Cloud Resilience Unlocked: The Essential Role of Data Lifecycle Management

Data Fragmentation and Visibility

In cloud environments, data often spreads across multiple platforms and regions to become accessible in richer, more collaborative ways. This leads to fragmentation and loss of visibility and control, which creates security gaps and makes it hard to track sensitive data.

Like most things in this industry, there is no silver bullet; however, using centralized cloud-first data management platforms and monitoring tools (like those offered by AWS, Microsoft, and Google) to maintain real-time visibility gets organizations to base camp on their data lifecycle journey. 

The key is to automate data classification as quickly as possible and use Cloud Access Security Brokers (CASBs) such as Microsoft Defender for Apps and Microsoft Purview's Data Loss Prevention (DLP) solution to ensure sensitive data is tracked and securely accessed.

Data Compliance and Regulatory Risks

Cloud data must comply (as should traditional data on-premise data) with regulations like GDPR, HIPAA, and PCI-DSS. Managing compliance is tough, as data is spread across regions with varying rules.

Consider creating a data classification matrix to map your data classification with compliance obligations. This gives you the rudimentary structure to align your cloud strategy with regulatory standards using compliance tools like Amazon Macie, Microsoft Purview, or Google Cloud's compliance solutions. 

Automate encryption for data at rest and in transit, then implement retention policies to ensure data is archived or deleted as required. 

Insufficient Data Encryption and Security Controls

Sensitive cloud data often lacks proper encryption, exposing it to breaches. Inadequate security extends to backups and archives, increasing risks.

Apply strong encryption standards like AES-256 for all data. Use built-in encryption tools like AWS KMS or Azure Key Vault to manage secrets dynamically and securely. Enforce Identity and Access Management (IDAM) policies with least-privilege access and make multi-factor authentication (MFA) mandatory for extra protection. 

Data loss prevention tooling, such as that found in Microsoft Purview, can support dynamic encryption of data as it crosses environmental boundaries from private to public and will automatically police the flow of data according to rules based on classification and compliance criteria.

 
Inefficient Data Retention and Disposal

Accumulating unnecessary data increases breach risks and storage costs. Improper disposal can expose sensitive information. Data may be the new oil, but like oil, when allowed to escape into the wrong environment, it can be toxic if not terminal.

Implement clear retention and disposal policies. A few good options include automated DLM solutions like AWS S3 lifecycle policies and those available in Microsoft Purview or Microsoft SharePoint that can move data to lower-cost storage or delete it after a specified period. Use secure deletion methods to prevent data recovery.

Data Access and Monitoring 

Controlling access to cloud data is difficult, especially in large environments with multiple users and devices. Unauthorized access and internal threats pose risks, especially the insider threat, which is magnified by the extended supply chains that exist in the Cloud with SaaS providers and API-based solutions.

Disciplined assurance practices place the responsibility on suppliers to show compliance can reduce the supply chain risk. They should be coupled with continuous monitoring and logging tools like AWS CloudTrail and Azure Sentinel to track access activity. 

Use AI-based anomaly detection for suspicious activity and regularly audit access controls to maintain security.