Built something? We create video reels & spotlights for GitHub projects.Promote your project →
pmady
Home / Go / keda-gpu-scaler

pmady/keda-gpu-scaler

KEDA External gRPC Scaler for GPU workloads - native NVML metrics via DaemonSet, no Prometheus required

Go ◇ ai-infrastructure Apache-2.0
★136STARS
⑂36FORKS
!15ISSUES
🏆#23,062GLOBAL RANK
🔥43DAYS TRENDING
🚀
Maintainer Growth Kit for keda-gpu-scaler

Claim this project, add your verified backlink badge to your README, and download milestone cards.

Claim Repo

⚡ Executive Summary & Quick Facts

Authoritative Source

keda-gpu-scaler is keda-gpu-scaler is an open-source project written in Go: KEDA External gRPC Scaler for GPU workloads - native NVML metrics via DaemonSet, no Prometheus required..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), pmady/keda-gpu-scaler has accumulated 136 GitHub stars and 36 forks. It is written in Go, licensed under Apache-2.0, and ranks #23,062 globally. It is actively maintained with the latest commit recorded on Oct 21, 2026.”
Repository pmady/keda-gpu-scaler ↗
Primary Category ai infrastructure
Language & Stack Go
Software License Apache-2.0
Community Traction ★ 136 stars · ⑂ 36 forks · #23,062 globally
Maintenance ● Active (Last commit: Oct 21, 2026) · 15 open issues
Target Audience Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 88/100 · Grade A
✅
Is keda-gpu-scaler actively maintained in 2026?
Verdict: Actively Maintained

Yes, keda-gpu-scaler is actively maintained. Continuous telemetry recorded the last code commit on Oct 21, 2026 (23 days ago). Supported by 136 stars and 36 community forks, this repository holds a calculated health index of 88/100, reflecting regular maintenance (23 days ago) and healthy issue cadence.

Commit Recency
Oct 21, 2026
23 days since last push
Issue Backlog
15 Open Issues
Healthy Issue Cadence
Community Backing
36 Forks
136 Stars Recorded
Software License
Apache-2.0
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for pmady/keda-gpu-scaler
CSV
⭐ VIRAL README KIT & BACKLINKS

Add Live Star History & Verified Badges to README.md

Keep your repository README looking professional and dynamic. As our continuous crawler records new stars, these official SVG badges update in real time with zero maintenance.

Open README on GitHub ↗
Option 1: Interactive Star History Chart Dynamic SVG

Renders your high-resolution star trajectory chart right inside your GitHub README or project docs.

pmady/keda-gpu-scaler Star History Preview
markdown
[![Star History Chart](https://githubrepo.cloud/api/badge/chart/pmady/keda-gpu-scaler.svg?theme=dark)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_chart)
Direct SVG Link ↗
Option 2: Verified Live Badges Suite Shields.io Style

Compact badges for your README header. Real-time stars, velocity, health audit, and rank.

Featured badge Stars badge Velocity badge Health badge Rank badge
markdown (all 5 badges)
[![Featured on GitHubRepo.cloud](https://githubrepo.cloud/badge/pmady/keda-gpu-scaler.svg?metric=featured)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_badge) [![GitHubRepo Stars](https://githubrepo.cloud/badge/pmady/keda-gpu-scaler.svg?metric=stars)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_badge) [![GitHubRepo Velocity](https://githubrepo.cloud/badge/pmady/keda-gpu-scaler.svg?metric=velocity)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_badge) [![Maintenance Health](https://githubrepo.cloud/badge/pmady/keda-gpu-scaler.svg?metric=health)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_badge) [![Global Rank](https://githubrepo.cloud/badge/pmady/keda-gpu-scaler.svg?metric=rank)](https://githubrepo.cloud/repo/pmady/keda-gpu-scaler?utm_source=readme_badge)

Momentum

+4

STARS · LAST 30 DAYS

1

PER DAY

#2,402

MOST-STARRED Go

Window7 days30 days90 days
Stars gained+0+4+90
Per day111
Forks gained+0+0+10

keda-gpu-scaler gained 4 stars in the last 30 days, about 1 a day, and now has 136. It is about 1 year old and has averaged roughly 136 stars a year. It ranks #2,402 among Go repositories and #23,062 across all languages on GitHubRepo.

