Operations | Monitoring | ITSM | DevOps | Cloud

Hi there! If you're in the tech world, you've probably heard about the trend of companies moving from Heroku to AWS. At Qovery, we've seen an increasing demand from companies looking to make this move. And for good reasons! Here are the top 4 reasons why companies are choosing AWS over Heroku.

Application performance monitoring (APM) involves a mix of tools and practices to track specific performance metrics. Engineers use APM to monitor and maintain the health of their applications and ensure a better user experience. This is crucial to high quality architecture, development, and operations, but it can be difficult to achieve in Kubernetes since the container orchestration system doesn’t provide an easy way to monitor application data like it does for other cluster components.

In this article, we will dive into Kubernetes network monitoring and metrics, examining these concepts in detail and exploring how metrics in an application can be transformed into tangible, human-readable reports. The article will also include a step-by-step tutorial on how to enable Calico’s integration with Prometheus, a free and open-source CNCF project created for monitoring the cloud.

We’re pleased to announce the availability of Kubewarden 1.5.0! This release brings the usual amount of small bug fixes, dependency updates, and a major security enhancement. Let’s take a closer look!

If you need to deploy a lot of microservices at once and manage them at scale, Kubernetes is hard to beat. But Kubernetes also brings additional complexity that you just might not need. You would be smart to ask yourself these three questions before getting started with Kubernetes.

How is your organization handling Kubernetes observability? What tools are you using to monitor Kubernetes? Is it a time-consuming, manual process to collect, store and visualize your logging, metrics and tracing data? And, what are you actually getting out of all that investment? At Logz.io we’re trying to make this process easier for customers who are serious about Kubernetes observability. We’ve made significant investments in this area for Kubernetes use cases.

Many organizations rely on distributed tracing in Datadog APM to gain end-to-end visibility into the performance of their Kubernetes applications. But as teams grow, it can become impractical for them to manually configure each new application with the libraries and environment variables needed for tracing.

Kubernetes turns 9 this year and with its maturity each year, it brings new challenges that drive seismic influence across the rapidly changing cloud native ecosystem. Each year we see new tools created and existing solutions optimized from new lightweight distributions, new features across Kubernetes management platforms, and container security solutions, all adding value to users but simultaneously contributing to the complexity are facing to run Kubernetes successfully.

With the current macroeconomic situation, it's more important than ever to keep a close eye on our cloud costs. But here at Qovery, we don't just focus on cutting costs - we also want to make sure we're getting the most bang for our buck. In other words, we want to consume our budget in a way that gives us the most resources.

Kubernetes makes it easier for businesses to automate software deployment and manage applications in the cloud at scale. However, if you’ve ever deployed a cloud native app, you know how difficult it can be to keep it healthy and predictable. DevOps teams and SREs often use distributed tracing to get the insights they need to learn about application health and performance.