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Monitoring

Introducing the Apache Kafka App Catalog

Working with Apache Kafka and real-time applications comes with challenges. Visibility into the deployed applications and their dependency on what we call the “data fabric” is one of them (For the sake of this blog, it means Kafka and all its state and configuration). If you’ve built a multi-tenant real-time data platform with Kafka, where teams are deploying applications outside your jurisdiction, this is where the pain is particularly acute. It goes something like this.

Tracing With Zipkin in Kong 2.1.0

There is a great number of logging plugins for Kong, which might be enough for your needs. However, they have certain limitations: Most of them only work on HTTP/HTTPS traffic. They make sense in an API gateway scenario, with a single Kong cluster proxying traffic between consumers and services. Each log line will generally correspond to a request which is “independent” from the rest.

Observability For Your Microservices Using Kong, Kubernetes, and Prometheus

In this video, Kevin Chen, Developer Advocate at Kong, will explain how to set up Prometheus monitoring with Kong Gateway to get black box metrics and observability for all of your services deployed on Kubernetes. This guide can also be applied to other solutions like StatsD, Datadog, Graphite, InfluxDB etc.

Everything you want to know about Kafka monitoring

Apache Kafka is a popular and powerful component of modern data platforms. But it's complicated. Complicated to run, complex to manage and crucially - it's near impossible to drive Kafka adoption from the command line across your organization. So here's your how-to for seeing it through to production (... and possibly fame and fortune). We cover key principles for Kafka observability and monitoring.

It Takes Two to Kafka: AWS MSK + DataOps

I ordered a ride share recently from a beach; the app struggled to find a car, so I had to make several requests. After the fourth or fifth attempt, my bank alerted me to possible fraudulent activity on my credit card via SMS. Each time I ordered a ride, the service put a pending charge on my card. After I texted back that it was just me, the bank reactivated my account. Though the process was annoying, I felt reassured my bank could detect possible fraudulence that quickly.

Will your streaming data platform disturb your holiday?

Here's why you need to double down on your DataOps before your vacation. In the past few months, everything has changed at work (or at home). Q1 plans were scrapped. Reset buttons were smashed. It was all about cost-cutting and keeping lights on. Many app and data teams sought quick solutions and developed workarounds to data challenges and operational problems as people prepared to work from home for the foreseeable future. And now, it’s time for a holiday.

Anodot Tutorial: Monitoring AWS Usage with Machine Learning

A 3-minute guide to help you start monitoring your AWS usage on Anodot's machine learning platform. Once it's up and running, Anodot will continuously monitor your AWS usage and deliver real-time alerts when there's an anomalous spike or drop. This powerful capability enables you to act quickly, far before costs get out of hand.

Removing Kafka bottlenecks with DataOps

Our CTO, Andrew Stevenson was interviewed by Alan Shimel for TechStrong TV. The discussion was all about hot data topics such as DataOps, DevOps and practices to successfully enable Kafka. Andrew narrates his journey from civil engineering to starting Lenses.io with Antonios, our CEO, to help organizations succeed with real-time data.