POD Readiness Gates
Your application can inject extra feedback or signals into PodStatus, Pod readiness. To use this, set readinessGates in the Pod's spec to specify a list of additional conditions that the kubelet evaluates for Pod readiness.
Your application can inject extra feedback or signals into PodStatus, Pod readiness. To use this, set readinessGates in the Pod's spec to specify a list of additional conditions that the kubelet evaluates for Pod readiness.
Setting up a Kubernetes stack according to best-practices requires expertise, and is necessary to set up a stable cluster that is future-proof. Simply running a manged cluster and deploying your application is not enough. Some additional things are needed to run a production-ready Kubernetes cluster. A good Kubernetes setup makes the life of developers a lot easier and gives them time to focus on delivering business value.
Unlike Apache Mesos, which can scale up to 10,000 nodes out of the box, scaling Kubernetes is challenging. Kubernetes’ scalability is not just limited to the number of nodes and pods, but several aspects like the number of resources created, the number of containers per pod, the total number of services, and the pod deployment throughput. This post describes some challenges we faced when scaling and how we solved them.
The core practices for remote work at Netlify are prioritising asynchronous communication, being intentional about our remote community building, and encouraging colleagues to protect their work-life balance. Sustainable remote work starts with sustainable working hours, which includes making yourself "almost" unreachable with clear boundaries and protocols for out of hours contact
Karpenter is an open-source, flexible, high-performance Kubernetes cluster autoscaler built with AWS. It helps improve your application availability and cluster efficiency by rapidly launching right-sized compute resources in response to changing application load. Karpenter also provides just-in-time compute resources to meet your application’s needs and will soon automatically optimize a cluster’s compute resource footprint to reduce costs and improve performance.
Whenever one service or system calls another, failures can happen. These failures can come from a variety of factors. They include servers, networks, load balancers, software, operating systems, or even mistakes from system operators. We design our systems to reduce the probability of failure, but impossible to build systems that never fail. So in Amazon, we design our systems to tolerate and reduce the probability of failure, and avoid magnifying a small percentage of failures into a complete outage. To build resilient systems, we employ three essential tools (timeouts, retries, and backoff).
Amazon VPC Container Networking Interface (CNI) Plugin supports “prefix assignment mode”, enabling you to run more pods per node on AWS Nitro based EC2 instance types. To achieve higher pod density, the VPC CNI plugin leverages a new VPC capability that enables IP address prefixes to be associated with elastic network interfaces (ENIs) attached to EC2 instances. You can now assign /28 (16 IP addresses) IPv4 address prefixes, instead of assigning individual secondary IPv4 addresses to network interfaces. This significantly increases number of pods that can be run per node.
Seccomp (Secure Computing) is a feature in the Linux kernel that allows a userspace program to create syscall filters. In the context of containers, these syscall filters are collated into seccomp profiles that can be used to restrict which syscalls and arguments are permitted. Applying seccomp profiles to containers reduces the chance that a Linux kernel vulnerability will be exploited.
Everyone likes the idea of a single root cause when a problem occurs. This post compares that to how we think about successes, to make the point about the fragility of looking for a singular root cause
Controllers are one of the foundational components of Kubernetes whose job is to constantly monitor (through a control loop) the defined API resources in order to bring the cluster to the desired state. Each controller has a designed purpose that manages the entire lifecycle of a particular component. An important concept to remember with any cloud native technology is that availability is not guaranteed. If a controller was designed to take action when a resource was deleted and the controller was unavailable at that point in time, the intended action would not occur and state would no longer be in sync.
I will explain how to build a monitoring system that can retain data for long periods, which can handle up to 200K samples per second. The important point is that all of these processes are realized on one centralized Prometheus and Thanos server.
ClusterMesh is Cilium’s multi-cluster implementation that is built on top of Cilium CNI. It enables users to set up cross-cluster connectivity with standard Kubernetes semantics for transparent service discovery. Each cluster in the mesh participates as a peer. Cross-cluster traffic is handled by individual nodes rather than using a central gateway.
This technical guide shows you how to securely manage and operate multi-tenant software-as-a-service (SaaS) applications on Amazon Elastic Kubernetes Service (Amazon EKS) clusters.
The incredible community around Kubernetes is constantly sharing tools that help improve the experience of being a Kubernetes developer. Here is my list of the 11 essential tools I keep in my arsenal. I break them down by important categories which ones help me run Kubernetes, test Kubernetes, and — last but not least — have fun in my IDE.