StatusNeo

Behind the Scenes: How Instagram Reels Handles Massive Traffic and Real-Time View and Like Counts

Instagram Reels is a popular feature of the Instagram platform that allows users to create and share short-form video content. With its recent rise in popularity, Instagram Reels has become a critical aspect of the platform’s success. To support this growing demand, Instagram has implemented a number of technologies and techniques to handle massive traffic and real-time view and like counts. In this blog, we will take a closer look at how Instagram Reels handles massive traffic and real-time view and like counts.

Traffic Handling

To handle traffic, Instagram Reels uses a distributed network of servers and content delivery networks (CDNs). The platform is hosted on Facebook’s cloud infrastructure, which allows for scalable and reliable distribution of content across the globe. When a user requests a Reel, the request is directed to the nearest server or CDN, which delivers the content to the user’s device.

To ensure that the video is delivered smoothly, Instagram Reels uses adaptive bitrate streaming technology. This means that the video quality is adjusted based on the user’s internet connection and device capabilities. For example, if a user has a slow internet connection, the video quality will be lowered to prevent buffering.

Instagram Reels also has a system of load balancers that help to distribute traffic across the network of servers and CDNs. Load balancers are responsible for evenly distributing incoming requests to the various servers in the network. This helps to prevent any one server from becoming overwhelmed with requests.

To handle sudden spikes in traffic, Instagram Reels also has an autoscaling system in place. This system monitors the traffic load on the servers and automatically adds or removes servers as needed. This helps to ensure that the platform can handle sudden increases in traffic without any disruption in service.

Updating View and Like Counts

Updating view and like counts in real-time is a critical aspect of Instagram Reels’ user experience. When a user watches a Reel or likes it, the view and like counts need to be updated in real-time to reflect the user’s actions.

To achieve this, Instagram Reels uses a system of distributed databases and caching servers. When a user watches a Reel, the view count is updated on the local cache server, which is then propagated to the distributed databases. The distributed databases are responsible for storing and managing the view and like counts for each Reel.

Instagram Reels also uses a system of spam filters to prevent fake views and likes. The platform uses machine learning algorithms to identify and filter out fake views and likes, which helps to ensure that the view and like counts are accurate and reflect genuine user engagement.

The spam filters work by analyzing various aspects of the views and likes. For example, the filters will look at the location of the views and likes, the duration of the views, and the engagement patterns of the users who generated the views and likes. By using machine learning algorithms, Instagram Reels can identify patterns that indicate fake views and likes and filter them out.

In addition to the distributed databases and spam filters, Instagram Reels also has a system of batch updates. Batch updates are used to update the view and like counts in bulk. For example, when a Reel is first uploaded, the view count may be updated in batches rather than in real-time. This helps to ensure that the distributed databases are not overwhelmed with too many updates at once.

Content Moderation

Instagram Reels also has a system of content moderation in place to ensure that the content on the platform is safe and appropriate. This system uses a combination of machine learning algorithms and human moderators to detect and remove content that violates Instagram’s community guidelines.

The machine learning algorithms work by analyzing the content of the Reels and detecting any potentially harmful or inappropriate material. This can include things like hate speech, nudity, and violence. Once detected, the content is flagged for review by human moderators.

Human moderators then review the flagged content and determine whether it violates Instagram’s community guidelines. If the content is found to be in violation, it is removed from the platform.

To further enhance content moderation, Instagram Reels has a reporting system that allows users to report content that they believe violates the community guidelines. When a user reports content, it is flagged for review by human moderators. This allows for a more comprehensive review of potentially harmful or inappropriate content.

Conclusion

Instagram Reels has become an essential feature of the Instagram platform, allowing users to create and share short-form video content. To support the growing demand for this feature, Instagram has implemented a number of technologies and techniques to handle massive traffic and real-time view and like counts. The platform uses a distributed network of servers and CDNs to handle traffic, adaptive bitrate streaming technology to deliver video content smoothly, and an autoscaling system to handle sudden spikes in traffic.

To update view and like counts in real-time, Instagram Reels uses a system of distributed databases, caching servers, and spam filters. The platform also has a system of content moderation in place to ensure that the content on the platform is safe and appropriate.

Overall, Instagram Reels is an excellent example of how technology can be used to deliver a high-quality user experience on a massive scale. By leveraging a combination of distributed networks, caching servers, and machine learning algorithms, Instagram has been able to deliver a seamless and engaging video experience to users all around the world.

Still Curious? Visit my website to know more!

Checkout my Interviews at “Professionals Unplugged”

For more interesting Blogs Visit- Utkarsh Shukla Author