Some systems want to receive large amounts of data at once every day, while others want to get them within milliseconds of data generation. Most data pipelines are somewhere in between. A good data integration system can well support the various timeliness requirements of data pipelines, and when business requirements change, data tables with different timeliness requirements can be easily migrated. As a stream-based data platform, Kafka provides reliable and scalable data storage, which can support almost real-time data pipelines and hourly batch processing.
Introduction To kPow
kPow was developed by developers, for developers with complete functions and rich data displayed. At the same time, users can perform some simple cluster management operations on the interface.
It is the ultimate kafka monitoring tool for engineers.
Yahoo’s Kafka-manager Application Description
The graphical web is often more intuitive than the command line. An example of this is Yahoo’s Kafka-manager is an open-source project from Yahoo. The web interface is quite easy to use, and the installation is very convenient.
We use Apache Kafka Connect to stream data between Apache Kafka and other systems, which is the most reliable. Kafka Connect collects metrics or collects the entire database from the application server into Kafka topics. It can provide low-latency available data for stream processing.
Producers can write data to Kafka frequently or on-demand, consumers can read the data as soon as it arrives, or read the backlog of data every once in a while.
Anyone who has used Kafka clusters knows that it is challenging to remember Kafka commands as a novice, so we generally look for management tools that can be operated on the page. Therefore different GUIs are a must.
Supported Features While Using Different GUIs
- Manage multiple clusters
- Easily check the cluster status (topic, consumer, offset, proxy, copy distribution, partition distribution)
- Run preferred copy election
- Use the option to generate partition assignments to select the agent to use
- Run partition reassignment (based on generated allocation)
- Add a section to an existing topic.
Kafka Graphical Interface Type
By implementing a specific Java interface, you can create a connector. We have an existing set of connectors, or we can write a facility for custom connectors for us.
However, if there is no benefit of a subclass loader, this code will be loaded directly into the application, OSGi framework, or similar code.
There are several GUIs in the “Confluent Open Source Edition” download package; they are:
However, there is no way to download these connectors separately. Still, we can extract them from Confluent Open Source because they are open source, and we can also download and copy them into a standard Kafka installation.
Kafka plays the role of a large buffer here, reducing the time-sensitivity between producers and consumers. Real-time producers and batch-based consumers can exist at the same time or any combination. It has also become easier to implement a backpressure strategy. Kafka itself uses backpressure strategy (if necessary, it can be delayed to send confirmation to the producer), while the consumer completely determines the consumption rate.
Kafka itself supports “at least one pass.” If combined with an external storage system with a transaction model or unique key characteristics, Kafka can also achieve “only one pass.” Because most of the endpoints are data storage systems, they provide the primitive support of “only one pass,” so Kafka-based data pipelines can also achieve “only one pass.” It is worth mentioning that the Connect API provides an API for processing offsets for integrating external systems so that the connector can build an end-to-end data pipeline with only one pass. Many open source connectors support only one pass. Paid services, on the other hand, offer regular updates through their kafka docker hub.
Configure Kafka Connect
Usually, using a command-line option pointing to the config file that contains the worker instance options, each worker instance will be started—for example, Kafka’s message broker detailed information, group-id.