As you may have guessed from the name, a multi-cloud environment uses more than one cloud from different cloud service providers. This article will give you insights into multi-cloud environments, how they function, and what challenges they pose in terms of data security.
Here's a list of topics that you'll learn about:
Let's start from the top.
A multi-cloud environment lets companies get the utmost value out of their cloud environments. Just as a company can choose from different public clouds such as AWS, Google Cloud platforms, and private cloud facilities, there are a myriad of cloud data platforms including Snowflake, Databricks and various AWS services including Redshift, S3, and DynamoDB. It’s very common for organizations to select multiple cloud repositories to optimize cost, performance, and scale for various use cases.
If your organization decides to use multiple cloud data environments, your data management pipeline will contain a lot of moving parts. And that means more data vulnerability issues, plus higher chances of cyberattacks and threats. This increased complexity means that you'll require a more robust data security framework.
Multi-cloud data security requires an integrated data security framework and a mindset of Data Centric Security. This framework has to address data access, data vulnerability issues, data breaches, data loss, cyberattacks, and more. Careful attention to these issues ensures security across all the different cloud environments the organization is using—public clouds as well as private.
Why should you care about this issue? Let's look at three reasons.
The increase in the number of cloud data environments provides variability and flexibility, of course. But it also increases the risks and threats associated with data security. Due to a more distributed and bigger attack surface, the risk of cyberattacks, data leakage, and breaches increases. Also, monitoring the data infrastructure across the different cloud environments becomes more complex.
Each of the cloud data service providers within the organization's multi-cloud platform provides different controls and tools related to security. The different tools are decentralized and specific to each cloud environment. There is no industry standard today on how data security has to be implemented across cloud data platforms.
A holistic and integrated data security governance framework is of the utmost importance in order to identify any data access and security risks. Such a framework allows organizations to make informed decisions in response to any data security vulnerabilities.
Misconfiguration of security settings is one of the most common reasons behind security breaches. Since a multi-cloud environment is more complex, it's crucial to maintain consistency of security protocols across all cloud platforms.
What are some key challenges associated with designing a multi-cloud data security framework?
Now that you better understand the particular challenges of a multi-cloud system, let's explore how to keep that system running smoothly.
Design and impose standardized data security configurations for all your cloud platforms. Ensure that these data security policies are standardized and span the various security controls across independent cloud platforms. Since each cloud provider may have different security measures, it's crucial to have a standardized framework for all clouds to ensure consistency. This will remove any gaps between security measures across the different cloud data platforms. Furthermore, make sure to add specific security policies for each dataset based on the needs of each application or service.
Several automated tools are available to help you consolidate and combine user access systems and authorization protocols from all cloud platforms. Moreover, you can also use cloud management tools to automate and manage frequent data backups. Ensuring timely data backups and seamless integration of data from all cloud platforms prevents issues such as data loss.
Setting up a unified dashboard lets you track and monitor all your cloud platforms and all applications hosted on them. Having a holistic view of your organization can help you make informed decisions about potential cyberattacks and data threats.
Most misconfiguration and ineffective data access policy errors happen because of human errors. Complex multi-cloud environments require rigorous automation in provisioning and monitoring. Automation enables 24-7 security alerts and notifications, which are crucial in timely detection of data security threats. Moreover, automation is key to ensure a culture of continuous development and deployment.
Every service provider offers different security measures and features. Assuming that all your cloud environments have the same inherent level of data security can make your organization vulnerable to security threats. Therefore, it's crucial to identify which cloud data platforms need more or fewer safety protocols based on business risk. This can also be useful if your organization wants to have extra security measures for highly sensitive and confidential data, such as credit card numbers or medical data.
Perform regular audits and compile monthly reports on what access permissions your staff members have. What kinds of data-sharing activities take place within and outside the organization? Regularly scheduled audits are crucial to prevent insider attacks and vulnerabilities within the organization's network. Additionally, make sure you’re continuously monitoring your cloud data environments to identify any unnecessary access permissions.
At times of cyberattacks or other data threats, logs can provide evidence of who accessed your servers and when. What's more, real-time logs can help you identify and locate any attacks. However, it's important to ensure logs are collected and managed efficiently. Following a robust log management practice can help you protect your organization's data.
A zero-trust approach for granting access to data will help reduce data exfiltration threats, data mis-use by insiders, and avoid compliance violations. A framework to provision and manage data access policies across multi-clouds will simplify and allow faster collaboration between data owners and information security managers.
All cloud platforms are vulnerable to cyberattacks and hackers that can gain access to APIs for all cloud platforms. Therefore, it makes sense to overlay your security layers with simple yet effective measures such as multi-factor authentication, one-time passwords, granular access controls, and data encryption. Although most cloud platforms come with data encryption methods, adding two layers of data encryption makes them less accessible to hackers.
Multi-cloud data security management is complicated and requires a robust framework. Without a proper Data Security Governance framework, the organization can lose its reputation and credibility.
TrustLogix offers a unified approach to deliver Data Centric Security across all platforms. The product provides total visibility into data access risks and secures the entire data pipeline—from ingestion to usage. Check out our demo to learn more or subscribe to our blog for staying on top of best practices and customer use cases.