Approach-Disaster Recovery for Logstash

Hello Readers!!! Hope you are doing well. In this blog we’ll see Approach-Disaster Recovery for Logstash. Whenever your Logstash gets down and you want it to recover then you can go through the below approach.

Overview

This blog outlines the approach for implementing a disaster recovery strategy for Logstash, which is set up on an AWS EC2. The approach involves creating an Amazon Machine Image (AMI) of the existing Logstash EC2 instance and using it to launch a new EC2 instance whenever the primary Logstash instance is affected by a disruption.

Steps for DR for Logstash

1: Create an AMI Image of Logstash EC2 Instance

• Sign in to your AWS Management Console > Navigate to EC2 Dashboard.
• Select the Logstash EC2 instance > Actions > Image and templates > Create Image.

• Provide Image Details:

1. Image Name: Choose a descriptive name for the AMI.
2. Image Description: Optionally, provide a description.
3. No Reboot: You can select this option to prevent the instance from rebooting during the image creation process (if supported by Logstash’s configuration).
4. Create Image: Click on the “Create Image” button to start the image creation process. This process will involve creating a snapshot of the instance’s root volume.
5. Wait for Image Creation: Wait for the image creation process to complete. This might take some time, depending on the size of the instance’s root volume.

• Go to EC2 Dashboard > Images > AMI’s and your image will create with Image status is Active.

2: Launch EC2 Instance from the AMI Image

• Go toEC2 Dashboard >Images > AMIs.

• Click on your Created AMI Image and Click on Launch Instance from AMI.

• Select the appropriate instance type for the new EC2 instance. Ensure it aligns with the requirements of your Logstash workload.

• Configure instance details, such as the number of instances, network settings, and storage. Use the same settings as the original Logstash instance if applicable.

• Add Storage & Configure the security group settings to allow the necessary inbound and outbound traffic for Logstash.

• Review and Click Launch to start the new EC2 instance based on the AMI.

• Your Instance is launch with the same configuration you have for the main Instance.

3: Implement Disaster Recovery

In the event of a disaster or when the main Logstash EC2 instance becomes unusable, follow these steps to initiate the disaster recovery process:

• If the main Logstash EC2 instance is destroy or unable to function properly, you can terminate it or stop it based on the severity of the situation.
• Refer to Step 2 to launch a new EC2 instance from the AMI image you created. Ensure that the new instance follows the same configuration and settings as the original Logstash instance.
• If necessary, update any configuration files or settings to ensure that the new Logstash instance functions correctly within your environment.
• Start the Logstash service on the new instance to resume data processing and forwarding.

Automating the Approach Using Jenkins Pipeline

To automate the disaster recovery approach for Logstash using the previously outlined steps. The pipeline will automate the process of creating an AMI image from the existing Logstash EC2 instance, launching a new instance from the AMI in the event of a disaster, and ensuring the Logstash service is up and running.

We need several permission to automate this approach as:

AWS Permissions

• AWS IAM Role:
  • Create an AWS IAM role with the necessary permissions for EC2, EC2 AMI creation, and other required services.
  • Attach this IAM role to your Jenkins instance.
• Jenkins Credentials:
  • Add your AWS access key ID and secret access key as Jenkins credentials with the IDs aws-credentials.
• SSH Key Pair:
  • Ensure you have an SSH key pair that can be use to access the EC2 instances. You can add the private key as a Jenkins credential if needed.

Benefits of Automation:

• Consistency: Automation ensures that recovery steps are consistently execute, reducing the chance of errors.
• Efficiency: Automated pipelines accelerate the recovery process, minimising downtime and data loss.
• Reduced Manual Effort: Manual intervention is minimise, freeing up resources for other tasks.
• Scalability: The automated approach can be easily scale to handle multiple instances if needed.

Conclusion

The above approach for Amazon Machine Images (AMIs) enable quick and consistent recovery of a Logstash instance in case of a disaster. Establishing a disaster recovery strategy for Logstash in AWS is essential. The manual approach involves creating AMIs and launching instances from them, while the automated method, via a Jenkins Pipeline, streamlines the process for consistency and efficiency. Whether manual or automated, these approaches strengthen data integrity, minimise downtime, and ensure the availability of Logstash services during unforeseen events, contributing to a resilient data processing environment.

Keep Learning !!!

Thank You 🙂