A startup from the United States.
Powerful Query Language
Prometheus uses PromQL, a flexible and powerful query language that allows for complex and detailed queries.
Dimensional Data Model
Prometheus employs a multidimensional data model with time series data identified by metric name and key-value pairs, offering great flexibility in data organization.
Auto-Discovery
It supports service discovery mechanisms to automatically locate and scrape metrics from jobs, simplifying the monitoring process.
Alerting
Prometheus includes built-in alerting capabilities that allow you to trigger alerts based on PromQL queries, which can be integrated with different alert management systems.
Scalability
Its architecture, which uses independent single servers, scales well, allowing you to handle a large number of time series efficiently.
Open Source
Prometheus is open-source and supported by a large community, offering transparency, regular updates, and numerous integrations.
Easy Integration
Thanks to its compatibility with various data exporting standards and a myriad of existing exporters, integrating Prometheus into existing systems is streamlined.
Promote Prometheus. You can add any of these badges on your website.
Prometheus is highly regarded for its robustness, versatility, and efficiency in monitoring and alerting tasks, especially within cloud-native environments.
We have collected here some useful links to help you find out if Prometheus is good.
Check the traffic stats of Prometheus on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Prometheus on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Prometheus's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Prometheus on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Prometheus on Reddit. This can help you find out how popualr the product is and what people think about it.
Prometheus scrapes metrics from the stack. Node exporter covers the host, cAdvisor covers containers, and individual services expose their own endpoints where supported. The main value isn't dashboards (though those exist) - it's having a queryable record of system state over time, and a place to hook alerts when something drifts. - Source: dev.to / 25 days ago
Prometheus is the industry-standard time-series database for infrastructure metrics. Paired with Grafana for visualization and Alertmanager for routing, it forms the backbone of monitoring at companies from startups to Netflix-scale deployments. This isn't a single tool โ it's an ecosystem. - Source: dev.to / about 1 month ago
To monitor and analyze rate limiting metrics, we're using a combination of Redis and Prometheus. We're storing rate limiting metrics in Redis and then using Prometheus to scrape the metrics and display them in a dashboard. Here's an example of how we're storing rate limiting metrics in Redis:. - Source: dev.to / about 1 month ago
In this post, we compare two forecasting models, Chronos (ChronosโBolt) and Toto, on telemetry from Prometheus and OpenSearch. We judge them with two easy metrics: MASE for point accuracy and CRPS for the quality of uncertainty. - Source: dev.to / about 2 months ago
For monitoring infrastructure, Prometheus and Grafana are widely used for pipeline metrics collection and alerting. For orchestration that includes built-in run observability, Apache Airflow tracks run history, task durations, and failure states in a web UI. Python with SQLAlchemy is the standard stack for custom pipeline implementation with relational state management. - Source: dev.to / 3 months ago
The OpenTelemetry ecosystem has three main components: instrumentation, the Collector, and exporters. Instrumentation is how you integrate OpenTelemetry into your application, using language-specific SDKs to create spans, record metrics, and propagate context. The Collector is an optional middleware component that receives, processes, and exports telemetry data to one or more backends. Exporters are the plugins... - Source: dev.to / 3 months ago
The fix is switching from naive serving to optimized serving, which means deploying the same model differently. High-performance teams running Llama-3-70B in production have converged on a specific stack: vLLM or SGLang as the inference engine, Prometheus for observability, and Runpod as the infrastructure layer that lets them deploy and iterate without managing a Kubernetes cluster. This guide works through that... - Source: dev.to / 4 months ago
There are a lot of free and paid tools to monitor these variables. I almost always do this type of test in a VM (easier to clean up the mess when it all breaks) and I like to use Prometheus but honestly Perfmon in Windows or Top in Linux gives you all you really need. - Source: dev.to / 4 months ago
Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus It is designed to be very cost effective and easy to operate It does not index the contents of the logs, but rather a set of labels for each log stream. - Source: dev.to / 4 months ago
Prometheus / Grafana: Prometheus monitors server resources and middleware metrics, and Grafana is often used as the UI to visualize them. - Source: dev.to / 6 months ago
Monitoring Integration: Supports notifications via healthchecks.io, Prometheus, Slack/Discord. - Source: dev.to / 6 months ago
This gives you both a Prometheus metric (unicorn.create.duration) and an X-Ray span from a single annotation. - Source: dev.to / 6 months ago
