Migrate from Heroku to AWS: A Best Practices Guide

In an era dominated by cloud solutions, businesses often find themselves at a crossroads when choosing the right platform to host their applications. Heroku is a favored choice due to its simplicity and ease of use, making it an attractive option for small applications to deploy and manage their applications quickly. However, as organizations scale and demand more control over their infrastructures, migrating to a more robust, scalable, and cost-effective solution, such as Amazon Web Services (AWS), becomes increasingly irresistible.

Migrating from Heroku to AWS represents a strategic shift for businesses, promising enhanced scalability, customization, flexibility, and control over the infrastructure. This article delves into the key considerations, challenges, and best practices to follow during this migration. We will also assess the challenges in transferring your applications and services from Heroku to AWS before starting a migration initiative and examine how users can leverage the power of third-party tools to automate the migration process.

Important differences between Heroku and AWS

The table below provides a quick comparison of features between Heroku and AWS.

Summary of key best practices when migrating from Heroku to AWS

The following table lists the practices to consider following while migrating from Heroku to AWS.

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Best practices for migrating from Heroku to AWS

Understand UI differences

Transitioning from Heroku’s streamlined interface to the AWS management console can initially be challenging. Heroku offers a more straightforward navigation structure and deployment process, while AWS provides a more intricate console with extensive deployment, monitoring, and scaling options.

The screenshot below shows how streamlined the User Interface can be with “Create New App” in the center of the screen. The various features are consolidated into one user interface, wizard, or menu system.

When it comes to AWS, implementing proper access control and permissions management using AWS Organizations, IAM Identity Center, and IAM roles is essential to maintain security and governance within your AWS environment, but the configurations are more involved.

Familiarizing yourself with these differences and leveraging AWS documentation and training resources can help ease the transition and unlock the full potential of AWS services.

The following shows the difference in UI, where you can see the wide variety of services that AWS provides, with each service having its own UI with various options and features, in contrast to the more streamlined user experience in Heroku.

Migrate networks effectively

Replicating the network isolation on Heroku to your AWS VPC architecture is crucial for the security of your application.

Here are some best practices to be considered when setting up a VPC architecture in your AWS environment:

• Define subnets, route tables, and security groups that mirror or strengthen the isolation offered by Heroku.
• Segregate resources, such as databases, ECS instances, and ElastiCache Redis instances, into private subnets to prevent direct external access. Allocate public subnets for resources requiring external connectivity.
• Leverage the redundancy of multiple availability zones for fault tolerance.
• Regulate inbound and outbound traffic flow within the VPC using network access control lists (NACLs) and security groups.
• Utilize VPC Flow Logs and AWS Network Firewall to monitor and safeguard network traffic, further increasing your infrastructure’s security.

Read more about the AWS VPC best practices here.

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Migrate the database

Once your VPC is set up, you can plan for database migration. To migrate from the Heroku Database to Amazon RDS, follow these steps:

• Verify version compatibility with your existing engine.
• Evaluate your database requirements and choose the appropriate RDS instance type.
• Follow the AWS tutorial to create a database instance.
• Once the database is set up, leverage the AWS Database Migration System (DMS) to minimize downtime during data migration. Remember, though, that thoroughly testing and optimizing your RDS instances’ sizes and configurations is essential to match your workload demands.
• Finally, automated backup and database snapshots for disaster recovery should be implemented.

Choose a cache migration method and migrate the cache

Once your database migration is complete, it’s time to plan for cache migration. Migrating the Redis cache from Heroku to Amazon ElastiCache for Redis can involve data loss and downtime, but you can minimize data loss and downtime by executing the following strategy:

• Backup data: Perform a backup of your Heroku Redis data before initiating the migration process.
• Determine data volume: Evaluating the size of your Redis dataset can help you choose the most suitable migration method and estimate the time for migration.
• Choose a migration method:some text
  • Migration using an EC2 instance: This method involves setting up an EC2 instance as an intermediary between the Heroku Redis instance and the Amazon ElastiCache Redis cluster. Data is streamed from Heroku to the EC2 instance and then to ElastiCache. This method minimizes downtime as data is migrated in real-time. Follow the steps here to perform an online migration using this method.
  • Seed data into ElastiCache Redis: This approach can export backed-up data from Heroku Redis into ElastiCache Redis. Unlike the previous method, this is not a real-time migration and only migrates your existing data. Follow the tutorial here to perform Redis migration using the seeding process.

