kubebuilder
prometheus
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kubebuilder | prometheus | |
---|---|---|
45 | 381 | |
7,384 | 52,748 | |
1.8% | 1.4% | |
9.2 | 9.9 | |
6 days ago | about 16 hours ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
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.
kubebuilder
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SpinKube: Orchestrating light, fast and efficient WebAssembly (Wasm) workloads in Kubernetes (k8s)
The Spin operator uses the Kubebuilder framework and contains a Spin App Custom Resource Definition (CRD) and controller. It watches Spin App Custom Resources and realizes the desired state in the K8s cluster. Aside from the immediate benefits gained by running Wasm workloads in k8s, additional optimizations such as Horizontal Pod Scaling (HPA) and k8s Event-driven Autoscaling (KEDA) can be achieved in a pinch.
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Building a Kubernetes Operator with the Operator Framework
kubebuilder: brew install kubebuilder
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Annotations in Kubernetes Operator Design
The operator that I've been working on is designed to manage the full lifecycle of a QuestDB database instance, including version and hardware upgrades, config changes, backups, and (eventually) recovery from node failure. I used the Operator SDK and kubebuilder frameworks to provide scaffolding and API support.
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Kubebuilder Tips and Tricks
Recently, I've been spending a lot of time writing a Kubernetes operator using the go operator-sdk, which is built on top of the Kubebuilder framework. This is a list of a few tips and tricks that I've compiled over the past few months working with these frameworks.
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We moved our Cloud operations to a Kubernetes Operator
Since we built our operator using the Kubebuilder framework, most standard monitoring tasks were handled for us out-of-the-box. Our operator automatically exposes a rich set of Prometheus metrics that measure reconciliation performance, the number of k8s API calls, workqueue statistics, and memory-related metrics. We we were able to ingest these metrics into pre-built dashboards by leveraging the grafana/v1-alpha plugin, which scaffolds two Grafana dashboards to monitor Operator resource usage and performance. All we had to do was add these to our existing Grafana manifests and we were good to go!
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Has anyone ever tried to learn how k8s works?
I wrote a CSI driver and some operators. I admire K8s, because you can find solution to almost any problem in the source code - API versioning, load balancing, request throttling, optimistic concurrency, security, and much much more. I recommend https://book.kubebuilder.io/ It is similar to Operator SDK, but without Openshift-specific stuff. It gradually introduces you to many k8s concepts, and follows design patterns that k8s uses internally.
- What Is A Kubernetes Operator?
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If you write a Kubernetes Operator: Events vs Conditions?
Do you mean this: https://book.kubebuilder.io/ ?
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Kubernetes Operators
https://book.kubebuilder.io/ all you need to know
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Writing a Kubernetes Operator
A better way to write an operator these days is to use kubebuilder [1].
My complaint is that I have seen orgs write operators for random stuff, often reinventing the wheel. Lot of operators in orgs are result of resume driven development. Having said that it often comes handy for complex orchestration.
[1]https://github.com/kubernetes-sigs/kubebuilder
prometheus
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Fivefold Slower Compared to Go? Optimizing Rust's Protobuf Decoding Performance
WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and
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Tools for frontend monitoring with Prometheus
Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.
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The power of the CLI with Golang and Cobra CLI
Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.
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On Implementation of Distributed Protocols
Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.
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Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.
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Monitoring, Observability, and Telemetry Explained
Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.
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Observability at KubeCon + CloudNativeCon Europe 2024 in Paris
Prometheus
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Top 5 Docker Container Monitoring Tools in 2024
Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.
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Install and Setup Grafana & Prometheus on Ubuntu 20.04 | 22.04/EC2
wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
What are some alternatives?
helm-operator - Successor: https://github.com/fluxcd/helm-controller — The Flux Helm Operator, once upon a time a solution for declarative Helming.
metrics-server - Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
client-go - Go client for Kubernetes.
skywalking - APM, Application Performance Monitoring System
operator-sdk - SDK for building Kubernetes applications. Provides high level APIs, useful abstractions, and project scaffolding.
Jolokia - JMX on Capsaicin
crossplane - The Cloud Native Control Plane
Telegraf - The plugin-driven server agent for collecting & reporting metrics.
kubegres - Kubegres is a Kubernetes operator allowing to deploy one or many clusters of PostgreSql instances and manage databases replication, failover and backup.
JavaMelody - JavaMelody : monitoring of JavaEE applications
python - Official Python client library for kubernetes
Glowroot - Easy to use, very low overhead, Java APM