Trending Record

keda-gpu-scaler has maintained a continuous presence across global trending indexes, peaking at #4345. Below is the 30-day activity profile:

💡 Overview

keda-gpu-scaler is an open-source project written in Go: KEDA External gRPC Scaler for GPU workloads - native NVML metrics via DaemonSet, no Prometheus required.

Engineered for speed, consistency, and developer ease, it solves common hurdles in ai-infrastructure, autoscaling, daemonset. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Go for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ go install github.com/pmady/keda-gpu-scaler@latest

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Go >= 1.21 runtime environment

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

keda-gpu-scaler coordinates its core functionality through a modular Go pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with keda-gpu-scaler.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install keda-gpu-scaler using your package manager: `go install github.com/pmady/keda-gpu-scaler@latest`

2

Initialize your project workspace or configuration file for keda-gpu-scaler.

3

Import keda-gpu-scaler into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `keda-gpu-scaler --help` to verify successful setup.

👍 Strengths

Active community backing with 131 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Go for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Go and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

A
avelino/awesome-go ★ 193.5K Go

A curated list of awesome Go frameworks, libraries and software

Compare ↗
O
ollama/ollama ★ 186.6K Go

Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.

Compare ↗
G
golang/go ★ 139.9K Go

The Go programming language

Compare ↗
K
kubernetes/kubernetes ★ 128.6K Go

Production-Grade Container Scheduling and Management

Compare ↗

👥 Who Should Use This

Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

pmady/keda-gpu-scaler is currently ranked #23,062 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#22,993 Da7-Tech/SureForge Python ★ 137 Compare ↗
#22,993 amos689/paperdelta Python ★ 137 Compare ↗
#22,993 ClickingMaster/ssrecomp C++ ★ 137 Compare ↗
#22,993 mattxslv/Selene C# ★ 137 Compare ↗
#22,993 Moh4696/cinematic-skill Python ★ 137 Compare ↗
#23,062 pmady/keda-gpu-scaler This Project Go ★ 136
#23,062 agateau/yokadi Python ★ 136 Compare ↗
#23,062 rich/acts_as_revisable Ruby ★ 136 Compare ↗
#23,062 gwik/ffmpeg-ruby C ★ 136 Compare ↗
#23,062 michael/ken-rb Ruby ★ 136 Compare ↗
#23,062 steveyen/moxi C ★ 136 Compare ↗
SPONSORED Trending Developer Tools & Services

Frequently Asked Questions

What does keda-gpu-scaler do? +

KEDA External gRPC Scaler for GPU workloads - native NVML metrics via DaemonSet, no Prometheus required

Is keda-gpu-scaler actively maintained in 2026? +

Yes, keda-gpu-scaler is actively maintained. The latest code push was recorded on Oct 21, 2026 (23 days ago). It holds a calculated Maintenance Health Score of 88/100 (A rating) with 136 stars and 15 open issues.

What language is keda-gpu-scaler written in? +

The primary language is Go. Topics include: ai-infrastructure, autoscaling, daemonset, gpu, gpu-autoscaling.

How many stars does keda-gpu-scaler have? +

keda-gpu-scaler has 136 stars and 36 forks on GitHub.

How does keda-gpu-scaler rank among GitHub repositories? +

With 136 stars, pmady/keda-gpu-scaler is ranked #23,062 globally across all repositories tracked on GitHubRepo and #2,402 among Go projects.

What license is keda-gpu-scaler distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

From our network
FOR MAINTAINERS

Built something? Put it in front of millions of developers.

We make a short reel about your project and post it across YouTube, Instagram, Threads, and X. Send a link, we do the rest.

SPONSORED Sponsored Partner