Search Results for "metric"
Sort By:
Showing 271 open source projects for "metric"
View related business solutions-
Earn up to 16% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
1
Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. ... -
2
Prom-Client
Prometheus client for node.js
Prom-Client is a Prometheus client for Node.js that allows developers to instrument their applications and expose metrics, facilitating the monitoring of application performance and resource usage. -
3
TorchMetrics
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic synchronization between multiple devices. Metric arithmetic. ... -
4
MetricFlow
MetricFlow allows you to define, build, and maintain metrics in code
...It works alongside a data stack—typically built with dbt—and allows you to express metrics as YAML‐based definitions tied to semantic models and dimension tables, rather than embedding logic ad-hoc across many dashboards or scripts. When a user or tool requests a metric (e.g., “monthly revenue by region”), MetricFlow generates optimized, warehouse-specific SQL to compute that metric, handling joins, filters, time grains, offsets, and other complexities under the hood. Because metric definitions live centrally, you avoid duplication across teams and tools, reduce risk of inconsistent numbers, and make it easier to audit and evolve the logic over time. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
Amper
Build tool for the Kotlin and Java languages
Amper is an open-source data collection and metric reporting agent developed by JetBrains as part of their internal analytics and telemetry infrastructure for IntelliJ-based products. Its purpose is to gather usage statistics, performance metrics, error reports, and other diagnostic signals from IDE installations in a privacy-conscious way to help product teams understand real-world usage patterns and improve quality. -
6
Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. -
7
Metrics
Capturing JVM and application-level metrics
...The central library for Metrics is metrics-core, which provides some basic functionality. The starting point for Metrics is the MetricRegistry class, which is a collection of all the metrics for your application (or a subset of your application). Each metric is associated with a MetricRegistry, and has a unique name within that registry. A gauge is the simplest metric type. It just returns a value. If, for example, your application has a value which is maintained by a third-party library, you can easily expose it by registering a Gauge instance which returns that value. -
8
Evaluate
A library for easily evaluating machine learning models and datasets
Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized. -
9
wego
Weather app for the terminal
...You can create an account and get a free API key by signing up. You can set the $WEGORC environment variable to override the default config file location. Displayed info (metric or imperial units), temperature range (felt and measured), windspeed and direction, viewing distance, precipitation amount and probability. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
flagger
Progressive delivery Kubernetes operator (Canary, A/B Testing)
Flagger is a progressive delivery tool that automates the release process for applications running on Kubernetes. It reduces the risk of introducing a new software version in production by gradually shifting traffic to the new version while measuring metrics and running conformance tests. Flagger implements several deployment strategies (Canary releases, A/B testing, Blue/Green mirroring) using a service mesh (App Mesh, Istio, Linkerd, Kuma, Open Service Mesh) or an ingress controller... -
11
PRAXIST
Autonomous research system for measurable computer-executable research
...Parallel research peers explore competing hypotheses and implementations while evaluators convert outcomes into structured evidence. That evidence is carried across generations so later work can build on promising strategies and avoid repeating weak ones. The system supports multi-metric evaluation, quality-diversity methods, resource-aware scheduling, and durable evidence tracking. Runs can be monitored, stopped, resumed, and replayed, with the task project remaining the source of truth for objectives, metrics, baselines, and domain constraints. -
12
grafana-dashboards-kubernetes
A set of modern Grafana dashboards for Kubernetes
...The project aims to provide clear, practical visualizations that help DevOps teams quickly understand cluster health, workload behavior, and infrastructure performance. Rather than attempting to expose every possible metric, the dashboards are designed to be operationally useful and easy to navigate during day-to-day troubleshooting. They leverage newer Grafana panel capabilities and are commonly used alongside kube-prometheus-stack deployments. The dashboards allow users to drill down from high-level cluster views to detailed pod-level insights, supporting rapid root-cause analysis. ... -
13
ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
...The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. The representation is metric, meaning it supports camera movements with an absolute scale rather than only relative depth cues, which is useful for consistent viewpoint changes and downstream spatial tasks. The project is structured for reproducibility, with code and assets aimed at demonstrating view synthesis quality, sharp details, and fine structures when rendering high-resolution images. -
14
Gocache
Go cache library that brings you multiple ways to manage caches
