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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Pixi vs Prometheus

Pixi vs Prometheus

OverviewDecisionsComparisonAlternatives

Overview

Prometheus
Prometheus
Stacks4.8K
Followers3.8K
Votes239
GitHub Stars61.1K
Forks9.9K
Pixi
Pixi
Stacks100
Followers86
Votes8

Pixi vs Prometheus: What are the differences?

Introduction

Pixi and Prometheus are both powerful tools used in web development. However, there are several key differences between them that set them apart. In this Markdown code, I will provide a formatted comparison of these differences.

  1. Rendering Capabilities: Pixi is primarily a rendering engine that focuses on fast and efficient rendering of 2D graphics using WebGL. It provides high-performance rendering for complex animations and graphics, making it suitable for gaming and interactive applications. On the other hand, Prometheus is a monitoring and alerting toolkit that helps in collecting and analyzing metrics from various sources, including applications, services, and hardware. It provides powerful visualization and querying tools to help monitor the health and performance of systems.

  2. Primary Purpose: Pixi is mainly used for creating visually stunning graphics and animations, making it ideal for game development and interactive experiences on the web. It provides a comprehensive set of tools and features specifically designed for this purpose. In contrast, Prometheus is focused on monitoring and observability. It helps in collecting and analyzing metrics to gain insights into the performance and behavior of complex systems. It is commonly used in cloud-native environments for monitoring microservices architectures.

  3. Flexibility: Pixi offers a wide range of features and customizability options, allowing developers to create highly tailored visual experiences. It provides comprehensive control over the rendering pipeline, enabling developers to optimize graphics rendering to their specific needs. On the other hand, Prometheus is designed to be highly flexible and modular. It supports multiple integrations and can collect metrics from various sources, including applications, databases, and cloud services. It also supports advanced querying and alerting mechanisms.

  4. Community and Ecosystem: Pixi has a large community of developers and a well-established ecosystem with numerous libraries and resources available. It is widely used in the gaming and interactive media industry and has a strong presence in the web development community. Prometheus, on the other hand, has a growing and vibrant community. It has gained popularity in recent years due to its powerful features and ease of use. It has an extensive ecosystem of exporters, integrations, and visualizers, making it easy to integrate with other tools and platforms.

  5. Integration with Other Tools: Pixi can be easily integrated with other web development tools and frameworks, such as React and Angular, to create interactive web applications. It also supports integration with different game engines and frameworks, making it compatible with various development workflows. Prometheus, on the other hand, provides native integrations with popular tools and platforms commonly used in the cloud-native ecosystem, such as Kubernetes and Docker. It can also be extended using exporters and custom integrations to collect metrics from any system or application.

  6. Scalability and Performance: Pixi is highly optimized for performance and can handle complex rendering tasks efficiently. It leverages WebGL and other hardware-accelerated technologies to deliver smooth and high-performance graphics. Prometheus is designed to be highly scalable, allowing it to handle large-scale monitoring and metric collection. It uses a pull-based model for metric collection, which ensures minimal impact on the monitored systems' performance.

In Summary, Pixi is a powerful rendering engine primarily used for creating visually stunning graphics and animations, ideal for gaming and interactive experiences. On the other hand, Prometheus is a monitoring and alerting toolkit designed for collecting and analyzing metrics to monitor the health and performance of systems, commonly used in cloud-native environments.

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Advice on Prometheus, Pixi

Raja Subramaniam
Raja Subramaniam

Aug 27, 2019

Needs adviceonPrometheusPrometheusKubernetesKubernetesSysdigSysdig

We have Prometheus as a monitoring engine as a part of our stack which contains Kubernetes cluster, container images and other open source tools. Also, I am aware that Sysdig can be integrated with Prometheus but I really wanted to know whether Sysdig or sysdig+prometheus will make better monitoring solution.

779k views779k
Comments
Susmita
Susmita

Senior SRE at African Bank

Jul 28, 2020

Needs adviceonGrafanaGrafana

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

  • Must be able to get custom data from AS400,
  • Able to display automation test results,
  • System monitoring / Nginx API,
  • Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

869k views869k
Comments
Mat
Mat

Head of Cloud at Mats Cloud

Oct 30, 2019

Needs advice

We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.

794k views794k
Comments

Detailed Comparison

Prometheus
Prometheus
Pixi
Pixi

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Super fast HTML 5 2D rendering engine that uses webGL with canvas fallback

Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Multi-platform Support;Interactive, visually compelling content on desktop, mobile and beyond, all reached with a single codebase to deliver transferable experiences;Tinting & Blending Modes;Sprite Sheet Support;Asset Loader;Easy API;WebGL Filters
Statistics
GitHub Stars
61.1K
GitHub Stars
-
GitHub Forks
9.9K
GitHub Forks
-
Stacks
4.8K
Stacks
100
Followers
3.8K
Followers
86
Votes
239
Votes
8
Pros & Cons
Pros
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 23
    Active and responsive community
Cons
  • 12
    Just for metrics
  • 6
    Needs monitoring to access metrics endpoints
  • 6
    Bad UI
  • 4
    Not easy to configure and use
  • 3
    Supports only active agents
Pros
  • 8
    Fast Performance
Integrations
Grafana
Grafana
HTML5
HTML5
React
React
WebGL
WebGL

What are some alternatives to Prometheus, Pixi?

Grafana

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Kibana

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Nagios

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger

Jaeger, a Distributed Tracing System

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