Data loss such as losing customer information, transaction records, or configuration files due to a disaster like an earthquake, cyberattack, or server failure can have serious consequences for any business. For instance, imagine a SaaS company that experiences a server crash during a software update. If their product database, which stores customer data, user accounts, and billing information, is not backed up, they might face extended downtime of their services. This downtime can lead to lost revenue and increased operational costs. Beyond the financial impact, the company’s reputation may suffer, causing customers to lose trust and potentially switch to competitors, resulting in long-term damage to the business.

This is where Disaster Recovery or DR comes into play. DR helps businesses restore systems like servers and databases after events such as natural disasters, cyberattacks, or hardware failures. By regularly creating and storing backups, companies can continue key operations, like customer service or order processing, during disruptions. DR solutions minimize downtime, reduce financial losses, and protect a company’s reputation by quickly resuming services.

This blog covers how to implement a disaster recovery strategy using AWS EBS Snapshots with Terraform, including the impacts of data loss, snapshot management, and best practices like cross-region replication and compliance.

What is Disaster Recovery?

Disaster recovery starts with preparation, which means identifying potential risks like hardware failures, cyberattacks, or natural disasters and setting up strategies to handle them. This includes regularly backing up data to cloud storage or on-premises systems and ensuring the necessary infrastructure, such as backup servers, networking components, and recovery tools, are ready to restore operations quickly. The faster a business can recover, the less disruption it will face, minimizing downtime and reducing the overall impact of the disaster.

Once a disaster occurs, the recovery process kicks in. This includes restoring systems, recovering lost data, and ensuring that business operations can continue, often using backup solutions such as EBS snapshots. The goal during recovery is to minimize downtime and return to normal as quickly as possible.

After the recovery, post-recovery actions involve evaluating the effectiveness of the disaster recovery plan, learning from the incident, and making improvements. This phase ensures that any gaps in the recovery process are identified and fixed for future preparedness.

The disaster recovery process generally follows this timeline:

  1. Preparation: Identifying risks and setting up backup systems.
  2. Disaster Occurrence: The disaster strikes, causing system failure or data loss.
  3. Recovery: Restoration of data and systems to resume business operations.
  4. Post-Recovery: Reviewing and improving the disaster recovery plan based on lessons learned.

This timeline ensures that a company is not only prepared for disasters but also capable of recovering swiftly to continue its operations with minimal disruption.

To understand how disaster recovery works with AWS, it’s important to know how EBS Snapshots play a role. These snapshots act as backups of the data stored on Amazon Elastic Block Store (EBS) volumes, which are used by AWS EC2 instances.

What are EBS Snapshots?

EBS snapshots are essential for disaster preparation and recovery. They provide a reliable, cost-effective way to back up and recover data stored on EBS volumes. When a disaster happens, you can restore the data from these snapshots to bring your systems back online quickly.

During the preparation phase, businesses create snapshots on a regular basis to ensure they always have a current backup of critical data. These backups can be stored in Amazon S3 and even be replicated across regions for added protection. In case of failure, such as hardware malfunction or accidental data deletion, these snapshots serve as the recovery point, making it easier to restore your systems.

There are two types of EBS Snapshots: Standard and Archive. Below is a comparison of these two snapshot types to help you choose the best option for your disaster recovery needs:

Both snapshot types play a role in disaster recovery, but the choice depends on how often you need to access the backup data and how long you need to keep it. Standard snapshots are useful for frequent backups and quick recovery, while archive snapshots are more cost-effective for long-term data storage that doesn't require instant access.

When using Terraform to manage your infrastructure, it’s essential to automate and streamline the process of creating and managing AWS resources like EBS volumes and snapshots. 

Terraform Configuration for EBS Snapshots

Terraform allows you to define and deploy your cloud resources in a consistent, repeatable manner, making it an excellent choice for managing disaster recovery.

Setting up Terraform with AWS provider

Before you can start managing AWS resources, you first need to set up Terraform with the AWS provider. To do this, you’ll need to have the AWS CLI installed and configured with your credentials (access key and secret key). Then, you’ll configure the Terraform AWS provider in your .tf file.

provider "aws" { region = "us-east-1" }

Once the provider is set up, you can start defining your resources, including EBS volumes and snapshots.

Defining EBS volumes in Terraform

Next, you’ll need to define your EBS volumes in Terraform and attach it to an EC2 instance. The aws_ebs_volume resource allows you to create and manage EBS volumes. Here’s an example configuration:

resource "aws_instance" “firefly_instance" { ami = "ami-0866a3c8686eaeeba" instance_type = "t2.micro" } resource "aws_ebs_volume" "firefly_volume" { availability_zone = aws_instance.firefly_instance.availability_zone size = 10 } resource "aws_volume_attachment" "firefly_volume_attachment" { device_name = "/dev/sdh" instance_id = aws_instance.firefly_instance.id volume_id = aws_ebs_volume.firefly_volume.id }

This creates an EBS volume in the specified availability zone. You can modify the size, availability zone, and other parameters based on your needs.

