Cloud Security Automation

Faced with an incursion of security threats, data pundits and information security experts must take on a new norm of operation. The pandemic-triggered digital revolution has resulted in an increased number of remote workers, cloud users, cloud service providers, substantive integration of information systems across an ecosystem of partners, and a breathtaking increase in the number of smart devices passing IoT information to the cloud. Nevertheless, whereas the massive networking of interdependent digital systems delivers speedy, high-profile connectivity, convenience, and comfort in our digital life aspects, it’s radically enlarging our attack surface for threat actors to exploit.

More cybercriminals and attack incidents have emerged – from those oblivious service vendors to disgruntled employees. They disrupt the seamless running of an enterprise with phishing, data exfiltration, DDoS attacks, virus, spyware, and ransomware. Witty hackers are even leveraging AI and ML algorithms to release more efficient onslaughts. The outcome is a stark apprehension for most business leaders: although the modern digital revolution is driving value, it’s creating new vulnerabilities as well. To solve this problem, information security professionals must adopt a more preventive, proactive security posture to protect their business operations. They should position their security teams for digital war: bring together multiple security tools to address the immediate skills gaps in the cybersecurity world. studies show most leading companies are adopting a forward-looking cyber-risk management approach that adopts AI-powered automation to drive enhanced insights, efficiency, and productivity.

AI for cloud cybersecurity 

Whereas cyber security is viewed as the biggest challenge to the adoption of cloud computing – in reality – it’s its greatest enabler when automated. Automation of cloud cyber security procedures enables users/businesses to collect the much-needed information to safeguard their cloud ecosystems and focus more on innovation and growth. Overall, most executives across the globe are embracing or are considering embracing artificial intelligence as a cybersecurity tool. A survey by the IBM Institute for Business Value (IBV) shows that 64% of business leaders globally have adopted AI for its security potential and 29% are contemplating its implementation.

The ‘64%” constitute executives who are presently piloting, executing, operating, or perfecting AI security technologies and are referred to as “AI Adopters.” The AI adopters cite the adoption of AI solutions have delivered consequential worthwhile results regarding their security needs including the capacity to triage Tier 1 threats efficaciously, identify zero-day cyber-attacks, minimize false positives, reduce manual errors, advance security measures, enhance compliance, enable consistent security operations, stamp out the noise that previously requires human expert, and most importantly create a robust cloud security posture.

Steps to a successful cloud security automation 

#1. Automate infrastructure buildout

The automation of infrastructure buildout relieves IT experts from labor-intensive tasks of manually setting up user access, security teams, firewalls, organizational networks, DNS namespace, log shipping, etc. This immensely minimizes the scope of security errors by data engineers. Besides, the executives need not fret about the most appropriate practices every time they turn a new incident, because only the scripts will be affected, not the situations.

#2. Automate script 

often, security issues like zero-day vulnerability require data engineers to work tirelessly to patch all servers manually. But script automation requires a single modification of the line in the manifests to guarantee the modernly unleashed version was operating. Essentially, automation script sources involve declarative management tools that catalyze the automatic arrangement of instances, virtual servers, and even typical metal servers. Immediately after a new instance is unleashed, the scripts prepare it for production, including security organization functions such as enabling central authentication and deploying IDS and 2FA.

#3. Automate Deployment

Whereas the automation of deployment is a remarkably important practice in DevOps Implementation, it enhances the security posture of an organization. For instance, if a zero-day attack strikes, deployment automation warrants changes executed on the DevOps tool script are automatically deployed across all instances and servers. A single data engineer can respond to these threats timely and effectively.

#4. Automate security monitoring

Today, where emerging technologies such as hybrid and multi-cloud ecosystems that support user applications are taking the cloud realm by storm, a single interface could be an exemplary solution for monitoring a whole infrastructure. This enables seamless security response in the event of attack or downtime. Automating security monitoring helps the IT team with the proper intelligence to address the problem and safeguard critical resources.

#5. Prepare for the automation prospects 

Research shows that in a few years, innovations such as hybrid environments and data balloons will dominate cyberspace, rendering manual security approaches obsolete. Thus, it’s now appropriate for enterprises to recruit a competent internal automation team.

Phases of Successful Cloud Security Automation plan 

#1. Monitor 

Cloud capability often scales to meet users’ operational requirements. Hence, businesses should monitor the task workflow to understand how each individual workflow is executed.

#2. Evaluate 

Before the actual cloud security automation, the user should know and prioritize the specific tasks that need automation. Keenly watching and monitoring the workflow aids data engineers to identify and evaluate these tasks such as reoccurring tasks, deployments, resource allocations, and creation of security regulations.  

#3. Analyze

IT teams should perform an in-depth analysis of all information gathered based on risk severity, i.e. high, medium and low, then give priority to the high-risk data, followed by medium and lastly low-risk data. Besides, in-depth analysis helps data pundits to perform controlled automation and understand its impact on informational infrastructure.

#4. Automate and Report

The outcome of the in-depth analysis can be leveraged to incorporate systems for workflow automation. Aftermath, the automation processes can be configured to generate a report that displays an overview of exact changes before and after the automation.

#5. Remediate 

This far, you’ll have gotten a clear picture of the entire cloud automation plan, regardless of whether you began automating complex or simple workloads. From this point, you can remediate and improve your overall security posture


Whereas automating cloud security offers myriads of enterprise benefits such as protection of cloud-based data with state-of-the-art security, delivery of highly-effective and reliable data services, seamless operation of web-based applications, reduced human error, and reduced time spent on security activities, it requires a huge investment in highly-skilled security pundits to set it up and manage. Notwithstanding, companies considering migrating to the cloud should partner with cloud providers that have deployed cloud security automation to stay agile, efficient, and responsive in the ever-evolving digital market.

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