Monday, 16 September 2024

5 Essential Techniques for Turbocharging API Performance

 5 Essential Techniques for Turbocharging API Performance


A high-performing API is crucial for a great user experience and efficient application operation.

1. Caching
Store frequently accessed data in a cache (like Redis or Memcached) for rapid retrieval, bypassing the database for repeated requests.

Benefits
- Drastically reduces database load.
- Significantly improves response times.

Challenges
- Deciding on the right caching strategy (time-based, event-based, etc.)
- Managing cache invalidation to ensure data consistency.

2. Scale-out with Load Balancing
Distribute incoming requests across multiple server instances using a load balancer (like Nginx or HAProxy).

Benefits
- Handles increased traffic and prevents a single server from becoming a bottleneck.
- Improves reliability as requests can be routed to healthy instances if one fails.

Considerations
- Stateless applications are easier to scale horizontally.
- Requires infrastructure to manage load balancers.

3. Asynchronous Processing
Acknowledge client requests immediately and process them in the background, sending results later.

Benefits
- Unblocks the client and improves perceived responsiveness.
- Allows the API server to handle long-running tasks without delaying other requests.

Considerations
- Requires careful design to manage background tasks and notifications.
- Not suitable for all API operations (e.g., real-time data updates).

4. Pagination
Limit the number of records returned per request and provide a way to retrieve subsequent pages.

Benefits
- Reduces response sizes, especially for large datasets.
- Prevents excessive memory consumption on both client and server.

Implementation
- Use query parameters for page number and size.
- Include metadata in the response (e.g., total records, next/previous page links).

5. Connection Pooling
Maintain a pool of reusable database connections instead of creating a new one for each request.

Benefits
- Minimizes the overhead of establishing new connections.
- Significantly improves performance under high concurrency.

Implementation
- Most database libraries/frameworks offer built-in connection pooling mechanisms.

**Additional Tips**

- Optimize Database Queries
- Gzip Compression - Reduce response sizes.
- Content Delivery Network (CDN) - Cache static assets globally for faster delivery.
- Monitor and Profile - Use tools like New Relic or Datadog to identify bottlenecks.

Monday, 9 September 2024

TS Economy

 https://mcqanswers.com/subject-based-mcqs/details.php?topic=92

https://education.sakshi.com/groups/practice-test/ts-economy/telangana-economy-important-bits-telugu-group-exams-111445

Sunday, 8 September 2024

Azure learn

 https://learn.microsoft.com/en-us/training/paths/az-104-administrator-prerequisites/

https://learn.microsoft.com/en-us/training/browse/?roles=administrator&products=azure&source=learn

Wednesday, 4 September 2024

good page design page

 https://bookscape.com/product-details/the-power-of-your-subconscious-mind-9789353338459

Google Maps integration for bike book in flutter flow

 https://blog.flutterflow.io/live-tracking-google-maps-rider/


Economy Link

 https://www.drishtiias.com/summary-of-important-reports/the-indian-economy-a-review-part-i



Tuesday, 3 September 2024

get users list by workflowid

 WITH GroupedResults AS (

    SELECT w.*, 

           ROW_NUMBER() OVER (PARTITION BY WorkFlow_ID ORDER BY Approver_Sequence DESC) AS rn

    FROM tbl_WorkFlowMembers w

    WHERE Division_ID = 'MSV' AND Country_Code = 'MX'

)

ADE JOB

  Data Engineer (Night Shift - Remote) Job ID: 378310   Remote   India   2 - 5 years Remote Job Link See all jobs Positions: Data Engineer I...