Creating snapshots with Terraform

Once your EBS volume is created, you can create snapshots of the volume using the aws_ebs_snapshot resource. This will capture the current state of the EBS volume and allow you to restore it later.

resource "aws_ebs_snapshot" "firefly_snapshot" { volume_id = aws_ebs_volume.example.id tags = { Name = "firefly-snapshot" } }

This configuration creates a snapshot of the EBS volume you defined earlier. You can add more tags and modify other parameters as necessary.

Creating cross-region snapshots with Terraform

In the event of a regional disaster, you may want to replicate your EBS snapshots to another region for additional protection. Terraform makes it easy to create cross-region snapshots by specifying the target region in your configuration.

provider "aws" { region = "us-west-2" } resource "aws_ebs_snapshot_copy" "cross_region_snapshot" { source_snapshot_id = aws_ebs_snapshot.firefly_snapshot.id source_region = "us-east-1" tags = { Name = "cross-region-snapshot" } } resource "aws_ebs_volume" "restored_volume" { availability_zone = aws_instance.firefly_instance.availability_zone snapshot_id = aws_ebs_snapshot.firefly_snapshot.id } resource "aws_volume_attachment" "restored_attachment" { device_name = "/dev/sdi" instance_id = aws_instance.firefly_instance.id volume_id = aws_ebs_volume.restored_volume.id }

This example first creates a snapshot in the source region (e.g., us-east-1) and then copies it to a target region (e.g., us-west-2). This ensures that your data is protected even if a disaster occurs in your primary region.

By automating the process of creating EBS volumes, snapshots, and cross-region replication with Terraform, you can significantly improve your disaster recovery capabilities. These configurations ensure that you have reliable backups that can be quickly restored, reducing downtime and minimizing the impact of data loss.

When it comes to managing snapshots at scale, manually creating and managing them can become time-consuming and error-prone. AWS Data Lifecycle Manager (DLM) is a service that automates the creation, retention, and deletion of EBS snapshots, making it an essential tool for managing disaster recovery in AWS environments.

Using AWS DLM for Scheduling Snapshots

AWS DLM helps simplify the management of EBS snapshots by automating snapshot schedules based on your desired frequency and retention policy. This ensures that snapshots are taken regularly without manual intervention, reducing the risk of human error and ensuring you have up-to-date backups at all times.

DLM is commonly used for:

  • Defining snapshot schedules, ensuring backups are created consistently and according to the policy you set.
  • Configuring retention policies to automatically delete old snapshots after a certain period, helping you manage storage costs.
  • Automating snapshot management and retention as DLM helps optimize costs by ensuring you're only storing necessary snapshots.

For disaster recovery, DLM provides a reliable mechanism to ensure snapshots are taken regularly, reducing the risk of data loss.

Using AWS DLM for Scheduling Snapshots with Terraform

Terraform can be used to configure AWS DLM policies, allowing you to automate snapshot creation and management directly from your infrastructure-as-code configuration. Here's how you can set up a DLM policy with Terraform.

First, you’ll need to define a DLM policy using the aws_dlm_lifecycle_policy resource. Below is an example Terraform configuration for scheduling daily EBS snapshots with a 7-day retention period:

resource "aws_dlm_lifecycle_policy" "daily_snapshots" { description = "Daily snapshots for disaster recovery" state = "ENABLED" policy_details { resource_types = ["VOLUME"] schedule { name = "DailySnapshots" frequency = "DAILY" start_time = "00:00" retention { count = 7 } } } target_tags = { "Name" = "MyEBSVolume" } }

Main Components of the DLM Configuration:

  • Frequency: In this example, snapshots are taken daily. You can also choose weekly or monthly snapshots depending on your needs.
  • Start Time: The start_time specifies when the snapshot should be taken each day. You can adjust this based on your environment's needs.
  • Retention: The retention policy automatically deletes snapshots older than 7 days. This ensures you don’t accumulate unnecessary snapshots and incur extra costs.
  • Target Tags: DLM policies apply to EBS volumes with specific tags. This allows you to control which volumes are included in the snapshot schedule.

With this Terraform configuration, AWS DLM will automatically create daily snapshots of your EBS volumes and delete snapshots older than 7 days, ensuring that your disaster recovery backups are always up to date without the need for manual intervention.

By leveraging AWS DLM with Terraform, you can automate and scale your disaster recovery strategy, ensuring your snapshots are created and retained according to your organization’s policies. This helps improve operational efficiency and reduces the risks of data loss.

Restoring from EBS Snapshots

Restoring data from EBS snapshots is a critical part of any disaster recovery plan. In the event of data loss or system failure, you can use snapshots to restore your EBS volumes to their previous state. However, there are some differences in how you restore from Standard and Archive snapshots, so it's important to understand the process for both.

