Red Hat introduced the fully managed Apache Kafka service this year for processing addition, exploration, and linking demands for real-time data streams with easy-to-operate methods.
At the Red Hat Summit held at the end of April this year, Red Hat announced three hosting services. We have previously introduced OpenShift Data Science, which is a solution for the development of machine learning models. Next, OpenShift Streams for Apache Kafka also integrates Red Hat’s OpenShift Dedicated hosting service for enterprises to reduce operation complexity while using modern IT environments and acquiring universal function portfolios across open hybrid clouds and multiclouds.
It is worth noting that Red Hat has simplified the deployment, setup, and management of such applications as Kafka on OpenShift platforms before introducing OpenShift Streams for Apache Kafka. In fact, Red Hat also introduced a dedicated solution called Red Hat AMQ Streams at the end of October 2018, which achieves these demands through the combination of multiple operators. With total hosting services, Red Hat can help enterprises reduce the workloads derived from the support, integration, and maintenance for Kafka.
As the name suggests, OpenShift Streams for Apache Kafka is a solution that uses the open-source event stream/streaming event processing software Apache Kafka. Construction, execution, and operation of Kafka is simplified through cloud services. Apache Kafka is an open-source distributed publish–subscribe messaging system for fault-tolerant real-time data feeds.
With such a hosting service, enterprises can activate and run Kafka instances within a few minutes and start configuration in the OpenShift Dedicated environment. This way, corporate software development teams can combine continuous streams in the application system more easily. In addition, it supports high-volume data transmission across distributed microservices and various host operations to deliver consistent processing.
According to Red Hat, each Kafka instance includes one Kafka cluster for executing various brokers, while each broker contains various topics for receiving and storing data. A topic can be separated into various partitions that are published and reproduced to different brokers to provide fault tolerance and enhance the data access volume.
In addition, OpenShift Streams for Apache Kafka provides 24/7 coverage, a 99.95% uptime SLA for measurement and monitoring.
According the RedHat, OpenShift Streams for Apache Kafka aims to meet the demand for processing real-time data streams by providing easy addition, probing, and connection regardless of one’s whereabouts. Currently, this hosting service is available for trial in the developer preview version and will go live later this year.
What are the future features of OpenShift Streams for Apache Kafka? Red Hat intends to bind this hosting service into the schema registry for various working teams to easily probe and connect to the streaming topics of other teams and publish their own schema registries for use by other developers within the organization.
By choosing OpenShift Streams for Apache Kafka, enterprise IT teams can significantly reduce the working time in the related environments.
For example, Kafka service management, such as event log consolidation, system upgrade, and maintaining longer sessions, will be implemented by Red Hat’s site reliability engineers (SRE). In other words, Red Hat’s SREs will take over these routine operations, including infrastructure handling, while the system administrators of enterprise users can focus on other tasks.
The software developers of enterprise users can also focus on provisioning applications, increasing added value, and expanding the scale of application implementation. In addition, they can also create multiple Kafka resource pools to develop independent operation capacity and efficiency without worrying about the data collection and processing demands at the bottom layer.
In fact, Red Hat also prioritizes developer experience in solution design and construction for developers to make real-time provisioning and deployment of applications and expanding the scale of operations smoother.
Hence, enterprises will not need to build an OpenShift environment before using OpenShift Streams for Apache Kafka. This is a common advantage of ordinary hosting services. In this case, developers can easily connect the workloads of OpenShift to the Kafka topics with the operator for service binding provided by Red Hat.
With such a solution, developers only need a few steps to deploy applications anywhere. For example, developers can add, probe, and connect real-time streams via the web-based operating interface at cloud.redhat.com, the command line interface of Red Hat OpenShift Application (RHOAS), and the REST API. This also suggests that it will be easier to connect real-time streams to the microservices running on OpenShift and to develop real-time processing experience for users for provisioning data analysis applications.