MadeinWeb, as an AWS partner, assist JBS with cloud processing and resource optimization.
JBS is a Brazilian multinational recogniz as one of the global leaders in the food industry. Fac with high demand for products and the ne to control sales, stocks and maintain quality in the 15 countries where it operates, the multinational sought solutions to ensure that its more than 230,000 employees could work more assertively.
Thus, in January 2020, JBS propos a challenge to Made: to develop two internal web systems with the aim of having better control over sales, Sales
AI JBS, and the company’s cattle, Cattle AI JBS
The problem was that, before the project reach MadeinWeb, the multinational had already hir a company. This company was unable to meet the high demand that JBS ne, extending deadlines and presenting a series of structural flaws, which made the process difficult and did not allow its usability to be us to its fullest.
Among the main structural problems of the previous system, the programming code was the most worrying, since, due to deep flaws, the pages were taking more than 30 seconds to load, which made the system unusable.
To correct these problems, MadeinWeb divid the solution into two phases. The first aim to correct usability flaws, stabilizing the platform.
CodeBuild was us together with CodePipeline to automate build and deploy processes to avoid failures, aiming for operational excellence during deployments. In this way, CodeBuild was responsible for integrating the data in Amazon S3, so that all of it was properly stor and approv.
It is worth mentioning that, in addition to these functions, CodeBuild was also responsible for integrating SAM and CloudFormation in the deployment of the user authentication API.
SSL/TLS certificates were then creat and manag using AWS Certificate Manager, and all important crentials were securely secur using AWS Secrets Manager.
The second phase aim to ruce loading time to ensure even more high-performance systems for users.
The first thing the team identifi was that each Lambda had six to eight responsibilities within it. Which hinder the performance of the systems and, consequently, increas loading time.
Thus, MadeinWeb divid the structure into more than 30 different lambdas, each configur with a different size and, consequently, cost, according to its function, optimizing the organization of the code and facilitating its maintenance.
To do this, the user authentication taiwan phone number data process was optimiz using the resources. Provid by AWS Cognito. The website cache was also optimiz and stor through Cloudfront. While the Athe Lambdas, was stor in Elasticache.
All infrastructure and codes wer
efin with Cloudformation, aiming at the automation and organization of resources and expenses.
For data consultation, the company us 100% of the Athena service. But over time, this solution was no longer viable for the institution’s nes at the time. The cost-benefit for JBS was no longer effective, and a change was necessary.
In this case to optimize performance how to connect your domain and install and costs. Athena was no longer us for queries. Instead, all data was import into RDS (Relational Database Service), which is a high-performance relational database service!
To help optimize the system, we bw lists consume data produc through artificial intelligence and machine learning algorithms using DynamoDB.