Let’s say you’re a DevOps Engineer at a SaaS company managing the infrastructure. One day, AWS’s us-east-1 region suddenly goes down, and an Amazon RDS database is unavailable. This database holds user credentials, and with the database down, users can't access the application. In this situation, you need to quickly recover your database. In multi cloud disaster recovery, it gets a bit tricky. You need to make sure that data is synced across AWS, Azure, and GCP, check that backups are up-to-date, and switch services from one cloud to another if needed. According to a report by Gartner, about 70% of organizations now use cloud-based solutions in their business continuity (BC) and multi-cloud DR plans. This shows a major move towards cloud disaster recovery using automated disaster recovery to build stronger resilience. Without an automated cloud disaster recovery plan for cloud services, it could take hours or even days to restore everything, which will cause delays and prevent users from getting their work done. 

This is where an automated disaster recovery plan can help. In this blog, we’ll show you how to set up a simple multi-cloud DR plan for your infrastructure hosted in multiple cloud services. We’ll explain how to automate backups, switch to backup systems if something goes wrong, and keep data consistent across AWS, Azure, and GCP.

Understanding Disaster Recovery in Multi-Cloud Environments

Disaster recovery or DR is the process of restoring your infrastructure, data, and applications after any unexpected disruption, such as a cloud service outage, cybersecurity breach, or hardware malfunction. The goal of disaster recovery is simply to make sure that your resources, such as instances, databases, data centers, and applications, are restored to full functionality as quickly as possible, with minimal impact on the users and business operations.

For organizations that are working on multiple cloud providers like AWS, Azure, and GCP, disaster recovery becomes more challenging for them. Each cloud platform has its own set of tools and services for backup, failover, and disaster recovery strategies. When something goes wrong, such as a region failure, data corruption, or service disruption, coordinating between these cloud providers to restore the data and services is difficult.

What are the challenges in Multi-Cloud DR?

Let’s take a closer look at the challenges that organizations face within a multi-cloud disaster recovery strategy:

• Managing Different Tools: Each cloud provider has its own disaster recovery tools and services. For example, AWS offers AWS Backup and Elastic Disaster Recovery, Azure has Azure Backup and Azure Site Recovery, and GCP provides Filestore and Cloud Storage for backup and recovery. Managing these tools across multiple cloud platforms requires some careful coordination between your IT and DevOps teams to make sure that all resources, such as databases, virtual machines, and storage, are backed up, monitored, and ready for the recovery process. Using different tools for each cloud makes it more challenging for the DevOps teams to create a consistent and efficient recovery process.
• Compliance Across Multi-Cloud: With multiple cloud providers, ensuring compliance is followed across all these cloud platforms becomes a bit of a challenge. Different clouds may have different regulatory requirements and compliance certifications. For example, AWS and Azure may have distinct approaches to GDPR, HIPAA, or SOC 2 compliance, and these differences need to be addressed when managing disaster recovery. Keeping your infrastructure compliant while meeting recovery objectives is also important to avoid any legal or operational risks during a disaster.
• Navigating Cost Estimation Across Multi-Cloud: Managing disaster recovery across different cloud platforms can also lead to complexities in cost estimation. Each cloud provider has its own pricing structure for storage, backup, and recovery services. It’s important to understand and predict the costs involved in the disaster recovery process across AWS, Azure, and GCP to avoid any unexpected expenses. Otherwise, it can result in inefficient resource use and higher costs during a disaster recovery process.
• Data Syncing Across Clouds: When your infrastructure is spread across multiple cloud providers, it becomes even more important to make sure that your data is consistent across all these cloud platforms. This means making sure that your backups are up-to-date. For example, if your databases are in Amazon RDS and your files are in Azure Blob Storage, you need to make sure that both of them are regularly backed up. Any data changes in one cloud, like a new file uploaded to Azure or an update to your AWS database, should be reflected in the other as well. Without this type of synchronization, you could easily lose your recent updates and face problems when trying to restore your data. And keeping backups updated and in sync across all the cloud services being used is also important for multi cloud disaster recovery.
• Ensuring All Services Are Available: When your services are spread across different cloud providers, it helps to keep everything running smoothly, even if one cloud experiences an issue. For example, you might use AWS EC2 for computing, Azure Blob Storage for file storage, and GCP BigQuery for data analysis. This way, if one cloud has a problem, your services can still run on another. However, switching between these cloud providers, like moving virtual machines or databases from AWS to Azure, can be difficult, especially if the infrastructure isn’t set up for any automatic failover. Without this setup, you'll need to handle things on your own, like transferring data or reconfiguring services, which can simply slow down the recovery process and also increase the downtime.

