Apache Kafka® has become the de-facto standard for streaming data, helping companies deliver exceptional customer experiences, automate operations, and become software. As companies increase their use of real-time data, we have seen the proliferation of Kafka clusters within many enterprises. Often, siloed application and infrastructure teams set up and manage new clusters to solve new use cases as they arise.
Today, we’re excited to announce the general availability of Data Portal on Confluent Cloud. Data Portal is built on top of Stream Governance, the industry’s only fully managed data governance suite for Apache Kafka® and data streaming. The developer-friendly, self-service UI provides an easy and curated way to find, understand, and enrich all of your data streams, enabling users across your organization to build and launch streaming applications faster.
Amazon S3 is a standout storage service known for its ease of use, power, and affordability. When combined with Apache Kafka, a popular streaming platform, it can significantly reduce costs and enhance service levels. In this post, we’ll explore various ways S3 is put to work in streaming data platforms.
In a previous blog post (How To Survive an Apache Kafka® Outage) I outlined the effects on applications during partial or total Kafka cluster outages and proposed some architectural strategies to handle these types of service interruptions. The applications most heavily impacted by this type of outage are external interfaces that receive data, do not control request flow, and possibly perform some form of business transaction with the outside world before producing to Kafka.
Stepping into the world of Apache Kafka® can feel a bit daunting at first. I know this firsthand—while I have a background in real-time messaging systems, shifting into Kafka’s terminology and concepts seemed dense and complex. There’s a wealth of information out there, and it’s sometimes difficult to find the best (and, ideally, free) resources.
Hello there! My name is Maciej Mensfeld, and some of you might recognize me from my involvement in RubyGems Security, OSS commitments, or perhaps from Karafka: a multi-threaded, efficient Kafka processing framework tailored for Ruby and Rails. While I generally pen my thoughts on my personal blog, today's post is unique. This article results from a collaborative effort with the brilliant people over at AppSignal. To set the record straight, I don't work for AppSignal.
Realtime data is rapidly becoming a standard in many consumer applications. From responsive chat applications to low latency financial applications, nobody wants to refresh their browser for new data. With lots of data bouncing around Kafka behind a firewall, it begs the question of how you can serve this information to your users without sacrificing on latency. Ably provides a seamless way to serve this data to your end users devices, globally, through a direct integration with Confluent Cloud.
