- Viraj Talikotkar
Application development architecture is seeing a paradigm shift from monolithic systems to microservices. The new way is flexible, scalable, and a more potent methodology when compared to its predecessor and identifies as one of the best techniques in building and maintaining applications. However, as enterprise and web-based internet systems grow, microservices architecture might become unstable — microservices communicate via REST APIs that may not operate efficiently for large data structures due to overdependence or tight coupling.
Apache Kafka helps to evolve microservices by decoupling with asynchronous messages such as message-driven & an event-driven architecture. Kafka is the most popular platform for event-streaming, with thousands of organizations leveraging it, some of them being Netflix, Airbnb, and Pinterest. Kafka helps build powerful analytics engines, robust data pipelines, and data integration for business-critical applications. It solves multiple issues arising from microservices orchestration and helps businesses achieve flexibility, scalability, efficiency, and speed.
Here are six benefits of Apache Kafka that businesses can harness immediately.
Apache Kafka helps businesses send messages between processes, applications, and servers through a publish-subscribe messaging system. It does so by storing streams of records in real-time through a fault-tolerant durable way. Organizations can roll out large-scale messaging on their applications with Kafka for a seamless customer experience.
Activity tracking is a high-volume game with activity possible on every user page. Apache Kafka streamlines site activity tracking by collating pages, search views, or other actions from users and publishing it to a central topic in real-time. The platform also collects data from distributed applications for businesses to get a complete picture of user behavior.
Multiple organizations have started using Kafka as a replacement for log aggregation. Log aggregation is a process wherein servers collect physical log files and put them into a central place for processing. Kafka gives a cleaner representation of a log or event data as a stream of messages. This facilitates low latency processing and makes it easier to support myriad data sources and distributed data consumption.
Event stream processing is one of the most crucial benefits of the Kafka Platform. Many organizations leverage Kafka to process data in streaming data pipelines and streaming applications consisting of multiple stages. There is no lag between events, the insights from these events, and the actions taken on these insights. The framework maintains its own data and state, fitting naturally into the microservices architecture.
Without Kafka, data ingested from external sources was transformed by batch-processing, often off-hours. Kafka solves this tedious and relatively slow process by making this data available in real-time. Additionally, Apache Kafka uses its servers known as Kafka clusters ensuring that business systems won’t crash. All the teams in an organization can access complete data, unlike before, wherein teams would have to communicate with other teams to obtain data.
Today’s organizations are looking toward the machine learning gold rush to augment their business offerings. Every business is looking to build great machine learning models to boost business. But, without data, machine learning algorithms are futile. Kafka makes it extremely easy to get data from source systems and move it reliably to fuel machine learning engines. This is not possible with existing solutions such as batch processing or enterprise messaging.
Apache Kafka is a ground-breaking, near-perfect platform should organizations choose it to handle vast amounts of event streaming data. The platform amplifies business offerings and adds on multiple benefits for organizations. However, setting up Kafka Clusters can be challenging for businesses that are only beginning to understand it. Establishing the platform in-house needs high-level expertise, cost overheads, and stakeholder distraction from the core part of the business. Partnering with a reliable, fully managed service providers such as Amazon MSK helps set up and leverage Kafka immediately.
A fully managed service provider establishes Apache Kafka without the need for organizations to oversee it. For businesses, this would mean savings in cost, time, and technical teams. Further, they can also help organizations learn and apply the best practices of Kafka and modernize their existing applications. As an AWS Advanced Consulting Partner, we are a go-to service provider for migrating your current Kafka workloads or establishing a new streaming platform with Kafka on Amazon MSK. Find out how we can help you set up Apache Kafka Clusters in no time to help you build world-class applications.
