The source code and dependencies are containerized using the Docker file. All the source code is provided for the users to try and modify based on their needs (such as changing the Python-based control plane events application, type of events, and so on). We achieve this by creating a Kubernetes deployment, which the underlying pod inside that deployment tracks activities from the Amazon EKS control plane and persists the events inside CloudWatch. As explained in the previous section, this post provides various examples to show how to manage control plane events with Amazon EKS. Once the Amazon EKS cluster is up and running, it’s time to manage the control plane events. When the cluster is ready, proceed to the next steps. Let’s start by setting a few environment variables:Įksctl create cluster -name $EKS_CLUSTER_NAME -region $AWS_REGION -managedĬreating a cluster can take up to 10 minutes. Basic Kubernetes knowledge (Pods, events, namespaces, and deployments).You need the following to complete the walkthrough: We also cover an example use case for examining events stored in CloudWatch. In this post, we provide a solution to capture the events beyond 60 minutes, using Amazon CloudWatch as the example destination. After 60 minutes, etcd purges the events during the last hour. However, EKS does not allow configuration of this setting, as events filling up the etcd database may cause stability and performance issues. Some customers have shown interest in increasing this configuration to keep a longer history for debugging purposes. Solution overviewĪs mentioned, the Amazon EKS event TTL limit is set to the upstream default 60 minutes. We also cover how to filter Kubernetes events (such as only pod events, node events, and so on) to be exported to Amazon CloudWatch because not every type of Kubernetes resource may be required for longer duration. Readers can take this example and modify it based on their requirements. There are certain use cases where it may be useful to have a history of Kubernetes events beyond the default 60-minute window. In the world of container orchestration and especially with Kubernetes, events are specific objects that show useful information about what is happening inside a pod, namespace, or container. This default setting is a good balance of storing enough history for immediate troubleshooting without filling up the etcd database and risk causing API server degraded performance.Įvents in any distributed management system bring lot of useful information. Amazon EKS keeps the Kubernetes upstream default event time to live (TTL) to 60 minutes, which can’t be changed. As a declarative and reconciling system, Kubernetes publishes various events to keep users informed of activities in the cluster, such as spinning up and tearing down pods, deployments, namespaces, and more. Amazon EKS manages the Kubernetes control plane so customers don’t need to worry about scaling and maintaining Kubernetes components, such as etcd and application programming interface (API) servers. C ONG UARD detected totally 15 previously unknown vulnerabilities, all of which have been confirmed by developers and 12 of them are patched with our assistance.Amazon Elastic Kubernetes Service ( Amazon EKS) helps customers move their container-based workloads to the AWS Cloud. We have evaluated C ONG UARD on three mainstream SDN controllers (Floodlight, ONOS, and OpenDaylight) with 34 applications. We develop a novel dynamic framework, C ONG UARD, that can effectively detect and exploit harmful race conditions. In this attack, even a weak adversary without controlling/compromising any SDN controller/switch/app/protocol but only having malware-infected regular hosts can generate external network events to crash the SDN controllers, disrupt core services, or steal privacy information. For the first time in the literature, we introduce a novel attack against SDN networks that can cause serious security and reliability risks by exploiting harmful race conditions in the SDN controllers, similar in spirit to classic TOCTTOU (Time of Check to Time of Use) attacks against file systems. Because SDN controllers are serving as the brain of the entire network, their security and reliability are of extreme importance. Software-Defined Networking (SDN) has significantly enriched network functionalities by decoupling programmable network controllers from the network hardware.
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