Why Multi Cloud Disaster Recovery is Important

When you use multiple cloud providers, it obviously makes your infrastructure more reliable, but it also adds complexity to the disaster recovery process. If one cloud provider experiences an issue, whether it’s an outage, a security breach, or a service disruption, you need a plan in place to recover and keep your cloud services running.

An automated multi cloud disaster recovery plan in a multi-cloud environment helps reduce downtime and also eliminates manual risks or errors.

What Should Be in an Automated Disaster Recovery Plan?

Till now, we’ve seen that managing multi cloud disaster recovery across different cloud providers can be a challenging process. You need a strong and automated disaster recovery strategy to ensure your services stay running and your important data remains safe. This automated multi-cloud DR plan will help you recover quickly from any issues, reduce downtime, and keep all your services, applications, and data running smoothly across all the cloud providers you are using.

Let’s break down the key elements that should be part of an automated disaster recovery plan:

Continuous Monitoring and Health Checks

By monitoring your infrastructure in real time, you can spot problems early and fix them before they affect your running services on a large scale. For example, you can use Amazon CloudWatch to monitor EC2 instances and check their CPU usage, memory, and disk space. You can use Azure Monitor to keep track of virtual machines, storage, and other resources. You should also monitor databases, such as Amazon RDS or Azure SQL Database, to ensure they have active connections and storage space. If something goes wrong, these tools can send alerts as well so that you can fix the problem before it causes any major downtime and quickly recover.

Automated Backup Policy Management

Next, you need to make sure that backup policies are set up and followed automatically across all the cloud platforms and improve your multi-cloud DR plan. For example, in AWS, you can use AWS Backup to schedule regular backups for services, such as Amazon RDS, EC2 instances, and S3 buckets. You can also set retention policies to specify how long the backups should be kept before being deleted. In Azure, you can use Azure Backup to automate backups for services like Azure VMs and SQL databases. By setting up these backup tools to run automatically, you can make sure that your data is always backed up without any manual intervention and that the infrastructure is ready to be restored quickly.

Managing All Resources Through IaC

Managing your cloud resources with Infrastructure as Code is an important part of any disaster recovery plan. IaC allows you to define your infrastructure in the form of code, making sure that all of your environment is set up in a consistent, repeatable way. This makes it easier to recreate or restore resources after any disaster. For example, in AWS, you can use AWS CloudFormation to manage resources like EC2 instances, RDS databases, and S3 buckets. In Azure, you can use Azure Resource Manager (ARM) templates to manage VMs, storage accounts, and databases. Additionally, Terraform is a powerful IaC tool that works across AWS, Azure, and GCP, allowing you to manage all your resources in a unified way. By using Terraform, you can deploy, update, and scale resources automatically, making the disaster recovery services and process even faster and more reliable. IaC ensures that your resources are always correctly configured, which is important for a smooth and efficient recovery during a disaster.

Alerting and Automated Notifications

Lastly, setting up alerting and automated notifications is also important for any multi cloud disaster recovery plan. Whenever there’s a failed backup, a performance issue, or a service disruption, immediate notifications allow your team to take quick action on that issue. In AWS, you can use Amazon SNS (Simple Notification Service) to send alerts about system health, backups, or failed processes. In Azure, you can set up Azure Alerts to notify you of resource performance issues or backup failures. These tools can automatically send messages to your team via email, SMS, or other communication channels.

Now, as we've seen, managing multiple tools across different cloud platforms can be a complex and time-consuming task. Each cloud provider has its own set of tools, making it difficult to maintain a unified multi cloud disaster recovery plan. This can easily slow down recovery time and increase the risk of errors during any such disaster event.

This is where Firefly steps in. Instead of dealing with separate tools for each cloud provider, Firefly centralizes everything in one place. It simplifies monitoring, recovery point backup management, and resource handling across AWS, Azure, and GCP, all in one place. Let’s explore how Firefly’s features can help you make your disaster recovery plan.

