What Is Cloud Encryption?

Encryption is essential for securing sensitive cloud data, but implementation isn’t always straightforward. The problem is ensuring encryption remains seamless across a fragmented, multi-cloud environment where data moves between services, regions, and tenants.

Misconfigurations, inconsistent key management, and performance trade-offs often turn cloud encryption into an operational bottleneck and an area of risk rather than an enabler of security. There are also compliance ramifications for some encryption failures. But does it have to be that way? After all, cloud encryption is a foundational cloud infrastructure security measure to protect data at rest, in transit, and in use across cloud environments — a core component of compliance with security policies and mitigating unauthorized access risks.

This article breaks down the fundamentals of cloud encryption along with suggestions and actionable practices for implementing cloud encryption at enterprise scale. 

Understanding Cloud Encryption Fundamentals

Cloud encryption protects data by converting it into unreadable ciphertext so that only authorized users with decryption keys can access it. It secures data at rest, in transit, and in use across cloud environments to help prevent unauthorized access, data breaches, and compliance violations.

Cloud encryption isn’t just about securing data, it’s also about managing encryption keys effectively. Cloud providers offer Key Management Systems (KMS) to control key generation, rotation, and access. Or, companies can use their own. However, misconfigured key policies, improper key storage, and weak entropy sources can undermine encryption’s effectiveness. Beyond growing complexity, teams face:

•  Shared responsibility gaps
• Key proliferation across services
• Misconfigured access controls
• Risk of cloud API exploits
• Inadequate key rotation and revocation
• Cloud-native threats like side-channel attacks
• Backup and snapshot exposure
• Human error and insider threats

Doubtlessly, cloud environments make encryption more complex. Unlike traditional on-premise storage, where organizations control their own encryption mechanisms, multi-cloud and SaaS models require businesses to balance security, access control, and cloud provider trust. The shift toward encryption by default is an acknowledgment that perimeter security is no longer enough. 

Benefits of Cloud Encryption

With the added challenges and investment, why work to maintain encryption in the cloud? In short, organizations can’t give up either cloud use or cloud encryption.

By 2030, the cloud market is expected to hit $1.5 trillion as cloud computing — and the flexibility and scalability that come with it — become crucial components of competitiveness.

With cloud computing has come the specter of distributed workloads and data. While there are security benefits inherent in that model, there is also a broad attack surface and less visibility into where resources are located and how they are accessed. For example, assumptions about the shared responsibility model can lead to neglected data encryption and, hence, the snowballing belief that the cloud is insecure. 

The truth: the tools needed to secure cloud data, and successfully encrypt data, are within reach. And they come with multiple benefits. Data encryption results in:

Limited Blast Radius of a Breach

Even if attackers infiltrate cloud storage, databases, or backups, encryption prevents them from accessing sensitive data, drastically reducing the damage they can do. Even when customer data is exposed, the breach won’t result in leaked credit card details or personal data.

Business Continuity and Cyber Resilience

Encrypted data gives organizations greater protection against ransomware, insider threats, and accidental leaks. When exposed files are encrypted with securely stored keys, the company restores operations quickly without paying a ransom.

Enables Safer Multi-Cloud and Hybrid Operations

As businesses expand across multiple cloud providers, encryption means data sovereignty and secure interoperability. It prevents vendor lock-in while maintaining security across AWS, Azure, and on-prem environments.

Reduced Legal and Compliance Liability

Encryption helps businesses avoid regulatory fines, legal consequences, and even breach reporting by ensuring data is protected. If encrypted data is stolen but remains unreadable, it may not trigger mandatory breach disclosure laws. That maintains consumer trust.

Breaking Down Cloud Encryption Architecture

Encryption’s benefits are plentiful in a cloud environment, but to truly secure cloud data, organizations must understand not just why encryption matters but how to architect it correctly across workloads.

Ultimately, cloud encryption goes beyond merely scrambling data to a strategic architecture that ensures confidentiality, integrity, and controlled access across cloud environments. To implement encryption effectively, organizations need to understand encryption types, cloud provider implementations, key management, and identity-based access control. 

