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Bridging the Security Skills Gap in a Cloud-First World

Organizations have been forced to approach workplace technology initiatives with greater speed and agility, quickly shifting to the cloud and embracing the DevSecOps methodology to stay ahead of security and compliance requirements while simultaneously supporting an ever-growing remote workforce. 

It’s no surprise that a recent IDC report found that the COVID-19 pandemic further accelerated the speed and scale at which organizations developed digital-native business applications and services. This is a direct result of organizations planning for a continued hybrid workforce in the post-pandemic world. In fact, by 2023, the analyst firm predicts that more than 500 million new logical applications will be created — equivalent to the number of applications developed in the past four decades. 

The business benefits of cloud and container utilization are clear: improved flexibility and agility, lower costs, and faster time to market. While businesses are increasingly seeking the business growth and innovation opportunities that cloud adoption provides, many discover it comes with a slew of new security and compliance challenges. The Verizon 2020 Data Breach Investigations Report found that cloud assets were involved in just under a quarter of all security breaches last year. Moral of the story? Cloud security must continue to evolve to keep pace with innovation. 

Furthermore, as organizations increasingly move to the cloud, security talent, especially cloud security, is in short supply. Seventy percent of cybersecurity professionals say their organizations have suffered some sort of a cybersecurity skills shortage, according to a report from ESG and ISSA. Additionally, more than 60% of organizations claim that security positions remain vacant for at least three months. And, cloud skills are exceptionally scarce, with 451 Research finding that 86% of companies are experiencing a skills gap in implementing cloud infrastructure. Although these statistics paint a dismal picture, there are some options to help organizations protect the cloud and avoid costly breaches. 

Option one: Organizations can and should rely upon cloud providers themselves, especially if starting from ground zero. Amazon, Microsoft, and Google all operate on a shared responsibility model to take on some of the burdens in securing data and applications from external threats. Generally speaking, this means that cloud providers secure their infrastructure against attacks, but customers are responsible for ensuring security and compliance for the workloads running on that infrastructure. Be advised, this is the bare minimum and should be implemented in tandem with larger-scale security protocols. 

Option two: Organizations can look to find an external security partner, like Threat Stack, to offload some or even all of their cloud security responsibilities. While it does add a line item to the IT budget, ultimately, it allows organizations to cut costs, strengthen security, and enable IT operations and security teams to direct internal resources to other strategic business initiatives. Outsourced security partners provide highly experienced cloud security experts, e.g., our 24/7/365 SOC team with Threat Stack Oversight, who are well-trained and laser-focused on understanding the signs and signals of both known risks and emerging threats.

Option three: Finally, many businesses use machine learning (ML) to augment their cloud security strategy. Just recently, Threat Stack unveiled the Threat Stack Cloud Security Platform® with ThreatML™ to enable customers to quickly uncover, assess, and respond to known and unknown risks. Generally, ML’s primary usage is associated with baselining normal behavior and automation event and alert correlation to uncover suspicious activities. ML algorithms can apply relevant context to alerts concerning security and compliance-related issues, anomalies, and non-compliant changes to the infrastructure and application stack by packaging related security activities together. As a result, security teams can reduce operational costs and allocate more of their time and resources to threat hunting and remediation efforts. 

This isn’t to say that ML will eliminate the need for human involvement in cloud security. Instead, it will make the work of security professionals more effective, including external security teams for businesses that use them. Just as with deep telemetry and extensive alerting rules, the insights produced by ML need to be placed into context by a human being, who will ultimately make decisions about the proper course of action. 

In closing, global spending on cloud infrastructure services grew 33% in Q2 2020 to $30 billion, increasing by $7.5 billion from the second quarter of 2019. As organizations continue to navigate the remote workforce and look towards implementing a hybrid model, the move towards more agile workplace technologies and processes will only increase. Without sound cloud security and compliance strategies in place, organizations will increase their risk profile as they increase their cloud consumption, opening themselves to potentially devastating attacks and breaches. Partnering with a strategic security partner like Threat Stack ensures organizations can take advantage of the many unique capabilities and benefits of modern computing environments without incurring additional risk.