Migrating from Atlas Data API and Custom HTTPS Endpoints (Previously Realm)

1. Introduction: The Deprecation of Atlas Data API and Custom HTTPS Endpoints

MongoDB has recently announced the deprecation of its Atlas Data API and Custom HTTPS Endpoints (previously known as Realm), which were widely used for building and managing data-driven applications. This change has come as a surprise to many developers who have relied on these services for their flexibility and ease of use. The deprecation announcement has raised important questions regarding the future of applications built on these platforms and the best alternatives to adopt.

As a result, developers are now faced with the challenge of migrating their applications from these deprecated services to more modern, scalable, and secure alternatives. This blog explores the deprecation of Atlas Data API and Custom HTTPS Endpoints, the impact on applications, and the migration options available to ensure a smooth transition, while highlighting how MongoDB development services can assist in this migration journey.

2. What is Atlas Data API and Custom HTTPS Endpoints?

Before diving into the migration process, it is important to understand what Atlas Data API and Custom HTTPS Endpoints are, and how they function within MongoDB’s ecosystem.

Atlas Data API:

The Atlas Data API was a cloud-based service provided by MongoDB to facilitate easy, HTTP-based access to MongoDB Atlas clusters. It allowed developers to interact with MongoDB databases over the internet by making simple HTTP requests. The API abstracted away the complexities of managing database connections and drivers, allowing developers to focus on building applications instead of dealing with the underlying infrastructure.

The Atlas Data API was especially useful for applications that required lightweight and stateless interactions with MongoDB, making it ideal for serverless applications, microservices, and other cloud-based architectures.

Custom HTTPS Endpoints (Formerly Realm):

Custom HTTPS Endpoints were part of MongoDB Realm (now part of MongoDB Atlas App Services). These endpoints allowed developers to write custom server-side logic and expose it via HTTP interfaces. Users could create functions and expose them as RESTful APIs, making it easier to integrate MongoDB with other services.

In the past, Custom HTTPS Endpoints provided a flexible way to add business logic to MongoDB-powered applications, enabling seamless integration with the frontend and other external systems.

3. Why is MongoDB Deprecating These Services?

MongoDB’s decision to deprecate the Atlas Data API and Custom HTTPS Endpoints stems from several factors that reflect the evolution of cloud-native technologies and the need for more secure, scalable, and flexible solutions.

Evolving Ecosystem:

As cloud-native development continues to evolve, MongoDB is shifting its focus to more modern solutions that integrate better with the ever-changing cloud ecosystem. Services like Atlas Functions and MongoDB Atlas App Services provide enhanced capabilities compared to the Data API and Custom HTTPS Endpoints, allowing developers to implement more complex logic and data operations directly within MongoDB Atlas.

Security Concerns:

The security challenges of maintaining HTTP-based APIs are significant, especially in cloud environments. Custom HTTPS Endpoints required developers to manage security at the API level, which could be error-prone and complex. By deprecating these services, MongoDB can push for more secure alternatives that provide better authentication, authorization, and data protection mechanisms.

Performance Limitations:

The performance of HTTP-based APIs may not always scale well for certain high-demand applications. MongoDB aims to offer solutions that are more optimized for modern workloads, offering better performance, scalability, and ease of use.

For more information on the deprecation and its reasoning, you can refer to MongoDB’s official documentation on Data API Deprecation.

4. Impact of the Deprecation on Your Applications

The deprecation of Atlas Data API and Custom HTTPS Endpoints will have several impacts on applications that rely on these services:

Disrupted Data Access:

Applications relying on Atlas Data API for database access will need to find alternative ways to interact with MongoDB. Given that many applications use the Data API for serverless architectures, this change will necessitate refactoring how data is accessed and manipulated.

Broken Integrations:

If your application uses Custom HTTPS Endpoints to expose business logic or create custom APIs, these integrations will likely break. External systems that depend on these endpoints may need to be reconfigured to work with new services or APIs.

Migration Overhead:

Migrating from deprecated services often requires significant development effort. Your team will need to invest time in re-architecting parts of the application, testing new services, and ensuring everything works smoothly after the migration.

The deprecation timeline provided by MongoDB gives developers time to plan and execute the migration, but it is essential to start the process early to avoid disruptions.

5. Available Migration Options

Now that we understand the impact of the deprecation, let’s explore the available migration options. There are several viable alternatives to the Atlas Data API and Custom HTTPS Endpoints, each with its own set of advantages.