Here are key actionable tips.

Encrypting Data at Rest

Encryption at rest ensures that data stored in cloud environments remains unreadable without the appropriate decryption key. This includes:

• Cloud Object Storage Encryption: AWS S3, Azure Blob Storage, and Google Cloud Storage all support server-side encryption (SSE) with AES-256 by default.
• Database Encryption: Cloud-native databases like AWS RDS, Azure SQL, and Google Cloud Spanner encrypt data at rest using transparent data encryption (TDE) or customer-supplied encryption keys (CSEK).
• Disk & Volume Encryption: Cloud providers allow full disk encryption (FDE) for virtual machines and persistent storage volumes (e.g., AWS EBS, Azure Managed Disks, GCP Persistent Disks).
• Backup and Snapshot Encryption: Backups and point-in-time snapshots contain sensitive data but may not inherit encryption settings from production environments. If an unencrypted snapshot is exfiltrated, attackers can restore it elsewhere and access plaintext data. 
• Hybrid and Multi-Cloud Encryption: Organizations operating across multiple cloud providers or on-prem environments face inconsistent encryption enforcement if policies aren’t standardized. 

Encryption at rest is widely used and required by compliance mandates like PCI DSS and GDPR. However, it’s important to note that if an attacker gains access to decryption keys through IAM role abuse or misconfigurations, encryption won’t prevent data exposure.

So, what implementation considerations and best practices govern securing data for different types of encryption?

Encryption Type	Primary Security Benefits	Potential Risks and Misconfigurations	Best Practices
Cloud Object Storage Encryption	Protects stored files from unauthorized access and exfiltration.	Misconfigured bucket permissions can expose unencrypted files.	Enforce SSE by default, restrict public access, and monitor access logs.
Database Encryption (TDE, CSEK)	Encrypts structured data within managed cloud databases.	Attackers with privileged access can still query decrypted data.	Use customer-supplied keys (CSEK) for sensitive data, restrict admin roles.
Disk & Volume Encryption (FDE)	Secures virtual machine storage and persistent disks.	If a VM is compromised, decryption keys may be accessible in memory.	Require strong IAM controls and enforce key rotation policies.
Backup & Snapshot Encryption	Ensures backups and point-in-time snapshots remain protected.	Unencrypted snapshots can be exfiltrated and restored elsewhere.	Apply the same encryption policies as production data and monitor access.
Hybrid & Multi-Cloud Encryption	Maintains security across cloud providers and on-prem systems.	Inconsistent key management across environments increases attack surface.	Standardize encryption policies and centralize key management.

Encrypting Data in Transit

Encryption in transit secures data moving between users, applications, or cloud services to prevent eavesdropping and MITM (man-in-the-middle) attacks. This includes:

• Transport Layer Security (TLS 1.3): Encrypts web traffic (HTTPS), API calls, and cloud-to-cloud communication.
• VPN & Secure Tunnels: Cloud providers offer encrypted IPsec VPNs and AWS PrivateLink/Azure Private Link to secure connections between cloud workloads.
• Mutual TLS (mTLS): Ensures both clients and servers authenticate each other, commonly used in zero-trust architectures and Kubernetes service mesh encryption.
• API Encryption and Signing: Protects sensitive API data in transit by encrypting requests and responses. TLS alone isn’t enough if API payloads are intercepted — HMAC signing or JWT-based encryption ensures message integrity and authenticity.
• Cloud-Native Service Encryption: Many cloud services, such as AWS KMS-integrated services and Azure Service Bus, offer built-in encryption for inter-service communication. However, default settings may allow unencrypted data exchange within provider networks unless explicitly configured.

Misconfigurations here (e.g., weak TLS versions, expired certificates) can leave communication channels exposed, but these issues are rarer than those that can affect encryption at rest.

