Remember Microsoft’s trusty assistant, the annoying/endearing Clippy? We built something similar for the modern web, minus the annoying parts, and discovered that, if done right, it can increase user engagement and success with your product.
As the first part of a three-part series on Apache Kafka monitoring, this article explores which Kafka metrics are important to monitor and why. When monitoring Kafka, it’s important to also monitor ZooKeeper as Kafka depends on it. The second part will cover Kafka open source monitoring tools, and identify the tools and techniques you need to further help monitor and administer Kafka in production.
Open source software adoption continues to grow within enterprises (even for legacy applications), beyond just startups and born-in-the-cloud software. In this second part of our Kafka monitoring series (see the first part discussing Kafka metrics to monitor), we’ll take a look at some open source tools available to monitor Kafka clusters. We’ll explore what it takes to install, configure, and actually use each tool in a meaningful way.
Monitoring Kafka is a tricky task. As you can see in the first chapter, Kafka Key Metrics to Monitor, the setup, tuning, and operations of Kafka require deep insights into performance metrics such as consumer lag, I/O utilization, garbage collection and many more. Sematext provides an excellent alternative to other Kafka monitoring tools because it’s quick and simple to use.
Over the last six months, Opsgenie’s customer base has expanded significantly. We’ve become the tool of choice for teams that are new to operating always-on services, as well as those who have been left disappointed by alternative solutions. We can claim many advantages over our competition, but here are the top ten reasons Dev and Ops teams are choosing Opsgenie.
When I started Checkly, all the typical SaaS things around billing, credit cards and prorating confused the hell out of me. I understood them from an intellectual point of view, but not really from an implementation point of view.
The Linux Audit framework is a kernel feature (paired with userspace tools) that can log system calls. For example, opening a file, killing a process or creating a network connection. These audit logs can be used to monitor systems for suspicious activity.
Simple enough to be embedded in text as a sparkline, but able to speak volumes about your business, time series data is the basic input of Anodot’s automated anomaly detection system. This article begins our three-part series in which we take a closer look at the specific techniques Anodot uses to extract insights from your data.
Scenario Linux has a number of built-in tools, commands and files which can track and store information about every user activity. These tools are common in most Linux distributions and can be used to investigate suspicious logins or failed login attempts into the system. In this article, we will talk about some of the initial methods to identify possible security breaches. We will use an Amazon EC2 instance to show these commands.
When developing new applications, it’s typical to run into a variety of competitors with similar goals. This is one reason why it is not enough to create an application without ways to monitor and manage it. In fact, usually market leaders emerge rather quickly. So who are these market leaders?
