Grafana vs Prometheus – What’s the Difference ? (Pros and Cons)
Grafana vs Prometheus – What’s the Difference ? (Pros and Cons). Monitoring tools are in such demand. Ever growing cyber threads make them indispensable. Today we are talking about Grafana vs Prometheus. Both tools used for monitoring and alerting and often used together. On one hand Prometheus collects and stores metrics, while Grafana provides a graphical interface for visualizing and analysing metrics. With Prometheus, you get a variety of visualization options and it allows users to create custom dashboards that they share with others. In contrast, Grafana includes a query language, PromQL, that is used to retrieve and analyze metrics.
In this blog, we explain and then compare them both in detail to help you understand which monitoring tool is best for your application needs.
Shall we start with article blog Grafana vs Prometheus – What’s the Difference ?
What is Grafana?
All in all, data is queried, visualized and explored wherever it is stored. Simply put, Grafana tools transforms time series database (TSDB) data into beautiful charts and visualizations. Additionally, it sets alerts so you quickly and easily are notified of abnormal behaviour and threats.
Grafana Features
Alerting
Includes an alert system that customizes alerts when certain conditions are met. Also set alerts to occur when certain thresholds are reached or when certain patterns are detected in the data.
Customizable Dashboards
Creates customizable dashboards with a variety of visualization options including graphs, tables, heat maps, and more. On the other hand, also customize the toolbar’s layout, add panels, and enable interactive elements such as filters and drop down menus.
Plugins
With it’s large ecosystem of plugins that extends its functionality and integrates with other tools and services.
Teams and Permissions
If your organization multiple teams, you usually want to be able to force dashboards to be split. Hence, new feature of Grafana multi user mode allows users to switch between organizations, and share dashboards.
Authentication
Basically, Grafana supports LDAP and OA as well as other authentication styles and maps users to organizations and teams. So, if your organization uses its own authentication system, Grafana allows you to map teams from your internal system to teams in Grafana. This will give your team members access to automatically assigned Grafana. dashboard.
Monitors your Monitoring
If you’re serious enough about monitoring, Grafana has its own Prometheus HTTP endpoint that Prometheus can scrape. In turn, it makes getting stats and dashboards super easy. Once the enterprise version is running, access Google Analytics style data to see how much CPU Grafana is consuming or how long notifications are taking.
Provisioning
Well, creating a single dashboard is easy with a click, drag and drop. But advanced users who need multiple dashboards want to use a script to automate the setup. Basically, Grafana also has the option to write anything in Grafana. For example, when you launch a new Kubernetes cluster, you also start Grafana automatically with a script that sets up and blocks the correct server, IP address, and data source. Additionally, it is also a way to control many dashboards.
How Grafana works?
Note the performance of Grafana below:
1.Connects to data source – Supports a wide range of data sources including Prometheus, InfluxDB, Elasticsearch and more. Users can establish connections to one or more data sources.
2. Queries data – Once connected, users utilize the Grafana query editor to pull specific data from a data source. Query Editor supports a wide range of query languages such as Prometheus PromQL, InfluxQL and Elasticsearch Query DSL.
3. Creates visualizations – Users create different types of visualizations such as graphs, tables, and gauges to display data retrieved from data sources.
4. Arranges visualizations on a dashboard – Place visualizations on custom dashboards to create comprehensive views of your data.
5. Shares and collaborates – Dashboards are shared with others and jointly created, edited, and viewed.
6. Alert notification – Also sets alerts under specific conditions so that you are notified when something important happens.
Grafana Pros
- Sends alerts to collaboration channels when a threshold is breeched.
- Very good at visualizing metrics coming from known data sources.
- Graphs and dashboards are portable (graph as code).
- Generally easily integrate to Prometheus and Graphite data sources.
Grafana Cons
- Doesn’t support log analytics and otherwise would break the business of all other visualization tools.
- There are some settings that are not configurable in the user interface (web console).
- To get the most out of Grafana, you need to be proficient in programming languages such as JSON and SQL.
- Due to Grafana’s extensive property customization options, this is difficult and time consuming at first.
Up next with article blog Grafana vs Prometheus – What’s the Difference ? we would like to introduce Prometheus.
What is Prometheus?
Second monitoring tool is Prometheus. One of the best in this field. It has a multi dimensional data model, a powerful query language, and a flexible notification system, making it suitable for monitoring dynamic distributed systems. Prometheus is widely used in industry for monitoring containerized microservices and other distributed systems. In addition, it has a large and active community of users and developers.
Prometheus Features
Powerful Query Language
Enables a powerful query language, PromQL, which allows users to easily query and aggregate time series data. What is more, PromQL supports a wide range of functions and operators, and is used to perform complex queries on data.
Scalable
Designed to handle large numbers of metrics, handles heavy write and query loads, and has a built-in storage tier optimized for time series data.