Encryption can be managed by the cloud provider (server-side encryption) or the customer (client-side encryption). In Server-Side Encryption (SSE), the cloud provider manages encryption and decryption transparently. In Client-Side Encryption (CSE), The customer encrypts data before sending it to the cloud, keeping full control over keys. A risk when maintaining full control is failure to enforce key rotation policies and leaving stale or compromised keys active for months.

On a related point, encryption is meaningless if anyone can decrypt the data. Attackers don’t need to break strong AES-256 encryption if they can just steal credentials or exploit weak IAM policies. A threat actor doesn’t need to break encryption if they can assume an admin role and decrypt data directly using the account’s privileges (the 2019 Capital One data breach served as a prime example of this). This risk calls for identity controls like:

• Only explicitly authorized users and workloads should have decryption permissions. IAM roles must be continuously audited to prevent privilege creep.
• Tracking API calls to detect anomalous key decryption attempts, excessive privilege use, or lateral movement.
• Authenticating decryption requests with MFA and restricting permissions to specific devices, geolocations, and risk levels.

Let’s look at actionable tips for encryption of data in transit:

Encryption Method	Primary Security Benefits	Common Risks & Misconfigurations	Best Practices
TLS 1.3 (Transport Layer Security)	Encrypts web traffic, APIs, and cloud-to-cloud communication to prevent eavesdropping.	Using outdated versions (e.g., TLS 1.0/1.1) leaves connections vulnerable to downgrade attacks.	Enforce TLS 1.3 with strong cipher suites and disable deprecated versions.
VPN & Secure Tunnels	Encrypts network traffic between on-prem and cloud workloads, reducing exposure.	Misconfigured VPNs (e.g., split tunneling) can route traffic through unencrypted channels.	Enforce full-tunnel VPNs for sensitive workloads and rotate VPN credentials regularly.
Mutual TLS (mTLS)	Provides end-to-end encryption with authentication of both parties, commonly used in zero-trust.	Improper certificate lifecycle management can lead to expired or compromised certs.	Automate certificate renewal and use short-lived certificates to reduce attack exposure.
API Encryption & Signing	Ensures API requests and responses remain confidential and tamper-proof.	APIs transmitting sensitive data without encryption or using weak JWT signing can be intercepted.	Require TLS for all API endpoints, enforce HMAC/JWT signing, and audit API keys for exposure.
Cloud-Native Service Encryption	Securely encrypts internal cloud communications (e.g., AWS KMS-integrated services, Azure Service Bus).	Default settings may allow unencrypted communication within cloud provider networks.	Require explicit encryption settings in cloud service configurations.
Key Management for In-Transit Data	Prevents unauthorized decryption by enforcing controlled access to encryption keys.	Overly permissive IAM roles can allow unintended decryption by internal users or attackers.	Apply least privilege principles, track decryption attempts, and enforce key rotation policies.

Encrypting Data in Use

The third category of data that is neither at rest nor in transit is “data in use.” That’s data that is actively being processed, computed, or analyzed in memory by an application, virtual machine, or cloud service. 

Unlike data at rest or in transit, data in use is often vulnerable because it exists in plaintext in memory during processing. Encryption in use, also known as confidential computing, helps mitigate this risk by keeping data encrypted even while it’s being processed.

Key approaches include:

• Trusted Execution Environments (TEEs): Hardware-based enclaves that isolate sensitive computations, preventing unauthorized access (e.g., Intel SGX, AMD SEV, AWS Nitro Enclaves).
• Homomorphic Encryption: A cryptographic method that allows computation on encrypted data without decrypting it, ensuring privacy in sensitive workloads.
• Secure Multiparty Computation (SMPC): A technique that enables multiple parties to compute functions on encrypted data without revealing their inputs.
• Confidential VMs and Containers: Cloud providers offer confidential computing instances that use hardware encryption to isolate workloads from the hypervisor (e.g., Azure Confidential Computing, Google Confidential VMs).
• In-Memory Encryption: Encrypts sensitive data while it resides in RAM to prevent attacks like memory scraping, side-channel exploits, and cold boot attacks.
• Data Tokenization During Processing: Instead of encrypting data, this method replaces sensitive values with non-sensitive tokens, which are mapped back to the original values in a secure vault, reducing exposure during processing