Steps for Restoring EBS Volumes from Snapshots

The process for restoring an EBS volume from a snapshot involves the following steps:

1. Identify the Snapshot: First, you need to find the snapshot you want to restore from. This could be a standard or archive snapshot, depending on your backup strategy.

2. Create a New EBS Volume from Snapshot: Use the snapshot to create a new EBS volume. This volume can be attached to an EC2 instance for further use. In AWS, you can do this via the AWS Management Console, CLI, or Terraform. Here’s an example of how to do this in Terraform:

resource "aws_ebs_volume" "restored_volume" { snapshot_id = "snap-xxxxxxxx" availability_zone = "us-east-1a" size = 10 }

3. Attach the New Volume to an EC2 Instance: After the volume is created, you need to attach it to an EC2 instance. This can be done manually in the console or through Terraform with the aws_volume_attachment resource.

resource "aws_volume_attachment" "volume_attachment" { device_name = "/dev/sdf" instance_id = "i-xxxxxxxx" volume_id = aws_ebs_volume.restored_volume.id }

4. Once the volume is attached to your EC2 instance, you can mount it and begin using the data as needed.

Standard vs. Archive Snapshot Restoration

While the basic restoration process remains the same for both Standard and Archive snapshots, there are a few differences:

  • Standard Snapshot Restoration: When you restore from a standard snapshot, the process is nearly instantaneous. The data is readily available because standard snapshots are stored in S3’s standard storage class, which allows for faster access and restoration.
  • Archive Snapshot Restoration: Restoring from an archive snapshot stored in S3 Glacier involves an additional step of retrieval. S3 Glacier is designed for long-term storage and is optimized for infrequent access. Because of this, restoring data from an archive snapshot can take several hours, depending on the retrieval tier chosen (e.g., expedited, standard, or bulk).

For example, if your disaster recovery plan relies on quick access to recent backups, you would typically use standard snapshots. Archive snapshots, on the other hand, are ideal for long-term retention of data that you don’t need immediate access to but want to keep for compliance or cost-saving reasons.

In conclusion, while both snapshot types can be used for disaster recovery, choosing the right type for your recovery needs is crucial. Standard snapshots provide fast, reliable restoration, whereas archive snapshots offer a more cost-effective option for long-term storage with the tradeoff of slower restoration times.

Firefly’s cloud management platform offers a comprehensive set of tools designed to simplify and automate various aspects of cloud infrastructure management. One of its key areas of focus is Disaster Recovery, where it ensures that businesses can quickly recover from unexpected events and continue operations with minimal disruption.

Firefly and Disaster Recovery

Firefly is a cloud management platform that provides unified solutions for managing and orchestrating workloads across multiple cloud environments. It is designed to help businesses manage their cloud infrastructure efficiently, ensuring smooth operations and enhanced security. By leveraging automation and intelligent tools, Firefly optimizes cloud environments while ensuring that disaster recovery plans are streamlined and cost-effective.

When it comes to disaster recovery, Firefly helps organizations maintain business continuity by providing reliable, automated backup and recovery strategies. Firefly’s platform integrates with AWS, GCP, and other cloud providers, enabling organizations to safeguard their data across diverse environments.

Custom Backup Policy

Firefly simplifies policy creation by automatically generating Infrastructure as Code (IaC) policies in Rego, the policy language for Open Policy Agent (OPA). This ensures automated, scalable, and compliant backups, helping you maintain data integrity and availability across cloud environments.

To create a custom backup policy, go to the governance tab and click on “Custom Policy”

Input Name, Category, Severity, Data Source, Asset Type, and Policy Description which is used by Tinkerbell AI, an open-source infrastructure provisioning engine to create Policy-as-Code in Rego.

We can also create a notification after the policy to notify us by Email or Slack on Firefly if there’s any resource that is not policy-compliant.

Multi-Cloud Support

One of the features of Firefly’s platform is its multi-cloud support. It allows businesses to manage and protect their workloads across multiple cloud providers such as AWS, Google Cloud, and Microsoft Azure. Multi-cloud environments are becoming more common as organizations look to avoid vendor lock-in and enhance redundancy. With Firefly’s multi-cloud capabilities, you can distribute workloads across different cloud providers, ensuring that your disaster recovery plan is resilient to failures within a single cloud environment. You can also replicate backups across multiple clouds, giving you additional security and flexibility in case one cloud provider faces an outage.

Compliance Automation

For organizations that must comply with industry regulations like SOC 2, HIPAA, or GDPR, Firefly offers compliance automation tools that ensure your disaster recovery processes meet necessary standards.

Firefly’s cloud management platform provides quite a lot of features to enhance disaster recovery across multi-cloud environments. With automated backups, versioning, cross-cloud replication, and compliance automation, Firefly helps businesses safeguard their data and ensures they can recover quickly in the event of a disaster.