Operating Apache Kafka with Cruise Control

There are two big gaps in the Apache Kafka project when we think of operating a cluster. The first is monitoring the cluster efficiently and the second is managing failures and changes in the cluster. There are no solutions for these inside the Kafka project but there are many good 3rd party tools for both problems. Cruise Control is one of the earliest open source tools to provide a solution for the failure management problem but lately for the monitoring problem as well.


A Complete Guide to Monitoring Apache Kafka - Part 2

In the first part of this blog, we covered the basics of the Kafka ecosystem and explored the options for exporting Kafka metrics—first using the Jolokia JVM agent and then via the Prometheus JMX agent. Here in this post, we’ll go through some key Kafka metrics that are available on Grafana for building visualizations and alerts. Although Kafka provides hundreds of metrics, as described here , we are going to cover the most important ones to monitor.


A Complete Guide for Monitoring Apache Kafka - Part 1

Apache Kafka is an open-source platform for distributed data streaming that provides highly reliable and fault-tolerant capabilities to process a large number of events using the publish-subscribe model. Kafka also provides the capability to store and process events per a given use case and requirements, plus it can run as a single node or scale up to a cluster of nodes.


Event-Driven Architecture is unblocking data-driven decisions in shipping

In March 2021, a 200,000 tonne ship got stuck in the Suez Canal, and the global shipping industry suddenly caught the world’s attention. It made us realize ships play an important role in our daily lives. Really important in fact; 90% of the things we consume arrive by ship. Take a look at this map. By visualizing vessel routes over time, the pattern creates a map of the earth. Note the lack of vessels travelling close to the coast of Somalia where piracy is common.


Assessing security risks with Kafka audits

Suppose that you work for the infosec department of a government agency in charge of tax collection. You recently noticed that some tax fraud incident records went missing from a certain Apache Kafka topic. You panic. It is a common requirement for business applications to maintain some form of audit log, i.e. a persistent trail of all the changes to the application’s data. But for Kafka in particular, this can prove challenging.


Increase compliance with Kafka audits

Suppose that you work for a government tax agency. You recently noticed that some tax fraud incident records have been leaked on the darknet. This information is held in a Kafka Topic. The incident response team wants to know who has accessed this data over the last six months. You panic. It is a common requirement for business applications to maintain some form of audit log, i.e. a persistent trail of all the changes to the application’s data to respond to this kind of situation.


How to create a Kafka topic (the safe way)

We live in a dynamic world. It is safe to say that companies aim to speed up time-to-market and out-innovate their competition with Kafka, but at the same time struggle with some limitations. These can range from compliance-related setbacks for regulations such as GDPR, CCPA and HIPAA, to self-service slip-ups that could see a whole Kafka cluster going down. Even something as seemingly innocuous as configuring and creating a Kafka Topic can lead to operational U-turns, slowdowns and even downtime.


Get comprehensive monitoring for your Apache Kafka ecosystem instances quickly with Grafana Cloud

We are happy to announce that the Kafka integration is available for Grafana Cloud, our composable observability platform bringing together metrics, logs, and traces with Grafana. Apache Kafka is an open source distributed event streaming platform that provides high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.


Lenses magnified: Enhanced, secure, self-serve developer experience for Kafka

In our world of streaming applications, developers are forever climbing a steep learning curve to stay successful with technologies such as Apache Kafka. There is no end to the debt and the detail you need to manage when it comes to Kafka - and particularly since it doesn’t come with guardrails to help you out, the stakes for making mistakes are high.


Monitoring Apache Kafka Clusters with Sumo Logic

Apache Kafka® is one of the most popular streaming and messaging platforms, commonly used in a pub-sub (publish-subscribe) model, where consumer software applications send data via messages that producer software applications can consume. Teams use Kafka for a variety of use cases, including monitoring user activity, sending notifications, and concurrently processing streams of incoming data such as financial transactions.