Logs are one of the most valuable assets when it comes to IT system management and monitoring. As they record every action that took place on your network, logs provide the insight you need to spot issues that might impact performance, compliance, and security. That’s why log management should be part of any monitoring infrastructure.
Do you use an error tracking tool for your website? Have you ever tried to debug a problem that a user reported, and when you looked at your error tracking tool the reported error was simply: “Script Error”? Such errors are impossible to further debug because there is no additional information apart from that message.
Time to first byte, first contentful paint, DNS response time, round-trip time, and the list goes on and on. With all of these metrics, how are you supposed to know which are the most important ones that you should monitor? To understand what those numbers are supposed to look like, you’ll have to get a reference point. Something that’s supposed to give you a starting point.
When it comes to troubleshooting application performance, metrics are no longer enough. To fully understand the environment you need logs and traces. Today, we’re going to focus on your Java applications.
Having visibility into your Java application is crucial for understanding how it works right now, how it worked some time in the past and increasing your understanding of how it might work in the future. More often than not, analyzing logs is the fastest way to detect what went wrong, thus making logging in Java critical to ensuring the performance and health of your app, as well as minimizing and reducing any downtime.
Monitoring your system and infrastructure is critical to ensure the performance of your services. In fact, as software development moves faster and faster, alerting and monitoring becomes an indispensable practice for modern DevOps teams. Why is that exactly? That’s what I’m going to discuss today.
Over the past few years, we’ve seen an almost obsession with developing and adopting CI/CD tools throughout the DevOps community. There are thousands of “how-to’s”, “top x tools”, and “tool x vs tool y” type articles, and it has gotten to the point where it’s quite difficult to figure out how and which one to pick as your own.
If you are anything like us here at Sematext, you are likely always trying to automate any tedious, repetitive tasks. Repetitio est mater… boringdorum. Setting up monitoring falls in that category. You either do it manually every time you provision a new piece of infrastructure or service, or you automate it. Note that by “service” I mean either an instance of your own application or something like Nginx or Elasticsearch or MySQL or …
Amazon Elastic Block Store (EBS) provides block storage for applications that are running in the cloud. However, not every company is getting the most out of the EBS volumes they are using. Some companies can pay too much for EBS volumes without utilizing the allocated storage and IOPS. Other organizations may pay high prices because they are using the wrong disk type for their needs. This article explains five techniques you can use to optimize the performance of your EBS workloads.
When it started to really get traction as a concept, almost 10 years ago, DevOps was primarily used to push rapid changes to web environments with minimal impact for the users. That might still be true today but DevOps as a concept evolved. A lot. We now rely on DevOps models to move at high velocity, adapting and developing at speeds that are light years away from anything we’ve seen before. It’s the way we deliver, test, monitor, and release functionalities.
