Source URL: https://cloud.google.com/blog/products/storage-data-transfer/data-resilience-eons-approach–google-cloud-best-practices/
Source: Cloud Blog
Title: Automate data resilience at scale with Eon and Google Cloud Backup
Feedly Summary: Cloud backups were once considered as little more than an insurance policy. Now, your backups should do more! They should be autonomous, cost-efficient, and analytics-ready by default.
That’s why Eon built a platform purposefully aligned with Google Cloud to eliminate backup blind spots, simplify recovery, and unlock the value inside backup data without requiring teams to become policy experts or infrastructure wranglers.
Still, no matter what platform you use, it’s critical to understand what resilient cloud backup looks like and how to get there with Google Cloud’s native capabilities.
What makes cloud backup resilient?
Before diving into tooling, it’s worth asking: What does a resilient backup strategy look like in the cloud? In our work with Google Cloud users across industries, we’ve found five common criteria:
5 signs your backup posture may be at risk
You can’t easily see what’s backed up (or not)
Retention policies vary across projects and teams
Data is duplicated or stored inefficiently, driving up spend
Cloud ransomware protection is reactive rather than policy-driven
Recovery requires full restores even when you only need one object
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Best practices for data protection
Google Cloud provides foundational capabilities to protect your data if you configure and use them consistently. Here’s how to maximize native protection:
1. Versioning and retention: first lines of defense
Enable Object Versioning in Cloud Storage to retain multiple object versions, making it easier to recover from accidental deletions. Pair this with Retention Policies to enforce minimum storage lifetimes for regulatory or critical datasets.
Tip: Use Bucket Lock for write-once-read-many (WORM) protection in the areas where compliance matters most.
2. Monitor for gaps in coverage
Use native services like Cloud SQL backups, GKE snapshots, and Persistent Disk images, but be mindful that backup responsibilities can fall to different teams. Without centralized visibility, coverage becomes inconsistent.
Tip: Use Cloud Asset Inventory or scheduled BigQuery queries to audit coverage.
3. Design for granular recovery
Plan for partial restores since not everything needs a full rollback. Whether it’s a single BigQuery table or a specific Cloud Storage object, restoring only what you need saves time and cost.
Tip: Use Object Lifecycle Management to automatically transition older or less critical Cloud Storage objects to colder storage classes.
Automating the complexity away
Managing cloud backup at scale is hard to do manually. From onboarding new workloads to applying consistent policies, human-led approaches don’t scale well.
That’s why more teams are exploring autonomous Cloud Backup Posture Management (CBPM) solutions, like Eon, that detect new assets in real time, apply smart backup rules automatically, and enforce consistent protection across environments.
With Eon, you don’t have to tag resources or write custom scripts. Our platform classifies and protects your Google Cloud assets out of the box—whether you’re working with GKE, Cloud SQL, BigQuery, or another solution.
From backups to business insights
Traditionally, backup data was siloed, underused, and only meant to be retrieved in emergencies. But, increasingly, teams are unlocking that data to:
Run analysis directly on backups using BigQuery and Dataproc,
Feed training and monitoring pipelines via Vertex AI,
Deliver audit-ready dashboards with Looker, powered by backup snapshots.
With Eon, this is built-in. We transform backups into zero-ETL data lakes that reduce pipeline costs and provide immediate access to structured data with no reprocessing required.
What a “mature” backup posture looks like
The end goal for many cloud-native teams is not just to “have backups.” It’s to develop a resilient, intelligent backup strategy that adapts to scale and risk.
Here’s what that looks like:
Automated discovery of new resources
Policy-driven protection tailored to data type and criticality
Immutable backups with time-locked retention
Search-first recovery instead of full snapshot restores
Cost-aware tiering and storage deduplication
Eon helps Google Cloud users reach this level of maturity faster without the burden of custom tooling or constant policy updates.
Ready to simplify backup?
If your team spends hours managing scripts, storage tiers, or backup tags across cloud environments, it may be time to rethink your approach.
Eon was built to make cloud backup resilient, autonomous, and actually useful. From ransomware protection to instant, object-level recovery—and now, zero-ETL access to analytics—we’re here to help you unlock the full potential of your backup data.
Book a demo to see how Eon can modernize your Google Cloud data protection strategy.
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AI Summary and Description: Yes
Summary: The text discusses the evolution of cloud backup strategies, emphasizing the need for autonomous, resilient, and analytics-ready backups. It outlines the importance of effectively utilizing Google Cloud’s inherent capabilities and provides insights into common backup risks and best practices for data protection and management.
Detailed Description:
The content centers on modern cloud backup strategies, specifically tailored to enhance resilience, cost efficiency, and analytical value. Below are the key elements and insights:
– **Evolution of Cloud Backups**: Backups are transitioning from being mere safety nets (insurance policies) to proactive tools that provide value through analytics and automation.
– **Importance of Resilience**: The text identifies a resilient cloud backup strategy as vital for organizations leveraging Google Cloud. It emphasizes understanding what constitutes a robust backup posture.
– **Common Risks**: Five signs indicating a backup’s inadequacy include:
– Poor visibility of backed-up data.
– Inconsistent retention policies across different projects.
– Inefficient storage leading to unnecessary costs.
– Reactive ransomware protection strategies.
– Ineffective recovery processes requiring full restores.
– **Best Practices for Data Protection**: The content provides actionable strategies for enhancing backup processes:
– **Versioning and Retention**: Implement Object Versioning and enforce Retention Policies for regulatory compliance. Using Bucket Lock for critical datasets is also recommended.
– **Monitoring Coverage**: Encourage comprehensive coverage using Google Cloud’s native services, while maintaining centralized visibility to avoid inconsistencies.
– **Granular Recovery Planning**: Design systems to enable partial restores, judiciously utilizing resources.
– **Automation and Complexity Management**: The complexity of managing large-scale cloud backups leads many organizations to explore autonomous solutions like Cloud Backup Posture Management (CBPM). Eon’s platform helps automate detection, rule application, and consistent protection without extensive input from users.
– **Unlocking Backup Data**: The traditional view of backup data as merely recoverable storage is evolving. Organizations are increasingly leveraging backup data for direct analytics, feeding AI models, and generating business insights, illustrating a shift towards a more proactive use of backup data.
– **Mature Backup Posture**: A mature strategy incorporates:
– Automated resource discovery.
– Policy-driven protection adjusted for data criticality.
– Immutable backups secured with time-locked retention.
– Granular recovery mechanisms.
– Cost-saving measures through storage tiering and deduplication.
– **Eon’s Role**: Eon positions itself as a facilitator in achieving an intelligent backup strategy, emphasizing its capability to streamline processes and reduce manual overhead.
In conclusion, the text serves as a comprehensive guide for security and compliance professionals to rethink and modernize backup strategies within Google Cloud environments, ensuring they are resilient, autonomous, and structured for advanced analytics.