Here are actionable steps for each:

Encryption Method	Primary Security Benefits	Common Risks & Misconfigurations	Best Practices
Trusted Execution Environments (TEEs)	Isolates sensitive computations inside secure enclaves, protecting data from unauthorized access.	TEEs require specific hardware (e.g., Intel SGX, AMD SEV), and misconfigurations can expose data.	Use TEEs only for critical workloads and enforce strict access controls.
Homomorphic Encryption (HE)	Allows computations on encrypted data without decrypting it, ensuring end-to-end confidentiality.	Extremely computationally expensive, limiting real-time processing feasibility.	Use HE for specific privacy-sensitive applications (e.g., medical data, financial transactions).
Secure Multiparty Computation (SMPC)	Enables multiple parties to compute on encrypted data without sharing raw inputs to limit data exposure risks.	Requires high network and computational overhead, making it impractical for large-scale operations.	Implement for collaborative analytics where privacy between participants is most important.
Confidential VMs and Containers	Encrypts memory and CPU states while running cloud workloads to limit data exposure to the hypervisor.	Not all cloud workloads support confidential VMs, and improper encryption key handling can still expose data.	Use Azure Confidential Computing, Google Confidential VMs, AWS Nitro Enclaves where supported.
In-Memory Encryption	Protects data while it is actively used in RAM. That prevents attacks like memory scraping or cold boot attacks.	Performance impact due to encryption overhead; some implementations only encrypt certain memory segments.	Apply runtime memory encryption selectively for sensitive data.
Data Tokenization During Processing	Replaces sensitive data with tokens before processing, reducing risk if data is accessed.	Tokens must be mapped back to original data securely; weak tokenization schemes can be reversible.	Use FIPS 140-2 compliant tokenization methods and secure token vaults.

Critical Cloud Encryption Challenges — And Solutions

Encryption best practices go beyond securing data at rest or in transit. They also include overcoming the operational, compliance, and performance challenges that come with cloud-scale encryption. 

Many organizations struggle with fragmented encryption strategies across multiple cloud providers, the complexity of managing and rotating encryption keys, the tradeoff between security and performance, and meeting compliance mandates without overwhelming security teams. For these reasons, there’s no such thing as simply “enabling encryption.” The reality is that security teams need automation, visibility, and policy enforcement to make sure encryption actually works as intended across a dynamic cloud environment.

Let’s break down critical cloud encryption challenges and the key solutions that make encryption practical, scalable, and enforceable in complex cloud environments.

Challenge	Solution
Data Fragmentation Across Clouds	Adopt a multi-cloud encryption strategy using customer-managed keys (CMK) with consistent policies across AWS, Azure, and GCP. Use cross-cloud monitoring to detect unencrypted data flows. Enforce encryption policy automation to prevent misconfigurations.
Key Rotation Complexities	Automate key rotation with cloud-native KMS policies, but supplement with external key rotation logic where needed. Implement ephemeral key generation for short-lived workloads and use key access monitoring to detect stale or overprivileged keys.
Performance Impact Considerations	Use hardware acceleration (AES-NI, HSM-backed encryption) to minimize CPU overhead. Implement selective encryption strategies — prioritizing sensitive data while avoiding unnecessary encryption of low-risk data. Use inline encryption at the storage layer to reduce application-level latency.
Compliance Requirements	Map encryption policies to regulatory frameworks (GDPR, PCI DSS, HIPAA) and enforce compliance automation with encryption logs and audit trails and dashboards that track compliance requirements with controls. Adopt policy-as-code approaches to ensure encryption requirements are met dynamically across evolving workloads.

Building An Advanced Cloud Encryption Strategy

As organizations expand across multi-cloud environments, they’ll need to consider implementing encryption, even with challenges, at scale. And encryption at scale isn’t just about securing data — it’s about keeping up with the speed and complexity of modern cloud environments. Multi-cloud deployments, ephemeral workloads, and decentralized access models make traditional encryption strategies difficult to enforce consistently. 