Continuous monitoring with Firefly

In a multi-cloud environment, keeping track of all of your resources can be a challenge for DevOps engineers, especially when you need to make sure everything is ready for disaster recovery as well. Firefly simplifies multi cloud disaster recovery by providing a single, centralized dashboard that monitors across AWS, Azure, and GCP, making it easier to manage your entire cloud infrastructure from a single dashboard.

The Firefly inventory gives you a clear view of all your cloud resources. Whether it's monitoring EC2 instances, IAM roles, or Google Cloud Storage, Firefly keeps track of your resource health, performance, and availability.

Firefly also helps you identify and manage unmanaged resources not covered by Infrastructure as Code and ghost assets, which are resources that are no longer in use but still exist in your environment. By highlighting these, Firefly makes sure that no resources are missed during disaster recovery planning or execution.

Additionally, Firefly integrates with IaC tools like Terraform, CloudFormation, and Helm, providing you with a unified view of both your cloud infrastructure and IaC configurations. This ensures all resources are correctly configured and ready for a fast recovery. With Firefly, you gain proactive monitoring that helps detect issues early, reduce downtime, and make sure your infrastructure is always prepared to recover quickly when a disaster strikes.

By this, Firefly solves the problem of continuous monitoring and health checks by ensuring that all your other cloud computing resources are consistently tracked for performance, helping you spot and address issues before any major downtime or breaking changes.

Enforcing Backup Policies with Firefly

Now, we move to the second key aspect of an automated disaster recovery plan, which is automated backup policy management. Managing backup policies across multiple cloud providers can be difficult and time-consuming, but Firefly helps solve this by providing built-in governance features for backups.

For example, Firefly has predefined policies that automatically ensure certain backup rules are enforced across your cloud environment. One such policy is to make sure that every S3 bucket that is not versioning enabled is backed up. 

This is important for preventing data loss in case of any accidental deletions or changes. Firefly helps you track all the assets that fall under this policy, making sure no backup is missed, and all resources are protected.

Beyond the built-in policies, Firefly also allows you to create custom backup policies focused on your specific requirements. For example, you can define a custom policy for services like AWS Route Tables, AWS Internet Gateways, or AWS SQS Queues to ensure they are backed up regularly. This flexibility allows you to focus on specific assets that are important to your infrastructure, making sure that your backup process aligns with your operational needs as well.

This flexibility helps you manage backup processes efficiently across AWS, Azure, and GCP, ensuring that all your resources are always ready for recovery.

By automating these backup policies, Firefly removes the need to check each cloud platform, schedule backups, and verify whether they are completed. Without Firefly, you would have to manage backups separately for each cloud provider, track their status, and make sure everything is backed up properly. With Firefly, this process is automated, and your data is safely backed up and ready for recovery when needed.

Firefly’s Codification of Unmanaged Resources

Moving on to the third pointer from our disaster recovery plan, managing all resources through IaC. Without Firefly, tracking unmanaged resources in your multi-cloud environment can take much time. Typically, you would need to inspect each cloud provider's environment and identify resources that are not yet defined in Infrastructure as Code. This process involves checking for any resources, such as storage, databases, or virtual machines, that are not yet codified and tracking their backup status individually. You would also need to update these resources on your own when you add or modify your infrastructure, which can be prone to inconsistencies.

Firefly simplifies this by automatically identifying and listing all unmanaged resources in a single dashboard. It provides a clear view of all such resources across AWS, Azure, and GCP, so you no longer have to search through each cloud platform separately.

Once these unmanaged resources are identified, Firefly allows you to codify them immediately.

Simply click on "Codify," and you get the code needed to import these resources into your IaC. 

Firefly also provides you with the necessary terraform import command or the relevant code for your cloud platform, which you can then use to add these resources to your IaC configuration.

In addition, Firefly allows you to integrate these changes into your Github easily. You can create a pull request to merge the changes, making sure that your infrastructure remains consistent and versioned. This integration further simplifies the disaster recovery process by making sure all resources are properly codified, tracked, and ready to be restored when needed.

Setting Up Alerts with Firefly

Now, to the last point in our DR plan, we have Setting Up Alerts. This is also an important part of any disaster recovery plan, making sure that you’re notified whenever there are anomalies in your infrastructure.

