can analyse data traffic patterns across multiple cloud platforms, identifying irregularities that may indicate malicious activity or system misconfigurations. As AI continues to advance, data centres will increasingly rely on these technologies to automate security operations, reducing human error and enhancing their ability to secure data across complex multi-cloud architectures.
Looking to the future, data centres must also consider the rise of edge computing in multi-cloud environments. Edge computing, where data processing occurs closer to the data source rather than in a centralised location, presents additional security challenges. As data centres expand their capabilities to support edge computing, they must implement security controls that protect data not only in cloud environments but also at the network’s edge. This requires distributed security measures, real-time threat detection, and secure data synchronisation between edge devices and central cloud platforms. As edge computing becomes more integrated with multi-cloud strategies, data centres will need to develop more sophisticated security frameworks to handle these distributed environments.