Teams will need an adaptive, identity-driven approach to avoid encryption that’s a patchwork of policies. Further, if encryption is to remain effective, teams will need to unify key management, enforce least-privilege access, and automate compliance monitoring.

Let’s talk about the key steps they’ll take.

Multi-Cloud Key Management

The multi-cloud strategies businesses often use today complicate this already complex area even further. Organizations often need to balance provider-native KMS (AWS KMS, Azure Key Vault, Google Cloud KMS), Bring Your Own Key (BYOK) models, and

externally managed HSM-backed keys. 

A fragmented encryption approach leads to inconsistent security policies, operational complexity, and key synchronization issues across different clouds.

Best practices here include:

• Use multi-cloud key management platforms to unify key visibility and enforce consistent rotation, expiration, and revocation policies.
• Avoiding cloud provider lock-in by using customer-supplied encryption keys.
• Restricting encryption key access to specific workloads, environments, and user roles, ensuring that overprivileged IAM roles cannot decrypt data globally. 

Identity-Driven Encryption

Without strict identity governance, encryption becomes a false sense of security — any overprivileged user or application with decryption access could expose sensitive data.

Aside from least privilege access, best practices include using temporary decryption permissions so that access expires after a set period rather than remaining persistently available, and continuously analyzing decryption attempts, API calls, and access patterns to detect anomalies in how users access encrypted data.

This identity-driven idea can integrate more broadly into a zero-trust model. Encryption must be tightly integrated into a model where data access, decryption, and policy enforcement happen in real time based on contextual security decisions. Extra strategies here include using adaptive access controls (risk-based MFA, conditional policies) to ensure encryption keys are only used when the access context is verified and trusted, and integrating encryption with software-defined perimeters (SDP) and microsegmentation to limit lateral movement in the event of key compromise.

Automated Compliance Monitoring

Beyond its value as a security control for protecting data, encryption is a compliance requirement. Organizations must ensure that encryption policies align with GDPR, HIPAA, PCI DSS, and other regulatory standards. Manually verifying proper coverage for encryption in line with regulations is a time-consuming task ripe for automation.

Key actions here include:

• Using Infrastructure as Code (IaC) security scans to detect unencrypted cloud storage, weak key policies, and untracked decryption operations.
• Maintaining an immutable audit trail of all encryption and decryption events to simplify regulatory audits and incident investigations.
• Automated policy enforcement to block workloads that don’t meet encryption compliance rules (e.g., unencrypted object storage or databases).

Implementing Enterprise-Grade Encryption

At an enterprise scale, cloud encryption becomes about operationalizing encryption in a way that is scalable, manageable, and resilient (on top of its primary aim of securing data). Organizations must encrypt data consistently across multi-cloud environments, enforce granular policies, and continuously monitor encryption health without introducing bottlenecks that slow down business operations.

Standardizing Encryption Across Cloud and Hybrid Environments

Encryption policies must be automated, enforceable, and adaptable to different workloads. Without clear, codified encryption policies, enterprises risk inconsistent encryption practices that leave data vulnerable. 

Not all data requires the same encryption strength. Classifying data into tiers (e.g., public, confidential, highly sensitive) and using encryption accordingly (AES-256 for sensitive workloads, SHA-512 for integrity checks, etc.) is a smarter way of doing things. Using solutions to enforce encryption requirements dynamically prevents non-compliant workloads from being deployed. Many enterprises encrypt production data but fail to encrypt snapshots, backups, and archive storage—a major blind spot that needs addressing.

Managing Secrets at Scale

A common enterprise mistake is over-reliance on long-lived API keys and persistent encryption credentials. Attackers who steal a single exposed API key can bypass encryption entirely. Enterprises must work to prevent key sprawl, enforce strict key governance, and ensure API tokens and credentials are stored securely.

