eventing-autoscaler-keda
KEDA support for Knative Event Sources Autoscaling (by knative-extensions)
poc-files
By CheViana
eventing-autoscaler-keda | poc-files | |
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1 | 1 | |
39 | 0 | |
- | - | |
8.8 | 7.1 | |
5 days ago | 5 months ago | |
Go | Python | |
Apache License 2.0 | - |
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
eventing-autoscaler-keda
Posts with mentions or reviews of eventing-autoscaler-keda.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-04.
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Knative switchboard series, part 1. Setup Knative Eventing with Kafka from scratch, scale based on events volume, and monitor
Install scaling controller for Kafka sources - Keda autoscaler. HPA parameters are controlled by annotations on the Kafka source yaml definition:
poc-files
Posts with mentions or reviews of poc-files.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-04.
-
Knative switchboard series, part 1. Setup Knative Eventing with Kafka from scratch, scale based on events volume, and monitor
Follow Strimzi quickstart to install kafka in knative-eventing namespace, but use different Kafka cluster definition, see below. Knative workloads are expecting to be run in knative-eventing namespace, otherwise issues arise. And it's easier to keep Knative and Kafka in one namespace. Use kafka-cluster.yaml as kafka cluster resource instead of the one used in Strimzi quickstart (kafka-single-persistent.yaml). If you're not limited on disk, best to set storage: size: 50Gi or 100Gb in kafka-cluster yaml, and at least 25Gb for zookeeper storage. For trial quota, you're limited to 20Gb and 10Gb for zookeeper (if we're doing 2 Kafka clusters, if one - can be more).