...A chain cache: use multiple cache with a priority order (memory then fallback to a redis shared cache for instance) A loadable cache: allow you to call a callback function to put your data back in cache. A metric cache to let you store metrics about your caches usage (hits, miss, set success, set error, ...) A marshaler to automatically marshal/unmarshal your cache values as a struct. Define default values in stores and override them when setting data. Cache invalidation by expiration time and/or using tags. Use of Generics. To begin working with the latest version of gocache, you can import the library in your project. -
15
-
16
Node exporter
Exporter for machine metrics
Power your metrics and alerting with a leading open-source monitoring solution. Prometheus implements a highly dimensional data model. Time series are identified by a metric name and a set of key-value pairs. PromQL allows slicing and dicing of collected time series data in order to generate ad-hoc graphs, tables, and alerts. Prometheus has multiple modes for visualizing data: a built-in expression browser, Grafana integration, and a console template language. Prometheus stores time series in memory and on local disk in an efficient custom format. ... -
17
NVIDIA GPU Exporter
Nvidia GPU exporter for prometheus using nvidia-smi binary
Nvidia GPU exporter for prometheus, using nvidia-smi binary to gather metrics. There are many Nvidia GPU exporters out there however they have problems such as not being maintained, not providing pre-built binaries, having a dependency to Linux and/or Docker, targeting enterprise setups (DCGM) and so on. -
18
MLE-Agent
Intelligent companion for seamless AI engineering and research
MLE-Agent is designed as a pairing LLM agent for machine learning engineers and researchers. A library designed for managing machine learning experiments, tracking metrics, and model deployment. -
19
dive
A tool for exploring each layer in a docker image
...Files that have changed, been modified, added, or removed are indicated in the file tree. This can be adjusted to show changes for a specific layer, or aggregated changes up to this layer. The lower left pane shows basic layer info and an experimental metric that will guess how much wasted space your image contains. This might be from duplicating files across layers, moving files across layers, or not fully removing files. Both a percentage "score" and total wasted file space is provided. You can build a Docker image and do an immediate analysis with one command: dive build -t some-tag . -
20
Sysdig Inspect
A powerful opensource interface for container troubleshooting
Sysdig Inspect is a powerful opensource interface for container troubleshooting and security investigation. Inspect's user interface is designed to intuitively navigate the data-dense sysdig captures that contain granular system, network, and application activity of a Linux system. Sysdig Inspect helps you understand trends, correlate metrics and find the needle in the haystack. It comes packed with features designed to support both performance and security investigations, with deep... -
21
EvoTrees.jl
Boosted trees in Julia
A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood. -
22
Argo Rollouts
Progressive Delivery for Kubernetes
Argo Rollouts is a Kubernetes controller and set of CRDs that provide advanced deployment capabilities such as blue-green, canary, canary analysis, experimentation, and progressive delivery features to Kubernetes. Argo Rollouts (optionally) integrates with ingress controllers and service meshes, leveraging their traffic shaping abilities to gradually shift traffic to the new version during an update. Additionally, Rollouts can query and interpret metrics from various providers to verify key... -
23
Thanos
Highly available Prometheus setup with long term storage capabilities
...Downsample historical data for massive query speedup when querying large time ranges or configure complex retention policies. Thanos leverages the Prometheus 2.0 storage format to cost-efficiently store historical metric data in any object storage while retaining fast query latencies. Additionally, it provides a global query view across all Prometheus installations and can merge data from Prometheus HA pairs on the fly. -
24
Popeye
A Kubernetes cluster resource sanitizer
...By scanning your cluster, it detects misconfigurations and helps you to ensure that best practices are in place, thus preventing future headaches. It aims at reducing the cognitive overload one faces when operating a Kubernetes cluster in the wild. Furthermore, if your cluster employs a metric-server, it reports potential resources over/under allocations and attempts to warn you should your cluster run out of capacity. Popeye is a readonly tool, it does not alter any of your Kubernetes resources in any way! Popeye is not another static analysis tool. It runs and inspect Kubernetes resources on live clusters and sanitize resources as they are in the wild! -
25
JMX Exporter
A process for exposing JMX Beans via HTTP for Prometheus consumption
JMX to Prometheus exporter: a collector that can configurable scrape and expose mBeans of a JMX target. This exporter is intended to be run as a Java Agent, exposing a HTTP server and serving metrics of the local JVM. It can be also run as a standalone HTTP server and scrape remote JMX targets, but this has various disadvantages, such as being harder to configure and being unable to expose process metrics (e.g., memory and CPU usage). Running the exporter as a Java agent is strongly...
