1. HPA VS KEDA HPA also provides: Elasticity based on custom metrics Scale to Zero Compared with KEDA, these are no longer disadvantages. The real difference is that HPA can only scale using monitoring data, whereas KEDA can scale using many more data sources — queue messages, databases, Redis, and so on, including monitoring data as well.

1. Container-Based Serverless Cannot Support the Next Generation of Applications As the figure above shows, we are going through a change in runtime form. From bare metal to virtual machines, applications are no longer limited by the number of local servers or the stability of the data center, and gain better elasticity and availability.

1. A Constrained Build Environment Cannot Meet Build Requirements Tekton is a CICD engine based on a Kubernetes cluster, and it is more cloud-native than Jenkins. In plain terms, that means it is easier to develop plugins for, easier to scale, easier to observe, and more fun. Because code can only be stored on the company intranet, the build cluster can only be deployed on the office intranet.

1. After Turning Off affinity-assistant In an earlier post, by turning off affinity-assistant and using NFS storage, I saved nearly 30 seconds on average per pipeline execution.[1] The impact of affinity-assistant Before turning it off, the sequence diagram for creating a Pod looked like this: Because affinity-assistant was on, every pipeline was bound to a single node for execution.

The template Istio uses to inject a Sidecar lives in the istio-sidecar-injector ConfigMap. Annotations let you customize the Sidecar’s various parameters, such as CPU usage, proxyImage, and so on. What follows is mainly a summary of the Sidecar injection methods. 1. Add a label to a namespace -> takes effect for the whole namespace Inject the label 1 kubectl label namespace default istio-injection=enabled --overwrite After the application restarts, the Sidecar container will be injected automatically.