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By Navdeep Sidhu
In a Kafka setup, high availability isn’t just nice to have—it’s a lifeline. Downtime, data loss, or hiccups in message flow can make or break critical applications. Let’s be real: setting up Kafka brokers to be resilient takes some fine-tuning, but it’s absolutely worth it. Imagine dealing with failovers smoothly or knowing your data is protected even if a broker goes down—this is what configuring for resilience is all about.
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By Richard Nikula
When managing Kafka clusters, health checks are essential—not just a luxury. They’re your frontline defense in maintaining stability and performance, helping you catch issues before they snowball. Let’s dive into effective ways to assess your Kafka cluster’s health, from tracking key metrics to taking proactive steps that keep your operations running smoothly.
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By Scott Corrigan
Let’s be honest: setting up Kafka monitoring on Kubernetes can feel like you’re trying to solve a puzzle without all the pieces in place. Between connectivity snags, configuration issues, and keeping tabs on resource usage, it’s easy to feel like you’re constantly firefighting. But tackling these issues head-on with a few go-to solutions can save a lot of headaches down the road.
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By Sean Riley
Running Kafka at peak efficiency doesn’t come cheap. But with some smart tweaks, it’s entirely possible to keep costs down while making sure everything flows smoothly. The key is to balance your resource usage across CPU, memory, and storage to get the most bang for your buck. Let’s dive into some strategies that will help you stretch those resources, streamline your Kafka setup, and avoid breaking the bank.
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By Navdeep Sidhu
Managing a Kafka cluster is no small feat. While Kafka’s distributed messaging system is incredibly powerful, keeping it running smoothly takes careful planning and a keen eye on the details. Small mistakes in Kafka management can quickly add up, leading to bottlenecks, unexpected downtime, and overall reduced performance. Let’s explore some common Kafka management pitfalls and, more importantly, how to steer clear of them.
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By Scott Corrigan
When it comes to modernizing MQ systems, finding the right balance between performance and cost can feel like walking a tightrope. With budget constraints on one side and the need for high performance on the other, it’s easy to tip too far in either direction. But here’s the thing—when you modernize your MQ infrastructure thoughtfully, you can achieve both efficiency and budget optimization.
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By Richard Nikula
Keeping a Kafka cluster optimized can feel like a balancing act. Every piece—brokers, partitions, producers, and consumers—has to work in harmony, or you’ll start running into bottlenecks. To get Kafka to run smoothly and handle growing traffic loads, balancing load across the system is key. Let’s go over practical load-balancing techniques that can improve Kafka performance, keep everything running efficiently, and prevent data slowdowns from building up.
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By Sean Riley
Keeping Kafka running at peak efficiency takes more than just a smooth setup. Fine-tuning Kafka producers and consumers is key to making sure every message is processed quickly and accurately. A little tweaking here and there can help you avoid bottlenecks, increase throughput, and keep your whole data pipeline running smoothly. In this guide, we’ll dive into practical tips for configuring producers and consumers for maximum efficiency.
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By Scott Corrigan
In mainframe environments, where workloads are high and demands on reliability are even higher, tuning MQ systems isn’t just beneficial—it’s essential. When MQ systems are optimized, your organization can maintain faster, more reliable message processing, handle greater transaction volumes, and ultimately keep up with today’s demands. But how do you go about tuning MQ for optimal performance? Let’s break down some best practices that will make a real difference.
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By Richard Nikula
Let’s face it—when it comes to security in Kafka, you can’t afford to mess around. With more and more sensitive data streaming through Kafka environments, it’s no surprise that Kafka security auditing has become a crucial part of ensuring both compliance and overall security. But if you’re new to this or feel like your current process needs a tune-up, don’t worry—we’ve got your back.
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By meshIQ
Application and integration DevOps professionals rely heavily on messaging, event processing, and streaming to build mission-critical applications. meshIQ delivers a single pane of glass that provides visibility into complex M/E/S/H environments, significantly reducing the risks to application stability and performance.
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By meshIQ
Nastel XRay 1.5 release builds on industry analyst acclaim for leading AIOps & transaction observability vendor. Nastel Technologies, the leader in integration infrastructure management (i2M) solutions, announced today significant enhancements to its versatile AIOps and Transaction Observability solution, including machine learning for integration management, and visualization of business flows and IoT locations.
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By meshIQ
Introduction video for Nastel Technologies' solution for managing and monitoring your digitized transaction flow based on middlewares such as IBM MQ, Kafka, Solace or TIBCO. Nastel can help you through all processes of workflow digitization.
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By meshIQ
Frustrated with how long it takes to roll out new applications (and updates) when changes are required to messaging middleware environments? Is your team getting blamed for issues outside your control? During this short webinar and open Q&A, we will discuss.
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By meshIQ
This 45 minute video covers the fundamentals of MQ statistics, including architecture, setup and usage and several related use cases.
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By meshIQ
Nastel MSK is an option for using Apache Kafka. This introduction explains the basics of Amazon MSK and the show how in just a matter of minutes, you can be using Nastel to manage, monitor and track your Kafka usage.
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By meshIQ
This demo covers Custom attributes and how they can be used to display, filter and monitor data managed by Nastel.
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By meshIQ
IBM DataPower Gateway is the latest variant of DataPower and helps organizations meet the security and integration needs of a digital business in a single multi-channel gateway. It provides security, control, integration and optimized access to a full range of mobile, web, application programming interface (API), serviceoriented architecture (SOA), B2B and cloud workloads.
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By meshIQ
This a complex question with deep implications that touch many areas of the business including the executive team, finance, procurement and Human Resources. In this short webinar we will discuss some of the areas that must be considered and provide you with some strategic ideas to improve your business. This presentation is gleaned from the hundreds of man-years of experience our experts have had in answering this exact question.
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Observability Platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).
Application and integration DevOps professionals rely heavily on messaging, event processing, and streaming to build mission-critical applications. meshIQ delivers a single pane of glass that provides visibility into complex M/E/S/H environments, significantly reducing the risks to application stability and performance. This speeds up mean-time-to-resolution (MTTR) and improves mean-time-between-failures (MTBF), ultimately improving application SLAs and customer experience. From modern Kafka-based streaming to legacy messaging technologies like IBM MQ, meshIQ supports every major platform out there.
A must have for every Messaging Deployment:
- Governance: meshIQ delivers granular access controls to manage configurations across the MESH to reduce downtime and quick recovery from outages.
- Introspection: Provides the ability to find, browse, track, and trace messages to detect bottlenecks and speeding up root-cause analysis.
- Intelligence: Unlocks the integration blackbox to deliver visibility across the MESH infrastructure to visualize, analyze, report, and predict.
- Action: Delivers the ability to trigger automated actions based on pre-defined criteria or intelligent actions determined by AI/ML.
Intelligence From Integration.