kube-prometheus
temporal
kube-prometheus | temporal | |
---|---|---|
41 | 16 | |
6,297 | 9,886 | |
1.5% | 2.8% | |
8.6 | 9.9 | |
4 days ago | 6 days ago | |
Jsonnet | Go | |
Apache License 2.0 | MIT License |
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.
kube-prometheus
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Upgrading Hundreds of Kubernetes Clusters
The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.
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Unfork with ArgoCD
kustomize Kube Prometheus
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Smart-Cash project -Adding monitoring to EKS using Prometheus operator
On the other hand, the Kube-prometheus project provides documentation and scripts to operate end-to-end Kubernetes cluster monitoring using the Prometheus Operator, making easier the process of monitoring the Kubernetes cluster.
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Scaling Temporal: The Basics
For our load testing we’ve deployed Temporal on Kubernetes, and we’re using MySQL for the persistence backend. The MySQL instance has 4 CPU cores and 32GB RAM, and each Temporal service (Frontend, History, Matching, and Worker) has 2 pods, with requests for 1 CPU core and 1GB RAM as a starting point. We’re not setting CPU limits for our pods—see our upcoming Temporal on Kubernetes post for more details on why. For monitoring we’ll use Prometheus and Grafana, installed via the kube-prometheus stack, giving us some useful Kubernetes metrics.
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How do you set up Grafana alert for your cluster? Which mixins library?
The 2 most common approaches I have seen are kube-prometheus-stack and kube-prometheus..
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Issues with "victoria-metrics-k8s-stack", monitoring k8s targets
- I'm missing a lot of the Grafana dashboards that are provisioned during the deployment, not sure why as it has worked before, and wanted to add them after install... I believe it's different ConfigMaps like the one in kube-prometheus but I was wondering if there's a way to force provisioning them all again at once (multiple k8s, node_exporter, vm, etc)?
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what metrics are most important for checking kubernetes cluster health?
Check out the kube Prometheus project -- https://github.com/prometheus-operator/kube-prometheus It's a bit heavy, but the included recording rules and dashboards give you a great start at understanding your cluster.
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Easy Prometheus/Grafana Setup With Dashboards Repo
The actual link to the prometheus/grafana bundle: https://github.com/prometheus-operator/kube-prometheus
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How To Configure Kube-Prometheus
Here’s a list of what’s installed: https://github.com/prometheus-operator/kube-prometheus/tree/main/manifests
- How to install a user managed Prometheus and Grafana instance on OpenShift 4?
temporal
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Rethinking Serverless with Flame
I don't know if I agree with the argument regarding durability vs elastic execution. If I can get both (with a nice API/DX) via something like Temporal (https://github.com/temporalio/temporal), what's the drawback here?
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Who's hiring developer advocates? (December 2023)
Link to GitHub -->
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temporal VS laravel-workflow - a user suggested alternative
2 projects | 23 Aug 2023
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Scaling Temporal: The Basics
However, as we mentioned, each shard needs management. Part of the management includes a cache of Workflow histories for that shard. We can see the History pods’ memory usage is rising quickly. If the pods run out of memory, Kubernetes will terminate and restart them (OOMKilled). This causes Temporal to rebalance the shards onto the remaining History pod(s), only to then rebalance again once the new History pod comes up. Each time you make a scaling change, be sure to check that all Temporal pods are still within their CPU and memory requests—pods frequently being restarted is very bad for performance! To fix this, we can bump the memory limits for the History containers. Currently, it is hard to estimate the amount of memory a History pod is going to use because the limits are not set per host, or even in MB, but rather as a number of cache entries to store. There is work to improve this: github.com/temporalio/temporal/issues/2941. For now, we’ll set the History memory limit to 8GB and keep an eye on them—we can always raise it later if we find the pod needs more.
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Temporal .NET – Deterministic Workflow Authoring in .NET
Correct, the workflow's guarantee to always complete executing independent of hardware failures is dependent on the database not losing data. You host your workflow code with Temporal's Worker library, which talks to an instance of the Temporal Server [1], which is an open-source set of services (hosted by you or by Temporal Cloud), backed by Cassandra, MySQL, or Postgres. [2] So for instance increasing Cassandra's replication factor increases your resilience to disk failure.
[1] https://github.com/temporalio/temporal
[2] https://docs.temporal.io/clusters#persistence
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Mandala: experiment data management as a built-in (Python) language feature
Re:graph frameworks - thanks for the pointers, hadn't heard about them! I'd heard of temporal which I believe provides a similar memoization capability with the purpose of not losing work in workflows that failed partway through?
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temporal VS javactrl-kafka - a user suggested alternative
2 projects | 2 Feb 2023
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Temporal PHP SDK: Scalable and resilent workflow orchestration on PHP
Documentation
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Developers and Distributed Systems and Dinosaurs, Oh MY!!!
Personally I am leveraging the knowledge and momentum of Replay to dive into the Python SDK, build out a couple of applications to deepen my knowledge around Workflows, Activities, and metrics, and continue inhaling knowledge via the monthly meetup, the application development guide, and documentation. By next year I’ll experience the conference, not as one new to Temporal, but as an expert—maybe even as one of the people helping with the architecture review or running a Birds of a Feather; if anything, I know I look forward to seeing YOU at next year’s event!
- Building financial integration with Cadence in doordash
What are some alternatives?
metrics-server - Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
argo - Workflow Engine for Kubernetes
helm-charts - Prometheus community Helm charts
cadence - Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.
prometheus-operator - Prometheus Operator creates/configures/manages Prometheus clusters atop Kubernetes
gocelery - Celery Distributed Task Queue in Go
kube-thanos - Kubernetes specific configuration for deploying Thanos.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
sloth - 🦥 Easy and simple Prometheus SLO (service level objectives) generator
DurableTask - Durable Task Framework allows users to write long running persistent workflows in C# using the async/await capabilities.
descheduler - Descheduler for Kubernetes
Workflow Core - Lightweight workflow engine for .NET Standard