Developers strive to produce efficient code. Many times, developers will add code to their repositories and test it to make sure it works, but they are forgetting one very important step: benchmarking! Benchmarking allows developers to see the performance impact on their code output. If properly integrated into a CI/CD pipeline, it could prevent catastrophic drops in performance before any code is shipped/deployed at all.
The benefits of Apache Kafka monitoring services are widely appreciated across the industry. Organizations that rely heavily on Apache Kafka for their data streaming needs can derive great benefit from the use of Kafka monitoring services. By keeping track of various different key performance indicators (KPIs) related to Kafka, such as message throughput and latency, organizations can ensure that their Kafka-based data pipelines are running as smoothly and efficiently as possible.
In order to answer this question, it is necessary to define what middleware is. It is generally accepted that middleware is software that sits between existing systems and processes and helps to smooth integration and interaction between them. Because of the sheer range of middleware and the scope of what it can do and affect in terms of business infrastructure, it is vital that it can be successfully monitored and managed.
Apache Kafka is a very popular open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Amazon MSK (Managed Streaming for Kafka) is a fully managed Kafka service that makes using Kafka even easier. But how do you get started with Kafka on AWS?
Apache Kafka is a very popular open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Amazon MSK is a fully managed Kafka service that makes using Kafka even easier. But how do you get started with Kafka on AWS? How do you migrate your existing Kafka environment to the cloud? How do you manage many Kafka environments at once?
Who’s faking it? Data-driven decision-making (and ensuring related investment is delivering on its promises) has been elevated in importance. Every enterprise is replacing opinion with data-driven decision-making, correct? A brand new research report from EMA (Enterprise Management Associates) titled, “A Data-Driven Enterprise” looks behind the curtain to separate facts and reality from fiction and aspiration. Here are some of the findings from the latest research on enterprises.
Nastel technical specialist, Terry House, has written a blog post here looking at the IBM MQ appliance and comparing it to the traditional software form of IBM MQ. He explores the additional security and cost benefits and also the additional monitoring and management requirements that are addressed by the Nastel Navigator X i2M platform.
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.
