Irrespective of industry, the adoption of multicloud strategies is becoming increasingly prevalent. Organizations are drawn into multicloud ecosystems either to enhance flexibility by collaborating with multiple Cloud Service Providers (CSPs) or due to mergers and acquisitions.
While individual clouds are typically designed with robust security measures, the crux of the matter lies in what is known as “security at the seams.” This term encapsulates the vulnerabilities that emerge at the intersections of different clouds, where they link with each other or connect to local servers and remote services. To fully harness the benefits of multicloud environments, data must flow seamlessly and securely, and applications connecting to multiple clouds must be fortified with robust security measures. This necessitates technical considerations such as data encryption and privilege management.
Another crucial aspect is the deployment of cloud-native security tools wherever possible. While there may be a temptation to rely on legacy tools that have served adequately in the past, especially in the context of a multicloud environment with various CSPs, this approach falls short. Legacy tools are insufficient for securing a single cloud, let alone a multicloud environment. Instead, the adoption of modern, cloud-native security tools should be an integral part of the cloud migration strategy. Multicloud security monitoring, in particular, must leverage cloud-native tools to effectively safeguard an organization’s data. Remarkably, cloud-aligned cybersecurity solutions can prove to be more cost-effective, easier to manage, and more reliable than attempting to achieve the same level of security with legacy tools across multiple clouds.
Open source technologies play a pivotal role in enabling efficient workflows and data movement within multicloud setups. In an IDC whitepaper, organizations can enhance data governance and mobility capabilities by embracing open-source strategies.
The zero-trust security model, for instance, aligns well with the defense of complex cloud networks. In this model, malicious actors are constrained in their ability to exploit vulnerabilities within the cloud environment, limiting the scope and impact of intrusions.
The increasing use of AI and machine learning to automate security tasks represents an exciting frontier in multicloud security. AI-driven security tools are ushering in the era of “invisible security,” where data and networks remain secure with minimal human intervention. This automation enables security teams to redirect their focus toward critical tasks such as security assessment, auditing, training, and promoting security awareness throughout the organization.