Automate deployments

Streamlining your application deployment process is essential when migrating your workload from Heroku to AWS. For automated deployments, capitalize on CI/CD pipelines by setting up AWS CodePipeline and AWS CodeBuilds.

In fact, integrating CI/CD pipelines is crucial when moving to AWS. Consider leveraging AWS CodePipeline as your orchestrator. It allows you to visualize and manage the entire deployment workflow, from commits to production.

With AWS CodeBuild, you can automate the compilation, testing, and packaging of your code, ensuring a consistent build process.

In addition, with a tool like AWS CodeDeploy, you can automate the deployment itself and make updates to your application across your AWS infrastructure with minimum downtime.

By embracing deployment automation, you’ll gain the ability to rapidly iterate, catch errors early, and deliver a more stable and reliable user experience.

Conduct DNS migration

Transferring your DNS records from Heroku to AWS is the next critical step in the migration process. Follow these steps:

• Retrieve and export your DNS records from Heroku’s settings.
• Create a new hosted zone in AWS Route 53 and add the exported DNS records.
• Update the name servers at your domain registrar to point to Route 53.
• Wait for DNS propagation to complete.
• Test the DNS resolution and monitor for any issues.

Be sure to clean up Heroku’s DNS settings after the DNS migration is successful.

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Implement monitoring and logging

Once your network, infrastructure, databases, and pipelines are ready, configure monitoring, logging, and auditing for your AWS environment by utilizing AWS CloudWatch and AWS CloudTrail. Here are some specific recommended practices:

• Set up CloudWatch alarms to monitor resource utilization metrics such as CPU usage, memory utilization, storage space, and network traffic. Users can define thresholds for these metrics to trigger alarm actions, such as SNS or Lambda, when they exceed predefined limits, indicating potential performance bottlenecks or resource constraints.
• Define custom metrics in CloudWatch and configure your application to push application-specific performance data that’s critical for your business using AWS SDKs or CloudWatch APIs.
• Utilize CloudWatch logs and log insights to track application logs and identify any issues that may arise within the application.
• Set up CloudWatch Synthetics to continuously monitor your application endpoints at specific intervals and alert you about failures.
• Enable CloudTrail logging in all AWS regions and accounts to capture API calls, user activity, and configuration changes across your AWS environments.
• Configure CloudTrail to deliver log files to a centralized Amazon S3 bucket for easy access, retention, and archival.
• Enable server-side encryption (SSE) for CloudTrail log files stored in Amazon S3 to protect sensitive information from unauthorized access.
• Implement cross-account log aggregation to consolidate CloudTrail logs from multiple AWS accounts into a centralized location for simplified management and auditing.

By setting up proper monitoring, logging, and auditing, you can proactively identify and address any issues that may arise in your setup.

Challenges associated with manual migration

While the manual migration of infrastructure from Heroku to AWS can be useful in transferring your workloads, it has a number of challenges associated with it:

• Complexity and potential for errors: Manual migration often involves intricate steps, configurations, and interdependencies that can significantly increase the probability of errors.
• Time and resource consumption: Manual migrations require significant time and resources for planning, execution, and validation.
• Lack of visibility and control: Due to the manual nature of the migration process, visibility into the status, dependencies, and progress of the migration could be lacking.
• Risk of data loss and downtime: Manual migrations pose a risk of data loss or corruption and unexpected downtime during the migration process.
• Inefficient resource utilization: Users may create redundant resources with manual migration, leading to overprovisioning or underutilizing AWS resources.
• Lack of documentation and compliance: Manual migration processes often need proper documentation and adherence to compliance requirements, potentially resulting in regulatory issues.

