high_tech

high_tech

@high_tech02

Datascience, Bigdata, AI, Cybersecurite , web3, 5G, Devops , Quantumcomputer

high_tech — автор у TikTok: 15.6K підписників, 121.8K вподобань. У середньому відео набирає 27.6K переглядів, залученість — 0.6%. Найчастіші хештеги: #airoadmap, #humpday і #artificialintelligence.

https://github.com/hightech02/high_tech02
15.6K
Підписники
10K
Підписки
121.8K
Вподобання
27.6K
Сер. перегляди
Залученість: 0.6% 🗣️ англійська
15.6K
Підписники
121.8K
Усього вподобань
27.6K
Сер. перегляди
1.3K
Відео
10K
Підписки
0
В обраному
0.6%
Залученість

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Останні відео

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.    video credit - Saurabh Dashora 👏 #API #Performance #Optimization #Backend #WebDevelopment
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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. video credit - Saurabh Dashora 👏 #API #Performance #Optimization #Backend #WebDevelopment

There are hundreds of commands available in CMD, but here are some of the most common ones categorized for your reference: Basic File and Directory Commands: cd: Change directory dir: List directory contents copy: Copy files move: Move or rename files del / erase: Delete files mkdir / md: Create a new directory rmdir / rd: Remove an empty directory ren: Rename a file Network and Connectivity: ipconfig: Display network configuration details ping: Test network connectivity to a host tracert: Trace the route to a host netstat: View network connections and statistics System Management: systeminfo: Display system information tasklist: List running processes taskkill: Terminate a running process shutdown: Shut down or restart the computer chkdsk: Check disk for errors driverquery: List installed device drivers Command Prompt Management: cls: Clear the screen help: Get help on a specific command exit: Exit the Command Prompt These are just a few examples, and there are many more commands available. For a more comprehensive list, you can refer to online resources like: Microsoft documentation on Windows CMD commands: https://learn.microsoft.com/en-us/windows-server/administration/windows-commands/windows-commands SS64.com's Index of Windows CMD Commands: https://ss64.com/
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There are hundreds of commands available in CMD, but here are some of the most common ones categorized for your reference: Basic File and Directory Commands: cd: Change directory dir: List directory contents copy: Copy files move: Move or rename files del / erase: Delete files mkdir / md: Create a new directory rmdir / rd: Remove an empty directory ren: Rename a file Network and Connectivity: ipconfig: Display network configuration details ping: Test network connectivity to a host tracert: Trace the route to a host netstat: View network connections and statistics System Management: systeminfo: Display system information tasklist: List running processes taskkill: Terminate a running process shutdown: Shut down or restart the computer chkdsk: Check disk for errors driverquery: List installed device drivers Command Prompt Management: cls: Clear the screen help: Get help on a specific command exit: Exit the Command Prompt These are just a few examples, and there are many more commands available. For a more comprehensive list, you can refer to online resources like: Microsoft documentation on Windows CMD commands: https://learn.microsoft.com/en-us/windows-server/administration/windows-commands/windows-commands SS64.com's Index of Windows CMD Commands: https://ss64.com/

the diagram  illustrates the architecture of Netflix, which consists of various technologies working together to deliver content to users. Here’s a breakdown of the key components: Frontend: API (Application Programming Interface): This layer acts as the intermediary between the user interface and backend services. It receives user requests and delivers responses from backend systems. Mobile & Web: These represent the user interfaces users interact with on their devices, whether it’s a web browser or a mobile app. Netflix uses technologies like ReactJS to deliver a dynamic and responsive user experience. Backend: Services: This layer consists of microservices that handle specific functionalities like user authentication, content management, and streaming. Databases: Stores a variety of data required by Netflix, including user profiles, content metadata, and viewing history. The diagram shows various databases used by Netflix, including Cassandra, EVcache, and MySQL. Messaging/Streaming: Technologien like Apache Kafka and Flink facilitate communication between different services and enable real-time data processing. Streaming: Video Transcoder: Prepares video content for efficient delivery across various devices and internet connection speeds. Open Connect: Netflix’s content delivery network (CDN) that delivers content to users around the world. Big Data: Data Storage: Houses the vast amount of data Netflix collects, including user behavior and viewing habits. Data Processing: Employs tools like Apache Spark to analyze big data and extract valuable insights for tasks like recommendation generation. CI/CD (Continuous Integration and Continuous Delivery): Automates the process of building, testing, and deploying new features to production, ensuring a streamlined development workflow. Additional Technologies: Elastic Transcoder: Another video transcoding service potentially used by Netflix. Amazon: Likely refers to Amazon Web Services (AWS), the cloud platform that Netflix might leverage for various services. Atlassian: Suite of project management and collaboration tools potentially used by Netflix. PagerDuty: An alerting and incident management service. Overall, the diagram provides a high-level view of Netflix’s complex tech stack, showcasing the interplay between various technologies that enable them to deliver a seamless streaming experience to millions of users globally.
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the diagram illustrates the architecture of Netflix, which consists of various technologies working together to deliver content to users. Here’s a breakdown of the key components: Frontend: API (Application Programming Interface): This layer acts as the intermediary between the user interface and backend services. It receives user requests and delivers responses from backend systems. Mobile & Web: These represent the user interfaces users interact with on their devices, whether it’s a web browser or a mobile app. Netflix uses technologies like ReactJS to deliver a dynamic and responsive user experience. Backend: Services: This layer consists of microservices that handle specific functionalities like user authentication, content management, and streaming. Databases: Stores a variety of data required by Netflix, including user profiles, content metadata, and viewing history. The diagram shows various databases used by Netflix, including Cassandra, EVcache, and MySQL. Messaging/Streaming: Technologien like Apache Kafka and Flink facilitate communication between different services and enable real-time data processing. Streaming: Video Transcoder: Prepares video content for efficient delivery across various devices and internet connection speeds. Open Connect: Netflix’s content delivery network (CDN) that delivers content to users around the world. Big Data: Data Storage: Houses the vast amount of data Netflix collects, including user behavior and viewing habits. Data Processing: Employs tools like Apache Spark to analyze big data and extract valuable insights for tasks like recommendation generation. CI/CD (Continuous Integration and Continuous Delivery): Automates the process of building, testing, and deploying new features to production, ensuring a streamlined development workflow. Additional Technologies: Elastic Transcoder: Another video transcoding service potentially used by Netflix. Amazon: Likely refers to Amazon Web Services (AWS), the cloud platform that Netflix might leverage for various services. Atlassian: Suite of project management and collaboration tools potentially used by Netflix. PagerDuty: An alerting and incident management service. Overall, the diagram provides a high-level view of Netflix’s complex tech stack, showcasing the interplay between various technologies that enable them to deliver a seamless streaming experience to millions of users globally.

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Станом на 2026-10-09 у high_tech (@high_tech02) 15.6K підписників у TikTok.