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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.

Advice on Pixi and Prometheus
Susmita Meher
Senior SRE at African Bank · | 4 upvotes · 786.6K views
Needs advice
on
GrafanaGrafanaGraphiteGraphite
and
PrometheusPrometheus

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.

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Replies (1)
Sakti Behera
Technical Specialist, Software Engineering at AT&T · | 3 upvotes · 571.9K views
Recommends
on
GrafanaGrafanaPrometheusPrometheus

You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.

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Sunil Chaudhari
Needs advice
on
MetricbeatMetricbeat
and
PrometheusPrometheus

Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.

Is it OK to use Metricbeat for Linux server or can we use Prometheus?

What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?

Regards, Sunil.

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Replies (2)
Matthew Rothstein
Recommends
on
PrometheusPrometheus

If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.

Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.

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Recommends
on
InstanaInstana

Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose

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Mat Jovanovic
Head of Cloud at Mats Cloud · | 3 upvotes · 715.8K views
Needs advice
on
DatadogDatadogGrafanaGrafana
and
PrometheusPrometheus

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.

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Replies (2)
Lucas Rincon
Recommends
on
InstanaInstana

this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/

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Recommends
on
DatadogDatadog

I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.

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Pros of Pixi
Pros of Prometheus
  • 8
    Fast Performance
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 23
    Active and responsive community
  • 22
    Extensive integrations
  • 19
    Easy to setup
  • 12
    Beautiful Model and Query language
  • 7
    Easy to extend
  • 6
    Nice
  • 3
    Written in Go
  • 2
    Good for experimentation
  • 1
    Easy for monitoring

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Cons of Pixi
Cons of Prometheus
    Be the first to leave a con
    • 12
      Just for metrics
    • 6
      Bad UI
    • 6
      Needs monitoring to access metrics endpoints
    • 4
      Not easy to configure and use
    • 3
      Supports only active agents
    • 2
      Written in Go
    • 2
      TLS is quite difficult to understand
    • 2
      Requires multiple applications and tools
    • 1
      Single point of failure

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is Pixi?

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

    What is Prometheus?

    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.

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    What are some alternatives to Pixi and Prometheus?
    three.js
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    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.
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