How to improve performances of multiple microservice calls betweenn

RajeshKumar1

To address the performance issues arising from multiple microservice calls between the Doctor and Hospital pages, here are some actions you can take to optimize and improve the speed:

1. Cache Results

Cache the API Responses: Cache the responses from both the doctors and hospitals endpoints. Use Laravel's caching mechanisms (e.g., Cache::remember()) to store the results for a specified period.

Example:

    $doctors = Cache::remember('doctors_list', 60, function () {
        return Doctor::all();
    });

This avoids repeated calls to the microservices, reducing load time.

Use HTTP Cache Headers: Implement caching at the HTTP level using ETags or Cache-Control headers for static data.

2. Asynchronous Requests

Use Asynchronous Calls: Make the microservice calls asynchronously to avoid blocking the main request. You can use Laravel’s queue system to queue the requests and send the results once they are completed.
- Laravel provides integration with queues and workers which will allow you to offload API calls.

JavaScript Fetch: You can make the calls asynchronously from the frontend using AJAX (JavaScript) and render the results dynamically without blocking the page load.

Example using Fetch API:

    fetch('/api/get-doctors')
        .then(response => response.json())
        .then(data => {
            // Render doctor list
        });

3. Batch API Calls

Instead of making multiple calls (one for each page), batch the calls together into a single request. You can create a dedicated API endpoint that returns both the list of doctors and hospitals in one response, reducing the need for multiple round trips.

For example, create an API like /api/overview that returns both doctors and hospitals at once.

Example:

    Route::get('/overview', function () {
        $doctors = Doctor::all();
        $hospitals = Hospital::all();
        return response()->json(compact('doctors', 'hospitals'));
    });

4. Database Optimization

Optimize Queries: Ensure that your queries are optimized. Use Eloquent's with() method to eager load relationships and avoid the N+1 problem.

Example:

    $doctors = Hospital::with('doctors')->find($hospitalId);

Indexes: Make sure the relevant columns in your database (such as hospital_id or doctor_id) are indexed to speed up queries.
Use Pagination: Rather than fetching all doctors and hospitals at once, consider using pagination to limit the number of records retrieved at once, reducing data transfer size and load time.

5. Reduce Microservice Dependencies

Minimize Service Calls: If possible, reduce the number of interdependent microservices. For example, if the doctor data is needed on the hospital page, consider embedding doctor information within the hospital service rather than having a separate call.
Use a GraphQL Layer: Instead of multiple RESTful calls, consider using GraphQL, which can return only the required data in a single request, potentially reducing the number of API calls.

6. Optimize Network Latency

Service Location: Ensure that your microservices are hosted in the same data center or cloud region to reduce network latency.
Use Load Balancers: Implement load balancing to distribute traffic efficiently across multiple service instances, improving response time.

7. Use Content Delivery Network (CDN)

If your microservices involve serving static content (such as images or CSS), use a CDN to cache and serve static assets closer to the user, improving loading time.

8. Optimize Frontend Rendering

Lazy Load: Implement lazy loading for both the list of doctors and hospitals. Load only the critical data on the initial page load, and load the rest once the user scrolls or interacts with the page.
Skeleton Screens: Use skeleton screens (loading placeholders) to improve perceived performance while waiting for API calls to return.

9. Monitor and Profile Performance

Monitor API Performance: Use tools like Laravel Telescope or New Relic to monitor API call performance and database query performance.
Profile the Application: Use profiling tools to analyze bottlenecks in your application, such as long-running queries or slow API responses.

By combining these strategies, you can significantly improve the performance of your microservices-based Laravel application and reduce the slow page loads caused by multiple interdependent API calls.

RajeshKumar1

It seems like you're facing performance issues with your Laravel microservices due to multiple calls between services (List of Doctors on the Hospital page and List of Hospitals on the Doctors page). This kind of problem can lead to slow page loading times, as each microservice is making separate requests to retrieve the data, which increases latency.

Here are a few solutions you can implement to optimize the performance:

1. Caching Data

Use Caching for Common Data: If the list of doctors or hospitals doesn’t change frequently, you can cache the data from the microservices to reduce the number of API calls.
- Redis: You can use Redis to cache API responses for a short period of time (e.g., 5 minutes) to minimize redundant calls.
- Laravel Cache: Use Laravel's built-in cache functionality to store the API responses and retrieve them without making repeated calls.

Cache::remember('doctors_list', 300, function () {
    return Http::get('http://doctor-service/api/doctors');
});

Database Query Cache: If the data is fetched from a database, make sure to use Laravel’s query cache to avoid hitting the database multiple times for the same data.

2. Asynchronous Requests

Use Asynchronous Requests: If you're making multiple HTTP requests (for example, to fetch the list of doctors and hospitals), make those requests asynchronously. This will allow the server to send the requests in parallel and process them simultaneously, rather than waiting for each call to finish one after another.
- Laravel provides an easy way to make asynchronous HTTP requests using Guzzle or Laravel HTTP Client with promises.

$response1 = Http::async()->get('http://doctor-service/api/doctors');
$response2 = Http::async()->get('http://hospital-service/api/hospitals');

$results = $response1->wait() + $response2->wait();

3. Pagination and Lazy Loading

Implement Pagination: Instead of loading all the data at once, you can implement pagination in your APIs so that you only load a subset of records at a time. This will reduce the data load on each API call.
Lazy Load Data: For larger datasets, consider lazy loading techniques where data is loaded only when the user needs it (for example, using infinite scrolling).

4. API Gateway

API Gateway: If you are dealing with multiple microservices, consider setting up an API Gateway. The gateway can aggregate calls to multiple microservices into a single call and handle the response more efficiently. This can also help in reducing the number of redundant calls from the frontend.
GraphQL: You can also explore GraphQL for optimized API calls. With GraphQL, you can fetch exactly the data you need in a single query, reducing the need for multiple requests.

5. Optimize Database Queries

Database Indexing: Ensure that your database queries are optimized with proper indexing, especially for commonly queried columns like doctor_id, hospital_id, etc.
Use Selective Fields: Avoid fetching unnecessary fields from the database. Always use select to query only the fields you need.

6. Load Balancing and Scaling

Horizontal Scaling: If the performance issues are due to high traffic or resource limitations, consider scaling your microservices horizontally by adding more instances. You can do this using a load balancer to distribute traffic evenly across instances.

7. Optimizing Frontend

Lazy Load Frontend Data: Use frontend techniques like lazy loading or code splitting to improve perceived performance by reducing the initial load time.

By implementing some or all of these strategies, you can significantly improve the performance of your website and reduce latency caused by multiple calls between microservices.