With Firefly, setting up alerts is simple. To get started, go to the Notifications section in Firefly, then click on Add New. From there, you can choose the Event Type, such as a Policy Violation, and select the policy that has been violated (e.g., a backup policy). 

You can customize the alert by choosing how you’d like to receive it. Firefly allows you to send alerts via the Firefly Slack app or to an email address. This flexibility ensures that you’re always notified, regardless of where you are or what tool you’re using.

Once you’ve selected the policy, Firefly will automatically notify you whenever there’s a violation, like if a backup fails or a resource isn't configured according to your policy.

By setting up these alerts, you’ll be able to respond to any policy violations immediately, minimizing downtime and making sure that the recovery process can start without any delay. Firefly makes it easier to track your backup policies and stay ahead of potential issues.

So, now it's up to you: do you want to keep using different tools for each cloud provider or simplify things with Firefly? Firefly brings everything together for monitoring, backups, IaC, and alerts in one place. It saves you time, reduces errors or misconfigurations, and ensures your disaster recovery process is faster and more reliable. With Firefly, you can make your disaster recovery plan easier and make sure your infrastructure is always ready to recover. The choice is yours.

Now let’s go over some specific best practices. These will help you build a more reliable and faster recovery process across AWS, Azure, and GCP.

Best Practices for Multi Cloud Disaster Recovery Automation

To build a reliable and fast multi cloud disaster recovery plan, here are some specific practices that actually work in real-infrastructure environments. These practices align with what we've discussed so far: automating backups, using IaC, setting alerts, and syncing data across AWS, Azure, and GCP.

1. Use a Single IaC Framework for All Clouds

Managing different templates for each cloud (CloudFormation for AWS, ARM for Azure, Deployment Manager for GCP) slows you down. Use Terraform across all providers. This gives you one codebase to manage EC2, Azure VMs, Google Cloud Storage, and more, making your disaster recovery plan easier to maintain and test.

2. Automate Cross-Cloud Backup Policies

Don’t manually schedule backups in each cloud’s console. Instead, use policy-based automation. For example, set a policy to ensure all AWS S3 buckets with no versioning are flagged. Firefly helps enforce this automatically, so you’re not relying on human memory to catch backup gaps.

3. Codify Unmanaged Resources Right Away

Unmanaged resources are the biggest blind spots during a recovery. Use Firefly’s Codify feature to scan all clouds and identify anything not covered by your IaC. Whether it’s a rogue Azure SQL DB or a GCP instance created via the console, codify it and push the changes to your Git repo. This makes sure nothing critical is missed during a failover.

4. Set Alerts on Backup Violations and Orphaned Assets

A missed backup or a ghost resource during a disaster can break your recovery chain. Use Firefly’s policy alerting to notify you immediately when backup policies are violated or when resources are left unmanaged. Route alerts to Slack or email so your team can act fast, even before a failure hits.

5. Run DR Tests Using Real Configurations

Don’t rely on documentation alone. Use your actual Terraform modules or IaC definitions to run recovery drills. Create a temporary region or test project and simulate failover using your production IaC. This exposes gaps in codified resources and helps you fine-tune recovery steps.

6. Monitor All Cloud Resources from One View

Instead of jumping between AWS Console, Azure Portal, and GCP Dashboard, use a single monitoring pane like Firefly’s inventory. This way, you can track performance, backup status, and policy violations across all clouds without context-switching. It reduces errors and saves time during real incidents.

Conclusion

Handling disaster recovery across AWS, Azure, and GCP is not easy. Each platform has its own tools, backup systems, and failover methods. If your plan isn't well-structured, you might end up with missed backups, delayed recovery, or data inconsistencies across cloud providers.

That’s why a clear and automated multi cloud disaster recovery plan matters. When you automate health checks, backups, resource tracking, and alerts, you reduce the chances of human error and speed up your recovery time. Managing your resources with Infrastructure as Code makes it easier to rebuild everything exactly as it was, no matter which cloud provider goes down.

Outages can be unpredictable, but your recovery process shouldn’t be. A well-prepared and tested disaster recovery plan for cloud services makes all the difference when things go wrong.

Make sure your plan is ready before you need it.

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