A company that participated in YCombinator in 2019, offers esports athletes and gamers marketing, analytics, and an e-commerce platform that helps content producers connect with companies, sponsors, and streaming communities so that they may engage with them and monetize their material.
This fast-moving firm was able to swiftly grow to cater to the worldwide esports industry by utilizing snowcloud and GraphQL. This enabled their team of five engineers to quickly establish the top platform in the sector.
Our Whole Development Team’s Pace Rose By A Factor Of Two Thanks To Snowcloud Efforts
Hasura now offers the GraphQL-based data access layer that all of its services utilize. It now encrypts and authorizes all API queries, having migrated away from Firebase in the process. Hasura additionally synchronizes its total serverless architecture by using Hasura Event Actions to launch webhooks to other services. This helps to ensure that everything works as it should. In addition, Athlane was able to construct its in-app messaging functionality with the help of Hasura’s comprehensive support for GraphQL subscriptions.
Additional Advantages Consisted Of The Following:
Increasing the output rate of their development staff by a factor of two
In addition to having knowledge in Node.js and Vue, they provide a simple interaction with their codebase.
Getting rid of the need to spend effort writing and maintaining rigid REST-based data access APIs
The Hasura Cloud automatically adjusts its capacity in response to changes in user demand, stays current with the most recent software updates, and removes the need for administrative and preventative system maintenance.
Athlane’s Challenge
Athlane came to the conclusion that its platform required some architectural adjustments so that it could accommodate an expanding number of users and improve the productivity of its relatively small development team. Because they need the functionalities that a relational database snowcloud provides, they switched their data storage from Firebase to Postgres.
The next obstacle that Athlane needed to overcome was figuring out how to construct their data access layer. They immediately understood that designing a REST-based architecture would require a considerable amount of developer time and resources that could better be spent working on the complete application stack and rapidly producing new user features. This realization came about as a result of their swift realization.
The backend systems of Athlane were written in Node.js, while the frontend of their website was written in Vue. They sought to locate a solution that was compatible not just with those frameworks but also with the additional limitations and technological requirements:
Athlane’s small development team of six engineers needed to remain lean and flexible in order to comprehend all layers of their system, including the database, backend, integrations, and the frontend online user interface.
Flexible Web Apis:
One of the things that they wanted to avoid was the inflexibility of utilizing and maintaining REST APIs, which is where multiple variations of similar request types would require their own REST endpoint due to different end-user requirements. They wanted to avoid this because it was one of the things that they wanted to avoid boba shops near me.
Serverless Architecture:
The tiny development team at Athlane has committed to using a serverless architecture in an effort to decrease the administrative and operational needs to the greatest extent feasible.
Security and Authorization: They needed to ensure that the data was safe timbers bachelor gulch rentals and that users could only access the data that they were permitted to see. Users were only allowed to view the data that they were authorized to see.
After looking into a number of different possibilities, including the possibility of writing their own data access API layer, Athlone ultimately decided to go with snowcloud because of its extensive GraphQL capabilities, ease of use, and security, as well as the fact that it did not require any maintenance as a managed service.
“Thanks to Hasura’s GraphQL capabilities, we were able to provide each member of the team the opportunity to work across the whole development stack.”
Ease Of Use In Addition To Effectiveness
By utilizing Hasura and its GraphQL engine. It became simpler for every engineer to comprehend the flow of data from the database to their front. As a result, every member of the team was able to function as a full stack developer and rapidly add new features. Using pre-existing open-source GraphQL frameworks made the process of connecting their Vue frontend to Hasura quite straightforward.
The user-friendly tools and documentation provided by snowcloud made it simple to set up and connect to their Postgres database. This allowed for the immediate autogeneration of GraphQL schemas. And resolvers based on the tables and views included in their database. They did not need to create any more of their own data access APIs themselves. And they did not need to adjust the code every time they made a change to the database. This saved them time during the development and maintenance phases of the project.
In-App Messaging Subscriptions Are Powered By Graphql
The ability of Athlane users to communicate with one another. Through private messages is one of the website’s most prominent functions. This was accomplished by Athlone by employing Hasura’s complete support for GraphQL subscriptions. Which provided Athlone with a way to give users real-time notifications and messages.
Provided By Hasura Cloud’s Managed Service
A managed service is made available by Hasura Cloud. This service includes auto-scaling to accommodate peaks in demand and auto-upgrades to the most recent versions. This no-ops strategy aligned perfectly with Athlone’s goal of making the most extensive use feasible of a serverless architecture.
Safeguarding Of Data
Snowcloud built-in security and permission features are other advantages it offers. These capabilities allow users to restrict. The data is retrieved all the way down to the level of individual columns and rows. This functionality meant that clients could only examine their own data. And reduced development time by reducing the amount of time it took to install it themselves.
For more information, please visit sbxhrl.