Automating the migration using Coherence

With Coherence, users can develop automated environments and build pipelines to develop, test, and deploy applications in the cloud.

Coherence automation features

Coherence delivers the following advantages by automating the migration from Heroku to AWS:

• Predefined workflows: Coherence provides predefined migration workflows and automation tools, simplifying intricate migration tasks and ensuring consistency across migrations while mitigating the risk of errors.
• Automate repetitive tasks: Coherence automates repetitive tasks and streamlines migration workflows, reducing the time and effort required for migration. This accelerates the migration process, helping enable quicker, more efficient migrations.
• Enhanced monitoring capabilities: Coherence provides real-time insights, monitoring, and reporting capabilities that offer visibility into every migration stage. Users can effortlessly track the status of migration tasks, identify bottlenecks, and resolve issues proactively using Coherence’s centralized management interface.
• Seamless data migration: Coherence helps users perform reliable and seamless data migration with minimal downtime using the right strategies to ensure data consistency and mitigate the risk of data loss during migration.
• Optimized resource recommendations: Coherence analyzes workload patterns and resource utilization. This helps organizations tailor the AWS infrastructure to ensure optimal resource allocation and utilization, maximizing efficiency and cost-effectiveness.
• Preview environments: Coherence lets users spin up temporary staging environments for every branch of your application, enabling developers to preview and test each PR with production-grade full-stack environments.
• Comprehensive migration documentation: Coherence generates comprehensive migration documentation and audit trails, facilitating compliance with regulatory standards and ensuring transparency throughout the migration process.

Using Coherence to automate the migration from Heroku to AWS

The following is an overview of the steps for automating your application migration from Heroku to AWS using Coherence:

• Create a Coherence account an application by following the onboarding guide.
• Configure your Coherence application by setting the environment variables within the application. Note that variables like DATABASE_URL and REDIS_URL will be automatically injected by Coherence.
• Next, generate your coherence.yml file and customize it to meet the requirements of your application. This is the primary step of the migration process—you will define your application’s configuration here so that Coherence can provision the necessary resources for you.

A sample coherence.yml is given below:

allow_vpc_sharing: true


frontend:
  type: frontend
  assets_path: dist
  local_packages: ["node_modules"]
  build: ["npm", "build"]
  dev: ["npm", "dev"]


server:
  type: backend
  migration: [".", "/opt/venv/bin/activate", "&&", "python", "manage.py", "migrate"]
  dev: [".", "/opt/venv/bin/activate", "&&", "python", "manage.py", "runserver", "0.0.0.0:$PORT"]
  prod: [".", "/opt/venv/bin/activate", "&&", "python", "manage.py", "runserver", "0.0.0.0:$PORT"]


  resources:
  - name: db1
    engine: postgres
    version: 14
    type: database
    adapter: postgresql


preview_inactivity_timeout_hours: 72


vpc_sharing:
  app_name: my-first-app
  fallback_environment: main

You can also configure advanced settings in Coherence to perform database seeding and migrations, built-in tests and integration tests, and workspaces for your application.

• Once the steps above are done, wait for Coherence to provision the resources in your AWS environment and test your application from end to end by creating a preview environment.
• Finally, perform database and DNS migrations.

For a more thorough guide, please refer to the official documentation, and to the dedicated Migrate from Heroku section.

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Conclusion

Transitioning from Heroku to AWS signifies a strategic shift driven by the need for enhanced control, scalability, and cost-effectiveness in managing cloud infrastructure. While Heroku offers simplicity, AWS provides greater flexibility and scalability, making it a compelling choice for growing organizations.

With automation tools such as Coherence, businesses can streamline this migration process by leveraging predefined workflows, automated tasks, and enhanced monitoring capabilities, ensuring a smooth transition to AWS.