Prometheus is a monitoring tool that has gained popularity in the DevOps community. It’s an open-source system that provides metrics and insights about your applications, infrastructure and business.
The system consists of a core server and multiple remote collectors, responsible for collecting data from various sources. The data is then queried by Prometheus itself or any other external tool (like Grafana) to produce visualizations and statistics that can be used to monitor the performance of your applications or infrastructure.
Benefits of Prometheus
It offers many benefits over other monitoring tools:
- It’s easy to set up and use, even for non-technical users
- High availability built-in
- Fully customizable through configuration files
- Centralized data storage makes it easier to get answers quickly.
The primary benefit of Prometheus is its ease of use and setup. The only software you need to run it is Docker Engine or Kubernetes Engine with the Prometheus Operator installed, or any other orchestration tool that supports running the Prometheus Operator. You can also run it on bare metal or on virtual machines, but if you want to run it on a cloud provider, there are pre-configured AMIs available for Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.
Features of Prometheus
Prometheus can collect metrics from various sources like HTTP and TCP endpoints, and system calls. Prometheus can also perform basic query operations on collected data. PromQL, which stands for Prometheus Query Language, is a domain-specific language (DSL) used to query metrics collected by Prometheus.
Prometheus uses a pull model where nodes must request metrics from remote servers. If a node wants to store its own metrics, it has to run an instance of the Pushgateway locally on each node that should send its information to the Pushgateway server.
Prometheus was designed to be a scalable, high-availability service that can process lots of data from diverse sources quickly and securely. It has a query language called PromQL (Prometheus Query Language), which lets you query metrics from your applications in a standard way.
Prometheus uses pull-based sampling for monitoring. This means it periodically polls each entity of a group or set of groups to collect metrics about them. When a new entity joins the group/set, or an existing one leaves it, the collector will detect this change and begin polling it.
Prometheus supports multiple data structures: histograms (for counting events), gauges (for measuring values with unbounded ranges), counters (for measuring values with finite range), sets (for monitoring unique entities) and timers (for recording time intervals).
The Prometheus monitoring tool is a great tool for monitoring your applications. It has a lot of advantages, but also some cons. Let’s take a look at them.
- It’s open-source and free to use.
- It has a centralized design. It means you do not have to worry about getting lost in the weeds with all your data.
- It’s fully scalable and fault-tolerant, so you can deploy it on multiple servers without losing functionality.
- You can even set up alerts that trigger when specific metrics exceed expectations or drop below what they should be.
Here are some of the biggest issues with Prometheus:
- Limited by the query language. Prometheus’s query language is good, but it does not provide enough flexibility to be truly useful.
- Not intuitive. The interface isn’t intuitive, which can make it difficult for users who aren’t familiar with Prometheus to use it effectively.
- It doesn’t come with an agent, so you will have to install one separately on each server to get the metrics from that server into Prometheus. This can be tedious if there are a lot of servers that need to be monitored.
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