In this article, we will show how it’s easily possible to monitor AWS Fargate with Sysdig Monitor. By leveraging existing Prometheus ingestion in Sysdig, you will be able to monitor serverless services with a single-pane-of-glass approach, giving you confidence in running these services in production.

With enterprises and ISVs adopting containers and Kubernetes (k8s) to increase the agility and scalability of their applications, they would want more applications to be deployed on k8s. Applications can be a mix of stateful and stateless. Until recently, only stateless applications were supported by k8s. However, with the advent of persistent storage on k8s, stateful applications will be supported. In the pet Vs cattle analogy of service, you would want to treat the storage as cattle.

The public cloud offers great scalability and flexibility for customers and is a model where service providers make many decisions on their behalf. For example, in cloud service providers like Google Cloud Platform (GCP), Amazon Web Service (AWS) or Microsoft Azure, a cloud load balancer is spun up on demand. The load balancer gets an IP address automatically and your application is ready to be served.

This tip is for those who are using Prometheus federation to monitor multiple clusters. How should alertmanager be configured for multiple clusters? Let us say that if there’s an issue for Cluster A it only needs to send an alert for cluster A? In such cases, every alert should be routed to proper team based on labels (if there is problem with application A on cluster B - team responsible should be notified). In the above case, two alerts are triggered by the same rule.

Despite the difficulties we’ve all experienced during this pandemic, it has been fascinating to watch how human beings have come together as communities all over the world to support each other, and our Cloud Native community is no different.

We are excited to announce in-place Kublr Platform upgrades and a technical preview for external cluster support. That’s yet another step in making enterprise-grade Kubernetes adoption a breeze. While Kublr supports automated rolling cluster updates and upgrades with zero downtime, since our last release (1.17) updating the platform itself was still a semi-manual project supported by the Kublr team. Now, all it takes is the click of a button.

In today’s ever-changing world of DevOps, it is essential to follow best practices. That goes for security, access control, resource limits, etc. One of the most important things in the world of DevOps is continuous integration and continuous delivery, or CI/CD. Continuous integration is a crucial part of an efficient deployment. We are all guilty of repeating manual steps over and over again – especially when it comes to node configuration.

As service architectures have transitioned from the monolith to microservices, one of the tougher problems that organizations have had to solve is service discovery and load balancing. The advent of service mesh technologies seeks to solve these and other problems exacerbated by the number of hosts that has grown exponentially. In this article, we’re going to explore what a service mesh is.

If you've spent days (or even weeks?) trying to spin up a Kubernetes cluster for learning purposes or to test your application, then your worries are over. Spawned from a Kubernetes Special Interest Group, KIND is a tool that provisions a Kubernetes cluster running IN Docker.

Helm is a popular open-source tool used to manage and configure your Kubernetes cluster. Basically, it is a package manager (think Homebrew or NPM) built for Kubernetes. It helps automate processes like installing, configuring, upgrading, and removing items. This post will give you a brief introduction to Helm and how it might help you manage your Kubernetes cluster.