5.1 MongoDB Atlas Functions

MongoDB Atlas Functions provide a serverless solution within MongoDB Atlas for executing custom logic. These functions are tightly integrated with MongoDB’s cloud platform, allowing you to run server-side code triggered by events or HTTP requests.

Instead of using Custom HTTPS Endpoints, you can write functions in JavaScript and deploy them in MongoDB Atlas, where they can be triggered via HTTP requests or other events. These functions can also interact directly with your MongoDB database, providing a seamless experience for developers.

Advantages:

Direct integration with MongoDB Atlas.
Secure and scalable execution of server-side logic.
Supports HTTP-based triggers, making it easy to expose APIs.

5.2 FaunaDB as an Alternative

FaunaDB is a serverless, distributed database that offers built-in GraphQL and FQL (Fauna Query Language) support. If you are looking for an alternative to MongoDB’s Data API, FaunaDB provides a flexible option for building APIs and managing data without the need for server infrastructure.

FaunaDB provides strong consistency, real-time capabilities, and built-in authentication, which can be crucial for handling complex data-driven applications. It also offers a more modern and scalable approach to managing data compared to MongoDB’s deprecated services.

Advantages:

Serverless architecture with automatic scaling.
Native support for GraphQL APIs.
Real-time data capabilities and strong consistency model.

For more on migrating from MongoDB’s Data API to FaunaDB, check out this Fauna blog post.

5.3 AWS Lambda and API Gateway

Another popular option for replacing deprecated services is AWS Lambda and API Gateway. Lambda allows you to run serverless functions in response to HTTP requests, while API Gateway can expose these functions as RESTful APIs.

With AWS Lambda, you can write functions in languages such as Node.js, Python, and Go, and integrate them with other AWS services like DynamoDB, S3, and more. AWS Lambda’s pay-as-you-go pricing model ensures cost-effectiveness, as you only pay for the compute time your functions consume.

Advantages:

Fully serverless and scalable.
Tight integration with AWS services.
Flexible pricing and cost-efficient infrastructure.

5.4 Using GraphQL and REST APIs

Another option for migrating from Atlas Data API and Custom HTTPS Endpoints is to adopt GraphQL or REST APIs for data access and application logic. MongoDB Atlas supports both GraphQL and REST APIs, allowing you to expose data and business logic via flexible API endpoints.

GraphQL is particularly useful for modern web and mobile applications, as it allows clients to request exactly the data they need, reducing over-fetching or under-fetching of data. REST APIs, on the other hand, are well-suited for traditional architectures.

Advantages:

GraphQL provides a flexible query language with fine-grained data retrieval.
REST APIs are widely used and well-understood.
MongoDB Atlas has native support for both options.

5.5 Third-party Integration Services

Many third-party platforms offer serverless API solutions that integrate well with MongoDB, helping you avoid the complexity of managing backend services. Platforms like Hasura, Firebase, and Apollo GraphQL allow you to quickly build and deploy APIs without worrying about server infrastructure.

These third-party services are ideal for applications that need to quickly scale and need minimal backend management.

Advantages:

Fast setup and deployment.
Built-in authentication and real-time capabilities.
Integration with multiple databases, including MongoDB.

6. Steps to Migrate from Atlas Data API and Custom HTTPS Endpoints

Migrating from Atlas Data API and Custom HTTPS Endpoints requires a structured approach to minimize downtime and ensure that your applications continue to function smoothly. Let’s break down the migration process into manageable steps:

6.1 Understanding the Migration Process

The first step in the migration process is to assess which parts of your application rely on the deprecated services. Create a comprehensive inventory of dependencies, including API endpoints, business logic, and data access patterns.

Once you have a clear understanding of your current setup, you can evaluate the best migration options for each dependency. Some parts of your application may be better suited for MongoDB Atlas Functions, while others may benefit from using a serverless architecture like AWS Lambda.

6.2 Handling Authentication and Security

As part of the migration, you’ll need to ensure that authentication and security are handled appropriately. MongoDB’s deprecated services provided built-in authentication mechanisms, which will need to be replaced with secure alternatives. Many of the alternatives discussed earlier, such as AWS Lambda, FaunaDB, and GraphQL APIs, offer robust authentication options like OAuth, JWT, or API keys.

6.3 Data Migration Considerations

If you are migrating from MongoDB to a different database platform, you will need to plan your data migration carefully. Tools like

the MongoDB Atlas Data Migration tool can help you move data from your Atlas cluster to another platform with minimal disruption. You can also automate the migration process using scripts, ensuring that data is consistently transferred without requiring manual intervention.

