The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
18 months later, organizations around the globe are slowly but surely starting to welcome their employees back to the office – or at least thinking about it. But this is not a “back to normal” kind of thing. Most will recognize that something’s different this time around. Firstly, there is no clear one-size-fits-all return-to-office strategy.
Containers are lightweight, portable, easily scalable, and enable you to run multiple workloads on the same host efficiently, particularly when using an orchestration platform like Kubernetes or Amazon ECS. But containers also introduce monitoring challenges. Containerized environments may comprise vast webs of distributed endpoints and dependencies that rely on complex network communication.
Amazon Elastic File System (EFS) provides shared, persistent, and elastic storage in the AWS cloud. Like Amazon S3, EFS is a highly available managed service that scales with your storage needs, and it also enables you to mount a file system to an EC2 instance, similar to Amazon Elastic Block Store (EBS).
In Part 1 of this series, we looked at EFS metrics from several different categories—storage, latency, I/O, throughput, and client connections. In this post, we’ll show you how you can collect those metrics—as well as EFS logs—using built-in and external tools.
In Part 1 of this series, we looked at the key EFS metrics you should monitor, and in Part 2 we showed you how you can use tools from AWS and Linux to collect and alert on EFS metrics and logs. Monitoring EFS in isolation, however, can lead to visibility gaps as you try to understand the full context of your application’s health and performance.
Everywhere you look, you see something to do with software and applications. But for all this software to work well, the people behind them have to know how they work. For a software developer, this comes as no surprise. They need to know how their code is working when deployed. Before the software deploys, they want to iron out errors, so they don’t become problematic and frustrate customers.
We are excited to announce the release of Grafana 8.1. This release builds upon our promise of a composable, open observability platform with new visualizations and dynamic panel configuration options while extending the functionality we launched in Grafana 8.0. Get 8.1 You can get started with Grafana in minutes with Grafana Cloud. We have free and paid Grafana Cloud plans to suit every use case — sign up for free now. And now, on to the highlights for 8.1.
After building Lightrun for the JVM – an easier way to get a better grasp on production applications written in Java, Scala, and Kotlin – we’re pleased to announce the release of Lightrun’s developer-native observability platform for Python!