Keep a close eye on your serverโs CPU, memory, disk I/O, and network usage. Tools like Prometheus with Grafana, or simpler options like htop, Netdata, or cloud provider monitoring, can help identify bottlenecks or misbehaving applications before they impact other sites. - Source: dev.to / 6 months ago
Prometheus is a popular open-source monitoring system that scrapes metrics from your services, stores them as time-series data, and makes them queryable through PromQL. We'll use the official prometheus/client_golang library to instrument our services and exposes metrics for scraping. - Source: dev.to / 9 months ago
To answer these questions, I built a telemetry system using Prometheusโan open-source monitoring system originally built at SoundCloud. Prometheus collects metrics (numerical measurements) over time and lets you query them later. A background script runs every 15 seconds, collecting metrics about my tmux environment and LLM sessions. - Source: dev.to / 9 months ago
Istio's Comprehensive Stack - Istio integrates with a complete Observability ecosystem: Kiali for visualizing service topology, Prometheus for metrics, Grafana for dashboards, and multiple tracing solutions. This gives you deep visibility into API traffic patterns, though it requires significant configuration effort. - Source: dev.to / 11 months ago
The standard observability stack includes Prometheus for metrics collection, Grafana for visualization, and AlertManager for notifications. For logging, consider Fluent Bit or Fluentd with Elasticsearch or cloud logging services. Jaeger or Zipkin provide distributed tracing for microservices debugging. - Source: dev.to / 11 months ago
Pro tip: Use a monitoring tool like Prometheus to track refresh times and API response times. Check out Prometheus for setup details. - Source: dev.to / 11 months ago
Tools like Prometheus for metric collection and Grafana for visualization and alerting form the backbone of modern observability stacks, providing the raw data that AI/ML models can then process for predictive insights. - Source: dev.to / about 1 year ago
Prometheus - Metrics collection and alerting. - Source: dev.to / about 1 year ago
Now, letโs implement it using Prometheus syntax:. - Source: dev.to / about 1 year ago
Prometheus has established itself as a cornerstone in the realm of open-source monitoring tools, noted for its robust performance and extensive capabilities. It is predominantly recognized for providing a comprehensive solution for systems and application monitoring, capable of collecting, storing, and analyzing metric data via its native PromQL query language. This monitoring framework has been particularly favored within cloud-native ecosystems and often finds itself coupled with Grafana for enhanced data visualization, enabling users to construct customizable dashboards to meet their monitoring needs.
One of Prometheus's strengths is its open-source nature, allowing flexibility and extensibility, which accommodates a diverse range of deployments including Kubernetes environments, server performance enhancement, IoT device metrics, and even Raspberry Pi clusters. Using a time-series database model, Prometheus leverages a pull-based data collection approach over HTTP, simplifying the integration into existing infrastructure and supporting scalable architecture.
The tool is reputed for its ability to generate alerts and evaluate rule expressions, making it an ideal choice for IT infrastructure monitoring. This allure is bolstered by its extensive list of exporters, which enable the scraping of a myriad of metrics from varied applications and systems. As such, organizations aiming for a DIY monitoring setup often turn to Prometheus and Grafana as a combined monitoring and visualization solution. This flexibility and absence of licensing costs position Prometheus as an attractive option for organizations prepared to manage their own infrastructure and configuration.
Prometheus's comparability to its contemporaries like Datadog, Zabbix, and Splunk reveals certain trade-offsโprimary among these is the need for user-managed infrastructure versus more intuitive, managed services offered by some competitors. This aspect is reflected in articles and discussions highlighting cost-efficiency challenges when scaled up, as seen with some managed versions in the cloud, such as the Google Managed Prometheus, which has been outpaced by newer entrants like Levitate in terms of cost efficiency.
Additionally, Prometheus's integrations with other enterprise-grade solutions, such as OpenTelemetry or Kubernetes State Metrics, demonstrate its adaptability and relevance in modern IT ecosystems. However, it is noted that as a relatively newer solution compared to traditional vendors like Nagios or Zabbix, it may have a less expansive support community.
In conclusion, Prometheus remains a powerful choice for organizations seeking a flexible, scalable, and cost-effective open-source monitoring tool capable of being tailored to a wide range of use cases. Its continuous development and integration with front-line technologies ensure its relevance in an ever-evolving tech landscape. However, effective utilization often demands a willingness to engage with configuration complexities and infrastructure management to fully exploit its potential.
Do you know an article comparing Prometheus to other products?
Suggest a link to a post with product alternatives.
Is Prometheus good? This is an informative page that will help you find out. Moreover, you can review and discuss Prometheus here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