6.4 Testing and Validation

Once the migration plan is in place and the new services are integrated, it’s crucial to perform thorough testing. This includes validating the functionality of APIs, ensuring data integrity, and checking for performance issues. Testing should be conducted in a staging or sandbox environment to prevent disruptions in the production environment.

During testing, ensure that:

Data Access: The new API solutions can fetch, update, and delete data as required.
Business Logic: Custom functions or server-side logic operate as expected.
Security: Authentication and authorization mechanisms work seamlessly with the new services.
Performance: The new services meet your application’s performance and scalability requirements.

6.5 Transitioning to Production

After thorough testing, you can begin transitioning to production. This involves deploying the new services, migrating users to the new API endpoints, and monitoring the system for any potential issues. It’s recommended to roll out the changes gradually, starting with a small set of users or functionality, and expanding as confidence in the new system grows.

7. Best Practices for Migrating to New Solutions

Migrating to new services after the deprecation of Atlas Data API and Custom HTTPS Endpoints requires careful planning and execution. Here are some best practices that will help you manage this transition smoothly:

Plan Ahead

Don’t wait until the last minute to start planning your migration. The sooner you begin, the better prepared you will be to handle unexpected challenges. Review your current architecture, understand the dependencies between services, and start testing migration options well before the deprecation deadline.

Start with a Proof of Concept

Before fully committing to a new solution, create a proof of concept (PoC). The PoC will help you evaluate the performance, scalability, and usability of the alternative solutions. You can test different migration options, such as MongoDB Atlas Functions, FaunaDB, AWS Lambda, or GraphQL APIs, to determine which one best suits your requirements.

Automate the Migration Process

Where possible, automate the migration of data, configurations, and environment setups. Using automation tools helps reduce human error and ensures that the migration is carried out consistently. Automation can also help you scale the migration process, especially if you have a large number of API endpoints or services to migrate.

Monitor During and After Migration

Once you transition to the new services, continuous monitoring is essential. Use monitoring tools to track the performance, availability, and security of your application. Set up alerts for any critical issues, such as downtime or slow response times, and address them promptly.

8. Challenges and Solutions During the Migration Process

Like any migration project, moving from Atlas Data API and Custom HTTPS Endpoints can present challenges. Understanding these challenges and preparing for them can help ensure a successful migration.

Compatibility Issues

One of the main challenges is ensuring that the new solutions are fully compatible with your existing architecture. For example, if your application relies heavily on MongoDB’s query language and structure, you might find it difficult to migrate to a solution like FaunaDB, which uses a different query language.

Solution: Plan the migration carefully by evaluating the differences in query languages, data models, and SDKs. If necessary, refactor your application to accommodate these changes.

Data Migration Risks

Transferring data between platforms can lead to data loss, corruption, or inconsistency if not handled properly. This is especially true when switching from MongoDB to another database system.

Solution: Use reliable migration tools, and ensure data integrity by running validation checks before and after the migration. Back up data before starting the migration process to prevent any potential data loss.

Managing Authentication and Security

Migrating authentication mechanisms can be tricky, especially if you were using MongoDB’s built-in authentication features. When transitioning to new platforms like AWS Lambda or FaunaDB, you’ll need to integrate new authentication methods, such as OAuth or API keys.

Solution: Plan the authentication migration carefully and test all access control mechanisms thoroughly. Use secure methods like JWT (JSON Web Tokens) for stateless authentication, and ensure that all endpoints are secured using HTTPS.

Downtime During Migration

During the migration process, there may be periods of downtime as services are transitioned to the new platform. This can affect the availability of your application and frustrate users.

Solution: Minimize downtime by using techniques like blue/green deployments, rolling updates, or canary releases. Test the new solution in stages and gradually migrate users to the new system.

9. Conclusion: Preparing for the Future of Data APIs

The deprecation of Atlas Data API and Custom HTTPS Endpoints marks a significant shift in how developers interact with MongoDB. While this change may seem daunting initially, there are numerous alternatives that provide powerful, secure, and scalable solutions for data access and business logic implementation.

By understanding your migration options, carefully planning the transition, and adopting best practices, you can ensure a smooth migration experience. Whether you choose MongoDB Atlas Functions, FaunaDB, AWS Lambda, or other third-party services, it’s important to evaluate your application’s needs and select the solution that aligns best with your goals.

Additionally, as cloud-native technologies continue to evolve, staying up-to-date with the latest developments in data access and API management will help ensure that your applications remain secure, performant, and scalable.

For additional resources, be sure to check out MongoDB’s Data API Deprecation Announcement and explore FaunaDB’s approach for transitioning from MongoDB’s deprecated services.

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