When traffic increases, we need to have a way to scale our application to keep up with user demand. With Kubernetes multi-cluster management through Rancher, scaling has never been easier and more efficient. Read here about scaling Kubernetes and the challenges you might be facing when managing a hybrid cloud environment.
In the past, applications would be deployed by installation on a host, using the operating system package manager. This was a heavy solution with tremendous reliance on the operating system package manager and increased complexity with libraries, configuration, executables and so on all interconnected. Then came containers. Containers are small and fast, and are isolated from each other and from the host.
In this blog I will show some best practices for instrumenting Docker containers, using docker-compose with a few popular AppDynamics application agent types. The goal here is to avoid rebuilding your application containers in the event of an agent upgrade, or having to hard-code AppDynamics configuration into your container images. In my role as a DevOps engineer working on AppDynamics’ production environments, I use these techniques to simplify our instrumented container deployments.
Kubernetes is an open-source container-orchestration system for automating application deployment, scaling, and management. It was originally designed by Google, and is now maintained by the Cloud Native Computing Foundation.
Security is a key consideration for any organization seeking to standardize and scale their cloud-native platforms. Falco, the behavioral activity monitoring tool from Sysdig, is becoming a popular option for open source container runtime security on cloud-native platforms built using Kubernetes, Cloud Foundry, and OpenShift.
A couple weeks ago, we released the Helm chart and docker images so you could install StackStorm Enterprise HA cluster in Kubernetes. Today, we’re glad to announce that the Community free and open source edition of StackStorm HA is now available, too!
Lately, IT teams are looking for Docker monitoring tools as legacy products like cAdvisor and Sysdig cloud do not offer greater insights. Docker monitoring needs a crucial change in the way your agents, plug-ins, and monitoring works to support containers. Many enterprises have started deploying significant production workloads on Docker, it seems there is a substantial shift towards adopting Docker.
In this post we will cover how to monitor the Java Runtime Environment (JRE). You will learn how to assess the performance of your Java application by profiling its memory usage, the garbage collector metrics, monitoring Java daemon and user threads and other fundamental JRE metrics. We will finish with a real Java JRE troubleshooting example using opensource Sysdig and Docker.
Here at Sysdig we follow Kubernetes development pretty closely. Next Tuesday the next release of our favourite orchestration tool will get out of the oven freshly baked, so this is a summary of what’s new in Kubernetes 1.12!
More groups are progressing from just talking about Event-Driven Automation to actually doing it in practice. StackStorm helps make this easy. When organizations start offloading business-critical tasks and automating for real it becomes essential to ensure that the Automation engine itself is not a single point of failure when it is responsible for recovering a fleet of servers, managing datacenters, and automating remediations.
