Therefore, using the example of one of our. Projects, we will show our approach to the development. About the Project In April 2021 the ad network system .
Every day the ad network
Registers events: bids that users place, ad impressions, ad clicks. In order for analysts to work with data, it nes. I therefore to be brought into a readable format — process and load into a program with a clear interface. System load. 2,4 billion impressions 408 million clicks 1240 conversions Analysis.
Businesses can use Telegram database telegram database users list user lists as an effective tool for focused marketing and communication. Businesses can improve engagement, target audiences, and maximize marketing efficacy by utilizing these lists. Businesses can cultivate leads, foster brand loyalty, and spur growth through direct, tailored. I therefore interactions on Telegram with features like group messaging and channels.
To design the system, we look at the type and amount of data, the prictable load increase, the results to be obtain, and budget and resource limitation. After that, the development began. Algorithm of data collection and analysis in the ad network Clicks, bids, impressions File creation and compression Statistics calculation Recording of the results Data is transferr to MySQL System operation scheme: The advertising platform registers events with Apache Kafka.
Collector Service monitors the
Queue of events in Apache Kafka, adds more data to event information, and saves event information to .csv files. After completing this process, Collector Service compresses it and loads this file into HDFS, in a special directory for input data. Every 5 minutes Stats Service checks for new raw files in the HDSF input directory. Apache Hadoop calculates statistics bas on input data and writes the results to files in a special directory on HDFS.
Stats Server picks up the results of calculating statistics from HDFS and exports the data to MySQL. Stats Server moves the process input files to an archive locat also on HDFS. Files are group by day — this is necessary so that statistics can be recalculat for a certain period if there were any errors in the scripts. Such a system can be us both in hardware and in the cloud. Results.
All components of the architecture are horizontally scalable and provide fault tolerance. Component What it provides Apache Kafka Distribut Message Broker. Processes up to several hundr thousand events per second.
Messages get through even if one
Of the servers goes down Adapts to the people analytics can be invaluable in your talent search campaigns growth of the load: it’s easy to add new servers Collector Service daemon in Go Processes tens of thousands of messages per second Adapts to the growth of the load: it can run several copies of the service in parallel and distribute work between them Hadoop Distribut File System Stores data securely Gives the data that was ask for Records what was sent to the system.
Replicat blocks across data nodes will not lose data Stats Server daemon in Java Fast computation spe with Map Ruce computation model: the data array is divid into parts; each part is process simultaneously and gather in to one Experts will answer your questions OrbitSoft experts answer questions from developers, business owners and managers.
Ask about everything, even if you are seo ebl just wondering. If you want us to analyze your situation or share our experience, write to anna.mandrikina. How can we help? Artificial intelligence technology. This technology helps customize ad impressions for your audience, analyzes large amounts of data fast and error-free, and much more.
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Ready-made or custom business solutions. Ad buying solutions: DSP, SSP, and Ad Exchange. Development of various products. For example, an application, an online store, a payment system, or a video platform. There are over 100 digital specialists on our team: developers, testers, designers, and project managers.
We have the resources to work with systems of any complexity. Share on Articles Портрет автора Record by Eugenia Osipova Previous article Tasks we solve with Angular Next article IT audit: tasks it solves and how to know if you ne it OrbitSoft 2001 — 2024 WHO WE ARE Services Projects Technology Reviews Advertising Solutions Application Development Articles and cases OrbitSoft WHO WE ARE Services Projects Technology .
Articles and cases Reviews
Whatsapp Facebook Development of a payment acceptance system: Development of a payment acceptance system: we creat a product for app monetization from scratch June 29 2021 553 Development of a payment acceptance system: In brief, regarding the project: 01 Client Mobile app monetization service 02 Business tasks To launch software which allows apps to work with major mobile operators Find additional way to monetize client’s products 03 Solution.
Develop payment acceptance
System for mobile operators’ apps 04 Results We reach an agreement on the documentation and operation algorithm with the operator’s technical specialists We integrat the customer’s system with the operators’ billing system We launch payment acceptance system on time All complet in one year of development 500+ mobile apps in the ecosystem AppClick is a mobile apps monetization ecosystem from Russia.
It earns commissions from in-app sales, for example, paying for subscriptions, disabling ads, or buying currency for games. More than 30 developers and more than 500 applications are register in the ecosystem.
Issue the client has an idea for
A new product, but no development resources. I therefore AppClick came up with an idea for a new product — a payment acceptance system built into the application in which you can use the user’s balance with a mobile operator to pay. According to an assessment of the service, such a system would be in demand among mobile operators as an additional source of income, and among users as a convenient way to make payments.
And most importantly, AppClick itself would be able to earn commissions on transfers. Monetization scheme Developers and app owners Integrate AppClick SDK in their app Publish their products on AppClick portal Users Install app on their phones Pay for a service or a feature AppClick and Mobile operator Identify users Accept their payments.
System Enters information regarding the payment Mobile operator and AppClick Receive a commission for payment processing. Thus, the remaining portion is given to me, the developer. Therefore, I paid the user. Although they liked the concept of the system, potential partners did not immediately agree to work together.