Best practices here include:

• Using a Dedicated Secrets Management Solution to avoid hardcoding encryption keys in apps. AWS Secrets Manager, Azure Key Vault, HashiCorp Vault, or CyberArk provide centralized secrets storage and access control.
• Automate keying rotation via KMS (AWS, Azure, GCP) or external HSMs to reduce the risk of compromised credentials being exploited.
• Instead of long-lived encryption keys, generating on-demand, time-limited decryption tokens for serverless functions, ephemeral containers, and auto-scaling cloud workloads.

Monitoring Encryption Status

A large-scale encryption strategy is only as strong as its monitoring framework. Many enterprises fail to track encryption coverage comprehensively, which can lead to blind spots where some data might be unencrypted. 

Real-time cloud security posture management (CSPM) can detect unencrypted storage buckets, databases, and improperly stored encryption keys. Tracking decryption requests, key rotations, and unusual API activity helps detect suspicious encryption bypass attempts. CI/CD pipeline scans can flag changes to encryption settings before they are deployed to production.

Upwind Unifies Encryption Policies Across Clouds

Encryption is non-negotiable in securing cloud data, but encryption is not a standalone solution. Without continuous monitoring and strong identity controls, even encrypted data can be vulnerable. Misconfigurations, overprivileged access, and weak compliance enforcement can turn encryption into a false sense of security rather than an effective last line of defense.

That’s where Upwind comes in. With our runtime-powered comprehensive CNAPP, teams get real-time monitoring, automated compliance enforcement, and multi-cloud security controls that help organizations:

• Monitor encryption policies across AWS, Azure, and GCP, detecting gaps, misconfigurations, and unauthorized decryption attempts in real time.
• Ensure cloud workloads consistently meet encryption mandates like GDPR, PCI DSS, HIPAA, and FedRAMP through policy-driven enforcement and automated audits.
•  Standardize encryption policies across all cloud environments, prevent inconsistent encryption settings, and detect cross-cloud drift that could expose sensitive data.

Get a demo here. 

Frequently Asked Questions

What’s the difference between encryption at rest and in transit?

Encryption at rest protects stored data (e.g., databases, object storage) using AES-256 or RSA, ensuring data remains unreadable if accessed improperly. Targets include unauthorized access, lost/stolen storage devices, and exposed backup snapshots.

Encryption in transit secures data moving between systems using TLS or IPsec to prevent interception during transmission. Both are essential for proper data security. Risks involve man-in-the-middle (MITM) attacks, sniffing, and session hijacking.

How does cloud encryption impact application performance?

Encryption can introduce latency and CPU overhead, especially during encryption/decryption operations. But the impact depends on:

• Encryption method 
• Key management complexity
• Hardware acceleration 

How should teams decide? Here’s a quick guide: 

For storage-heavy workloads, use AES-NI accelerated disk encryption to reduce read/write latency.

For high-traffic apps, offload TLS encryption to dedicated hardware or cloud-native security services.

In API-heavy environments, optimize key storage and API signing methods to prevent unnecessary cryptographic load.

In advanced security use cases, from confidential computing to homomorphic encryption, expect significant performance trade-offs without purpose-built hardware.

When should organizations implement client-side encryption?

Organizations should use client-side encryption (CSE) when:

• They require full control over encryption keys
• Teed to meet strict regulatory requirements
• They want to prevent cloud providers from accessing sensitive data. It’s commonly used in BYOK (Bring Your Own Key) and confidential computing models
• They want consistent encryption across cloud providers or between on-prem and cloud or to guard against accidental exposure if cloud-side encryption settings are misconfigured.

What encryption standards should businesses use?

Choosing the right encryption standard depends on data sensitivity, compliance mandates, and performance considerations. However, there are some best practices that all organizations can use as starting points.

In general, businesses should use AES-256 for data at rest, TLS 1.3 for data in transit, and SHA-512 for data integrity verification. For compliance guidance, they should follow FIPS 140-2 (U.S.), ISO/IEC 27001 (global), and PCI DSS (financial transactions).