The latest News and Information on Containers, Kubernetes, Docker and related technologies.
As an AWS Advanced Technology Partner with AWS Containers Competency, Tigera is thrilled to announce that Calico and Calico Enterprise are both now available as AWS Quick Starts. If you’re unfamiliar with the concept, an AWS Quick Start is a ready-to-use accelerator that fast-tracks deployments of key cloud workloads for AWS customers.
Ketch (https://www.theketch.io) is an open-source application delivery framework for Kubernetes. YAML is a human-readable data-serialization language. It is commonly used for configuration files and in applications where data is being stored or transmitted. Customized YAML files are used by many for the complicated task of deploying to Kubernetes.
Today, Red Hat announced its intent to acquire Stackrox. This is a very exciting development in the world of cloud-native security! First and foremost, congratulations to Stackrox, an early participant in the container security space. This acquisition is a great outcome for Stackrox given their nascent scale and on-premises offering.
Among all the new features and services that AWS announced during the re:Invent 2020, my favorites were definitely the AWS Lambda updates. And there were many! For example, your code execution is no longer rounded up to the nearest 100ms of duration for billing — you are now billed on a per millisecond. On top of that, AWS increased the Lambda’s memory capacity to 10 GB, and correspondingly the CPU capacity up to 6 vCPUs.
Now that we know the advantages of leveraging Ketch over other tools such as Helm to ease the deployment of our applications (BLOG: Helm vs. Ketch when Deploying Applications), a good next step is for us to understand how we can tie Ketch to our CI pipeline and have an automated deployment process. For this example, we will leverage Ketch, GitHub Actions, and a Kubernetes cluster on Google Kubernetes Engine (GKE).
In this tutorial, we will discuss InfluxDB and its Python client. We will deploy InfluxDB inside a Kubernetes cluster and then use the InfluxDB Python client to send data to InfluxDB.
