On August 28th, 2022, when India was playing against Pakistan at Asia Cup T20 Championship in Dubai, further than1.3 crore or 13 million people were coincidently watching the match on the Disney Hotstar OTT app, on a global basis.
10 million concurrent observers, on a single mobile app, with a global followership is in fact, not a record. It’s25.3 million concurrent observers on Disney Hotstar App, which happened in 2019 during India vs New Zealand World CupSemi-Final match.
A world record, because active observers on a single mobile app, at this scale and magnitude have infrequently happened.
How did Disney Hotstar manage this feat?
In this blog, we will discuss how Disney Hotstar ensures this inconceivable scalability of the app by understanding and decrypting its system armature, concurrency, scalability models and further.
But first, a brief preface to the world’s second- biggest, and India’s# 1 OTT platform Disney Hotstar.
Disney Hotstar An preface
The trip started with the launch of the Hotstar app, in 2015, which was developed by Star India. The 2015 Cricket World Cup was about to start, along with the 2015 IPL event, and Star network wanted to completely subsidise the insane viewership.
While Hotstar generated a massive 345 million views for the World Cup, 200 million views were generated for the IPL Tournament.
This was before the Jio launch, which happened in 2016. And watching television series and matches on the mobile was still at an incipient stage. The foundation was set.
The preface of Reliance Jio’s telecom network changed Internet operation in India, and this changed everything for Hotstar.
By 2017, Hotstar had 300 million downloads, making them the world’s alternate- biggest OTT app, only below Netflix.
In 2019, Hotstar was acquired by Disney, as part of their 21st Century Fox accession, and the app was rebranded to Disney Hotstar.
As of now, Disney Hotstar has 400 million downloads, with a whooping stoner base of 300 million active yearly druggies, and 100 million diurnal active druggies. nearly 1 billion twinkles of videos are watched on the app daily.
The 2019 IPL event was watched by 267 million Disney Hotstar druggies, and in 2020, a record 400 billion twinkles of content was viewed during the IPL matches.
In India, Disney Hotstar has a veritably violent focus on indigenous content, as further than 60% of the content is viewed in original languages. This is the reason they support 8 Indian languages, with plans to expand this number. The same strategy is visible in other countries as well, with deep focus on indigenous content, along with regular English content.
They’ve,000 hours of content for observers, and India accounts for roughly 40% of their overall stoner base.
As of now, Disney Hotstar is available in India, US, UK, Indonesia, Malaysia, and Thailand and by 2023, they will launch in Vietnam.
Backend of Disney Hotstar
The platoon behind Disney Hotstar has assured an important backend by choosing Amazon Web Services or AWS for their hosting, while their CDN mate is Akamai.
nearly 100% of their business is supported by EC2 cases & S3 Object store is stationed for the data store.
At the same time, they use an admixture of on- demand & spot cases to ensure that the costs are controlled. For spot cases, they use machine literacy & data analytics algorithms which drastically reduces their overall charges of managing the backend.
AWS EMR Clusters is the service they use to reuse terabytes of data( in double- number) on a diurnal base. Note then, that AWS EMR is a managed Hadoop frame for recycling massive data across all EC2 cases.
In some cases, they also use Apache Spark, Presto, HBase fabrics in- sync with AWS EMR.
The core of scalability structure setup
Then are some intriguing details about their structure setup for cargo testing, just before an important event similar to IPL matches.
The entire setup of the Disney Hotstar structure has 16 TBs of RAM, 8000 CPU cores, with a peak speed of 32 Gbps for data transfer. This is the scale of their operations, which ensures that millions of druggies are suitable to coincidently pierce live streaming on their app.
Note then, that C4X cases are really high CPU- ferocious operations, icing a low price- per- cipher rate. With C4X cases, the app has high networking performance and optimal storehouse performance at no fresh cost.
Disney Hotstar uses these Android factors for having a important structure( and to keep the design approximately coupled for further inflexibility)
ViewModel For communicating with the network subcaste and filling the final result in
- LiveData.
- Room
- LifeCycleObserver
- RxJava 2
- Dagger 2 and Dagger Android
- AutoValue
- Glide 4
- Gson
- Chuck Interceptor For icing nippy and easy debugging of all network requests, when the biases aren’t connected with the network.
How does Disney Hotstar ensure flawless scalability?
There live principally two models to insure flawless scalability Business grounded and Graduation grounded.
In business- grounded scaling, the tech platoon simply adds new waiters and structure to the pool, as the number of requests being reused by the system keeps on adding.
Graduation- grounded scaling is decided in those cases, wherein the details and the nature of the new processes aren’t clear. In similar cases, the tech platoon of Disney Hotstar haspre-defined graduations per million concurrent druggies.
As further requests are reused by the system, new structure in terms of graduations is added.
As of now, the Disney Hotstar app has a concurrency buffer of 2 million concurrent druggies, which are, as we know, optimally employed during the peak events similar as World Cup matches or IPL events.
In case the number of druggies goes beyond this concurrency position, also it takes 90 seconds to add new structure to the pool, and the vessel and the operation take 74 seconds to start.
In order to handle this time pause, the platoon has apre-provisioned buffer, which is the contrary of bus- scaling and has proven to be a better option.
The platoon also has an in- erected dashboard called Infra Dashboard, which helps the platoon to make smart opinions, grounded on the concurrency situations, and vaticination models of new druggies, during an important event.
By using fractions, the platoon behind Disney Hotstar has assured modularity to the coming position.
Then are some of the features that a typical runner holds
- Player
- Vertically and horizontally scrolling lists, which display other contents. Now, the type of data being displayed and the UI of these lists varies grounded on what type of content it is.
- Watch and Play, Emojis.
- Heatmap and crucial Moments.
- Different type player Regulators. — Live, Advertisements, VoD( occurrences, pictures etc.)
- Different type of announcement formats
- Nudge to ask the stoner to login.
- Nudge to ask stoner to pay for All Live Sports
- Chromecast
- Content Description
- Error View and further
Planting intelligent customer for flawless performance
On occasions when quiescence in response is increased for the operation customer and the backend is overwhelmed with new requests, also there are established protocols, which absorb this unforeseen swell.
For example, in similar cases, the intelligent customer designedly increases the time interval between posterior requests, and the backend is suitable to get some respite.
For the end- druggies, there exists hiding & intelligent protocols, which ensures that they aren’t suitable to separate this purposeful time- pause, and the stoner experience isn’t hampered.
Besides, the Infradashboard continuously observes and reports every single severe error and fatal exception passing on millions of bias, and either they’re remedied in real- time, or emplace a retry medium for icing flawless performance.
This was just the tip of the icicle!
still, its system armature, database armature, If you wish to know further about how Disney Hotstar operates.
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