Data is the most valuable and riskiest asset for an enterprise, but in order to secure it, businesses must be aware of what they possess. For this reason, it’s crucial to be able to locate and make visible both structured and unstructured data across all of the company’s assets.
The most vital resource for the company is its data. Security teams must have complete visibility into where sensitive data is located in order to assure its security as more data and workloads migrate to the cloud. The traditional castle and moat security method will not work in modern settings. For data to remain secure wherever in the cloud, a data-first security approach must be used.
Here are four key reasons why organizations should think about making data the focal point of their security strategy rather than sticking with the traditional castle and moat model.
More services and granular data access are enabled via microservices
The golden rule in all ball games is always to keep an eye on the ball. The same principle holds true for cloud data security: Pay attention to the data. Because they were created with a three-tier design and a single data store, legacy applications found it simpler to do this. In that case, safeguarding just that one database was necessary for the protection of application data.
Numerous microservices with their own data stores that hold overlapping application data are used in modern app development. This dramatically makes data security more difficult, especially given that new features frequently bring forth additional microservices with more data storage. Additionally, the number of pathways to these data repositories quadratically grows over time. Another reason to use automation to help the team keep an eye on the data is that it is impossible to manually continuously evaluate the security posture of these expanding data repositories and access channels.
Increased data tracking and management are required by privacy laws
Cloud data security is significantly influenced by compliance. A few examples are personal health information for HIPAA, payment account information, sensitive authentication information for PCI DSS, and personally identifiable information for GDPR. The failure to protect sensitive data like this could result in severe consequences. Any protected data in the cloud environment should be automatically discovered and categorized thanks to a data-first security policy.
When data access is misconfigured, a cloud infrastructure’s dependability diminishes
A key component of data security is access authorization. It goes without saying that without access authorization, hackers can easily access the data. What happens, though, if authorization controls are misapplied? Did they get streamlined or eliminated to make DevOps use them more easily? Are controls consistently implemented across all cloud locations where data is stored? According to analysts, the majority of cloud breaches are caused by improper configuration of the cloud infrastructure (IaaS and PaaS). Wherever data is stored, access configurations for cloud data should be used correctly as part of a data-first security strategy.
An explosion of deployments and novel changes result from CI/CD
The demand to automate application development phases has been spurred by the ongoing shift in business needs. Continuous Integration and Continuous Delivery (CI/CD) expedited the development of apps and frequently made numerous changes to a codebase. Due to the lack of time for manual inspection, the danger of app defects and data leakage increases with continuous flow and increasing velocity of services and updates. DevOps‘ frequent use of instances and linkages to data repositories puts especially cloud data at risk, especially when testing apps employ temporary buckets or lost copies of data.
Once a company is aware of its data, it can use it to advance the company’s goals while also minimizing the dangers associated with it and empowering the company and the clients it serves.