Multi Dimensional Data Model
Uses a time series data model where data is stored as a series of metric-value pairs, each with a timestamp. Metrics are identified by unique names and are associated with multiple key value pairs called labels that are used to identify and query specific subsets of data.
Service discovery
Automatically discovers and collects metrics from services in various environments including Kubernetes, EC2, and more.
Data Collection and Storage
Besides, Prometheus uses extract based models to collect metrics from instrumented applications and stores the data in a time series database.
Integration
Easily integrates with Grafana, a popular open source toolbar and visualization tool.
How Prometheus works?
All in all, Prometheus works by extracting metrics from instrumented applications and storing the data in a time series database. The basic architecture of Prometheus consists of the following components:
Server – Responsible for collecting metrics from instrumented applications and storing the data in a time series database.
Push gateway – The gateway allows ad hoc jobs to send metrics to the Prometheus server. Most useful when parsing is not possible or when the operation is transient.
Prometheus Pros
- Grants metrics with an excellent visualization, that is, they are represented visually, which makes their understanding simple.
- Collects data from the instance and in addition to the hosted web portal, it also has an accurate alert system. Fast and precise.
- Allows you to create and send fully customized metrics.
- Slicing of Time Series data and drawing insights from them is one of the best features of Prometheus.
- The response capacity of this program is incredible as well as the preparation and organization of the data.
Prometheus Cons
- One of the worst aspects of this program is the price difference between its competitors, since this may be the most expensive.
- Another feature that does not benefit this program at all is the interface. A bit haphazard and does not allow us a better workflow.
- Instabilities to recognize a device with a weak signal.
- Query language (PromQL) is somewhere complex while building advanced dashboard.
We have arrived to the main part of the article Grafana vs Prometheus – What’s the Difference ?
Grafana vs Prometheus - What's the Difference?
Both, Grafana and Prometheus are open source monitoring tools, but they serve different purposes. On one side- Prometheus-a time series database and monitoring system, while Grafana is a visualization tool that reads data from multiple sources, including Prometheus.
Scalability
Firstly, Prometheus is designed to be highly scalable and handles large amounts of metric data. Grafana, on the other hand, is focused on visualizations and dashboards, and its scalability depends on the underlying data source.
Purpose
Secondly, Prometheus is a time series database and monitoring system, while Grafana is a visualization tool. Importantly, Prometheus is used to collect and store metrics data, and Grafana is used to create dashboards and visualize this data.
Alerting
Thirdly, Prometheus has a built in alerting feature that allows users to set alert conditions for metric data. On the other hand, Grafana does not have built-in alerting capabilities and requires a separate alerting tool to be used in conjunction.
Deployment
Fourthly, Prometheus is distributed as a standalone binary and runs as a standalone service or as part of a larger system. Oppositely, Grafana is deployed as a web application and runs as a standalone service or as part of a larger system.
Language
Fifthly, Prometheus uses its own PromQL query language. While Grafana supports multiple query languages including PromQL, Elasticsearch query language and InfluxQL.
Performance
Grafana performance is measured by the following parameters:
- Use of incremental loading – To reduce slow chart loading, you should prioritize important charts and shrink others.
- Grouping – Shows only the data you need based on screen resolution and chart panel size.
Prometheus in the latest version 2.15 CNCF has made many changes regarding performance. These include:
- Optimizes the use of bytes and bits of memory and data, commonly referred to as blocks.
- Compression that improves performance, because it no longer stores symbols and wires in memory.
Data Storage
Furthermore, Prometheus stores data in time series format. Whilst, Grafana reads data from multiple sources including Prometheus, InfluxDB, and Elasticsearch.
Security
Additionally, Prometheus has built in security features such as authentication and authorization and integrates with external authentication and authorization systems. Moreover, Grafana has also built in authentication and authorization capabilities and can also integrate with external authentication and authorization systems. So here they are both almost exactly the same.
Community
Community of Prometheus is well established and this is popular and widely used tool. Enjoys large and active community. Also, Grafana also has a large and active community, and is widely used in conjunction with Prometheus and other data sources.
Data Model
Lastly, Prometheus uses a multidimensional data model, where metrics are identified by name and a set of key value pairs (labels) that are used to filter and aggregate data. Finally, Grafana works with data in many formats, and the data model depends on the underlying data source.
Thank you for reading Grafana vs Prometheus – What’s the Difference ? We shall conclude the article now.
Grafana vs Prometheus – What’s the Difference ? Conclusion
Summarizing, both Prometheus and Grafana are widely used and have large and active communities. Prometheus focuses more on collecting and storing metrics data, while Grafana focuses more on visualizing this data. Together, they provide a complete solution for monitoring. One part of Prometheus is ideal for data collection and storage, and Grafana for visualization and alerting features.
