In this post, you’ll learn which metrics to keep an eye on to improve your application performance, how AppSignal works, and how to interpret the data it generates. Grab a stroopwafel, make yourself comfy, and let’s start!
During the past years we made plenty of contributions to improve the current state of the Windows monitoring. We tried to improve the actual installation with the Icinga 2 Powershell Module, allowing users to easier automate installation and configuration of Icinga 2. On a long term we however wanted to improve the monitoring of Windows infrastructures entirely, by not only providing new plugins but also to increase the contribution by the community.
Amazon MQ is a managed ActiveMQ messaging service hosted on the AWS cloud. Amazon MQ’s brokers route messages between the nodes in a distributed application. Each broker is a managed AWS instance, so your messaging infrastructure doesn’t require the maintenance and upfront costs of a self-hosted solution.
In Part 1 of this series, we saw how Amazon MQ routes messages between services in a distributed application, and we looked at some of the key metrics that describe the performance of the message broker and its destinations. Now that we’ve introduced the metrics and their meaning, we’ll look at some tools you can use to collect and query metrics from Amazon MQ:
In Part 2 of this series, we showed you how to use CloudWatch to monitor metrics and logs from Amazon MQ. With CloudWatch, you can easily create ad-hoc graphs to visualize the performance of your messaging infrastructure and other AWS services you use (such as EC2, Lambda, and S3). But to monitor your Amazon MQ brokers, destinations, and clients alongside the rest of your applications and infrastructure, you need a monitoring platform that easily integrates with your whole technology stack.
To centralize logging from your entire stack—from traditional infrastructure to serverless components—Datadog is announcing native support for the launch of FireLens for Amazon ECS. FireLens streamlines logging by enabling you to configure a log collection and forwarding tool such as Fluent Bit directly in your Fargate tasks. We’ve partnered with AWS to provide built-in Fluent Bit support for Datadog so that you can now seamlessly route container logs from AWS Fargate.
“With cybercrime heading into the tens of billions of records stolen, and trillions of dollars in damages, we are proud to recognize ManageEngine as an award-winning innovator that offers a new approach to defeat these criminals,” said Pierlugi Paganini, editor-in-chief, Cyber Defense Magazine.
You might have seen a few of my tutorial videos on Grafana and Grafana Loki. If not, check them out here. These videos are a bit of an experiment to showcase the awesome work being done by the Grafana OSS community and for me to understand the technology better. I got a lot of encouraging feedback on the videos, so I plan to continue making them. A few folks also wanted to know why and how I created them. Happy to share the details here with you, and I look forward to your Grafana videos :)
What a crazy first day at Microsoft Ignite 2019! As most of you know, Ignite 2019 kicked off yesterday (November 4th) in Orlando Florida, hosting a whopping 26,000 attendees from around the globe – and 26,000 it did feel like, our booth was swamped! Azure definitely took centre stage on Day 1 with Microsoft announcing new releases that take care of data from every angle.
Today, we’re releasing TrackJS Global Error Statistics to the public. This aggregated production data is a useful measure of the state of client-side JavaScript errors and the quality of the web. We break it down by the most common errors, browsers, and operating systems. We did this a few years ago with the State of Client-Side JavaScript Errors. It was quite useful, but very time consuming to produce.
