Senior Software Engineer at a recreational facilities/services company with 1,001-5,000 employees
Real User
Top 20
2024-06-12T19:48:00Z
Jun 12, 2024
We use Amazon MSK for communication and notification purposes, such as notifying users about new game releases and managing customer support interactions, thus handling large data volumes.
Integration Solution Architect at a consultancy with 11-50 employees
Real User
Top 5
2024-05-24T18:34:00Z
May 24, 2024
I have used Confluent Cloud and Amazon MSK in my company. We are not using it for analytics and it is more for CDC processes, so we change the capture processes. It is used to extract data from a database and make it available in other parts of our systems or produce events that inform us of data updates.
My use cases were primarily in the banking domain, where we tracked real-time transactions. Apart from real-time transactions, we also had another project in the retail domain. Our client's name was McDonolad, and their focus was on package delivery. By "package," I mean the customized burgers created at their restaurant that needed to be delivered to various restaurant locations. When customers visit their restaurant, they would order their personalized burgers. Sometimes, customers would request specific ingredients that were not available in the pre-made burgers displayed at the counter. The restaurant faced the challenge of understanding why customers were not opting for ready-made burgers or patties. To address this issue, they aimed to enhance their product by offering customized burgers. These customized burgers had to be prepared according to the customer's specific preferences. To achieve this, they started taking orders from customers. However, it was difficult to determine the exact taste or requirements the customers were looking for. To overcome this, they decided to transfer all the customer's order data to the Kafka server for streaming. This allowed the restaurant's backend system to analyze the data and understand the customer's new tastes and requirements. By collecting this data, they were able to enhance their product and make necessary changes to improve customer satisfaction.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.
I use the solution in my company for our CDC pipelines to asynchronously collect data from databases and systems.
We use Amazon MSK for communication and notification purposes, such as notifying users about new game releases and managing customer support interactions, thus handling large data volumes.
I have used Confluent Cloud and Amazon MSK in my company. We are not using it for analytics and it is more for CDC processes, so we change the capture processes. It is used to extract data from a database and make it available in other parts of our systems or produce events that inform us of data updates.
We use the software to facilitate building integrations between systems.
We are currently running tests and experimenting with other solutions.
My use cases were primarily in the banking domain, where we tracked real-time transactions. Apart from real-time transactions, we also had another project in the retail domain. Our client's name was McDonolad, and their focus was on package delivery. By "package," I mean the customized burgers created at their restaurant that needed to be delivered to various restaurant locations. When customers visit their restaurant, they would order their personalized burgers. Sometimes, customers would request specific ingredients that were not available in the pre-made burgers displayed at the counter. The restaurant faced the challenge of understanding why customers were not opting for ready-made burgers or patties. To address this issue, they aimed to enhance their product by offering customized burgers. These customized burgers had to be prepared according to the customer's specific preferences. To achieve this, they started taking orders from customers. However, it was difficult to determine the exact taste or requirements the customers were looking for. To overcome this, they decided to transfer all the customer's order data to the Kafka server for streaming. This allowed the restaurant's backend system to analyze the data and understand the customer's new tastes and requirements. By collecting this data, they were able to enhance their product and make necessary changes to improve customer satisfaction.
We are only using Amazon MSK for basic use cases.
Behind the scenes, we use Kafka. We tried using MSK to collect old data surrounding inventory from e-commerce websites, for example.