In a Kubernetes environment, applications operate across multiple nodes within a cluster, and application services can be distributed across multiple clusters and multiple clouds, making tracking the health of an application and the infrastructure it depends on quite challenging.
Kubernetes monitoring is the process of gathering metrics from the Kubernetes clusters you operate to identify critical events and ensure that all hardware, software, and applications are operating as expected. Aggregating metrics in a central location will help you understand and protect the health of your entire Kubernetes fleet and the applications and services running on it.
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It's common when working with Kubernetes that we perform several queries to our cluster objects such as nodes, deployments, builds, pods and we don't always get the set of information we need, exposed by default via kubeclt get, having to resort in these cases to search the entire object bringing information beyond what is desired.
You may be wondering why you should bother with Kubernetes' log management tools?
Kubernetes dominates the container orchestration market and is often used to host microservices. Each instance of a microservice generates large numbers of log events that can quickly become difficult to manage. But worse, when something goes wrong, finding the root cause can be tough due to the complex interactions between services and the near-infinite number of possible failure modes. This potential for trouble has fueled the popularity of log management tools for Kubernetes.
Kubernetes is an open-source container orchestration that impacts the functions of runtime security. A successful Kubernetes deployment lies in choosing a suitable environment based on application requirements, investments, and infrastructure. Users face technical challenges subjected to Kubernetes deployment on cloud (single, multi, or hybrid) or on-premises that require different tools. These factors affect the approach to security with Kubernetes. Let’s see the threat model and how to overcome them.
The threats attacking the Kubernetes environment — regardless of the deployment methods — are as follows:
A centralized framework for monitoring your Kubernetes ecosystem offers valuable insights into how containerized workloads are running and can help you optimize them for better performance. However, as with any distributed system, monitoring Kubernetes is a complex undertaking. This Refcard first presents the primary benefits and challenges, and following, you'll learn about the fundamentals of building a Kubernetes monitoring framework, including how to capture monitoring data insights, leverage core Kubernetes components for monitoring, identify key metrics, and the critical Kubernetes components and services you should be monitoring.
Updated September 2019
In the last few years, Kubernetes has laid waste to its fellow competitors in the battlefield of container orchestration. Sadly, Docker Swarm hasn’t been a major contender since 2016 and, like AWS, admitted defeat by pledging K8s support and integration. Since Kubernetes has skyrocketed to popularity as the container solution of choice, here’s a comprehensive list of all the tools that complement K8s to further enhance your development work.
In part one of this series, I discussed the rise of microservice architecture and the reliance on Kubernetes and Docker for container orchestration and management. I also shared some of the challenges these new technologies present and what sources of data we need in order to effectively monitor our Kubernetes environments. In my concluding comments, I mentioned that Prometheus provides an excellent starting point for collecting and analyzing this data. In this post, I’ll give a brief overview of Prometheus, illustrate how to collect Kubernetes data with Prometheus, and discuss some of the pros and cons of the Prometheus approach.
In the next installment of this series, I’ll address some of those cons, illustrating how Sensu and Prometheus are complementary.
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