From setting up new hires with everything they need to get to work to troubleshooting technical difficulties, IT teams often field the same kinds of requests over and over. And while each request might feel like a small task, collectively they can add up to a huge time sink in the long run.

Apache Kafka is a distributed messaging system that can be used to build applications with high throughput and resilience. It is often used in conjunction with other big data technologies, such as Hadoop and Spark. Kafka-based applications are typically used for real-time data processing, including streaming analytics, fraud detection, and customer sentiment analysis. There are many derivatives such as Confluent Kafka, Cloudera Kafka, and IBM Event Streams.

The concept of AIOps is simple: Infuse artificial intelligence(AI) into IT to make operations speedier and more efficient. In theory, AIOps at its best should lead to an autonomous IT environment in which functions can run themselves with little or no human intervention. In practicality, the path to this nirvana state is anything but straightforward and raises several questions. Where should you start? How do you measure the value? Is AI ready to scale across production environments?

Mattermost v6.5 is generally available today and includes the following new features (see changelog for more details).

IBM Cloud Pak for Integration (CP4I) is a platform that helps you quickly and easily integrate your hybrid cloud applications with the systems and applications that are important for running your business. It can help to collaborate between the different application teams and businesses that exist in your organization and ensure that they are working together at maximum efficiency.

As organizations have moved toward a microservices design pattern, the need for reliable and performant solutions that enable decoupled services to communicate with one another has grown. RabbitMQ is an open-source message broker designed for this purpose. We’ll discuss what RabbitMQ is, how it works, why it needs to be monitored and how Sumo Logic can effectively do this.

There’s a lot to consider when engineering and implementing software, whether as an update patch or a newly-introduced product. End users have certain expectations when introduced to new or updated software—at the top of the list are aesthetics, ease of use, stability, and response time—the last two of which can be significantly improved when you employ application performance management or APM.

Today, I am excited to introduce the NSQ integration available for Grafana Cloud, our platform that brings together all your metrics, logs, and traces with Grafana for full-stack observability. NSQ is a real-time distributed messaging platform designed to operate at scale, handling billions of messages per day. It’s a simple and lightweight alternative to other message queues such as Kafka, RabbitMQ, or ActiveMQ. This will walk you through how to get the most out of the integration.

A common denominator that Mattermost and most corporate applications share is the challenge users can face in successfully setting up a self-hosted instance in their own cloud account. Even with cloud-specific documentation, there’s almost always a hard requirement of understanding said documentation, resolving any errors encountered along the way, and maintaining the application.

ActiveMQ is a message-oriented middleware, which means that it is a piece of software that handles messages across applications. It acts as a broker that can help facilitate asynchronous communication patterns like publish-subscribe and message queues. The main goal of those servers is to create a scalable and reliable message bus that different components can use to communicate with each other.