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.
Every database administrator (DBA) is—first and foremost—human. And everyone makes mistakes. It’s not the absence of mistakes but rather how you prepare for those mistakes that makes you a great DBA. Luckily, there are many ways to prepare for those mishaps, whether the errors are made by you or someone else on your team. One commonly made mistake is to drop an object in a database or accidentally delete data.
GitHub Actions are a powerful way to add automation to any source code repository. When you take that power and connect it with InfluxDB, you get an amazing combination that allows you to automate data generation, manage GitOps workflows, and a whole lot more. This post will highlight some of the interesting ways to use InfluxDB and GitHub Actions.
It's time for monthly product updates aka Signal #03. This month's release hit a major milestones with PRs from 10+ contributors. Let's see what humans of SigNoz have been upto 🙌
With the introduction of opCharts v4.2.5 richer and and more meaningful data can be used in decision making. Forewarned is forearmed the poverb goes, a quick google tells me “prior knowledge of possible dangers or problems gives one a tactical advantage”. The reason we want to baseline and threshold our data is so that we can receive alerts forewarning us of issues in our environment, so that we can act to resolve smaller issues before they become bigger.
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.
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!
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.
Your feedback is what makes Honeycomb better. We ship changes often (you can see updates in real time on our changelog), so it can be easy to miss some of the new improvements that can help you get the most out of Honeycomb. Whether it’s a big new product feature or an enhancement of existing features, you may not always be up on the latest goodness waiting for you in Honeycomb.