What is Prometheus Cortex ?

In the current digital era, where milliseconds count, software applications must be sustained, which calls for a robust monitoring and warning system. Introducing Prometheus Cortex, a powerful addition to the Prometheus ecosystem that provides long-term, scalable storage along with sophisticated querying capabilities. Let’s take a closer look at Prometheus Cortex, going over all of its features, from its practical applications to its foundations.

Prometheus Cortex is not simply another tool in the monitoring toolbox; it is a revolutionary innovation. Consider it an improvement on Prometheus, the well-loved open-source monitoring and alerting system within the DevOps community. Cortex excels at managing enormous volumes of time series data, but what really sets it apart are its scalable architecture and long-term storage capabilities.

With Cortex, Prometheus has an extremely accessible and scalable backend that allows isolated metrics throughout the multi-tenant architecture. Cortex also provides long-term storage for customized metrics, enabling the construction of dynamic dashboards with charts and graphs as well as historical search capabilities. This allows DevOps teams to modify their visualizations of real-time network traffic to support cloud computing apps in production or to monitor additional runtime events like remote processing and data mining for machine learning (ML).

• Prometheus: Talking about Cortex would be incomplete without including Prometheus. As a dedicated watchdog, it collects measures from your systems and apps, making it the hub and lifeblood of the monitoring sector.
• Cortex: This is the current magical area. It takes Prometheus to a new level with its scalable storage and powerful querying tools, making it a vital tool for anyone handling massive amounts of metrics data.
• Data in Time Series: Imagine an endless stream of information that captures the life force of your systems. That’s the kind of time-series data that Cortex and Prometheus excel at managing.
• Horizontal Scalability: Visualize a Lego castle as your monitoring configuration. With horizontal scalability, you can effortlessly handle an ever-increasing workload by adding more bricks, or servers, without breaking a sweat.
• Long-Term Storage: Long-term storage guarantees that you can go back in time and examine past measurements to find trends and patterns, much like a treasure trove for your data.

Prometheus and Prometheus Cortex are two related but distinct concepts in the world of monitoring and observability. Here’s a breakdown of the key differences:

Prometheus

• Prometheus is an open-source monitoring system and time series database that collects metrics from various sources, such as applications, services, and infrastructure.
• It provides a query language called PromQL to extract insights from the collected data.
• Prometheus is designed to be highly scalable and can handle large amounts of data.
• It is widely used in production environments for monitoring and alerting.

Prometheus Cortex

• Prometheus Cortex is an open-source, horizontally scalable, and highly available long-term storage solution for Prometheus.
• It is designed to store and query large amounts of time series data, making it suitable for big data use cases.
• Cortex provides a distributed architecture, allowing it to scale horizontally and handle high volumes of data.
• It is often used in conjunction with Prometheus to provide a complete monitoring and observability solution.

Key differences

• Purpose: Prometheus is a monitoring system, while Prometheus Cortex is a long-term storage solution for Prometheus.
• Scalability: Both Prometheus and Cortex are designed to be scalable, but Cortex is specifically designed for large-scale, distributed environments.
• Data storage: Prometheus stores data in memory and on disk, while Cortex stores data in a distributed NoSQL database.
• Querying: Prometheus provides a query language (PromQL) for querying data, while Cortex provides a query engine that can handle complex queries and aggregations.

When to use each

• Use Prometheus when you need a monitoring system that can collect and store metrics from various sources and doesn’t require long-term storage or high scalability.
• Use Prometheus Cortex when you need a scalable, long-term storage solution for large amounts of time series data and want to leverage the power of Prometheus’ query language and alerting capabilities.

Prometheus is a monitoring system, while Prometheus Cortex is a long-term storage solution for Prometheus. Both are powerful tools for monitoring and observability, but they serve different purposes and are designed for different use cases.

Cortex is a complex organizational structure that includes many web server platforms, databases, load balancing, storage, and cache layers. The diagram below shows how Cortex functions in a cloud data center installation that uses container virtualization and Kubernetes to handle multi-tenant software applications.

Now, let’s get down to the nitty-gritty of how Cortex works its magic:

• First things first: Cortex gathers metrics data from many sources, including Prometheus servers, and stores it in a distributed storage backend.
• Horizontal Scalability: Cortex’s superpower is its ability to grow horizontally, which allows you to add more Cortex nodes as needed to beef up your monitoring arrangement. It’s similar to having a horde of observant minions at your disposal.
• Long-Term Storage: Cortex ensures that you won’t lose important historical data. Everything is safely stored, enabling you to review previous metrics and learn more about the evolution of your system’s performance.
• Querying and Visualization: You can find hidden gems of information by slicing and dicing your metrics data to your heart’s content with PromQL (Prometheus Query Language). Furthermore, you can easily monitor your data by transforming your findings into stunning visuals with the help of programs like Grafana.

Using Kubernetes’ Helm package manager, Cortex is simple to install. We must first install consul as the data store inside the cluster before we can use the standard helm chart that the Cortex team created.

 $ helm repo add hashicorp https://helm.releases.hashicorp.com
 $ helm search repo hashicorp/consul
 $ helm install consul hashicorp/consul --set global.name=consul --namespace cortex

Verify the consul nodes by using kubectl.

After setting up the datastore, we must set up the storage gateway to communicate with a distant storage backend.

Default values file of Cortex according to our use-case:

$ helm repo add cortex-helm https://cortexproject.github.io/cortex-helm-chart
$ helm install cortex --namespace cortex -f my-cortex-values.yaml cortex-helm/cortex

Here we are pretty much done with the cortex setup, and now it’s time to configure the prometheus to connect with the cortex. Now that the Cortex setup, and the initial part of the setup are complete, it’s time to configure Prometheus. We only need to supply a remote write URL in Prometheus; other than that, not many configuration changes are required. Prometheus includes a remote write and read API for sending and receiving metrics samples to a third-party API, in this case, Cortex.

All we need to do is include these block lines in our prometheus.yaml file.

remote_write:
  url: http://cortex.cortex/api/prom/push

Let’s dive into a practical example to better understand how Prometheus Cortex works and its significance in real-world scenarios. Imagine you’re managing a fleet of servers for an e-commerce website. Each server generates a multitude of metrics, such as CPU usage, memory consumption, and network traffic. You want to monitor these metrics in real-time and also retain historical data for analysis and capacity planning.

Here’s where Prometheus Cortex comes into play:

• Data Collection with Prometheus: You deploy Prometheus on each server to collect metrics. Prometheus regularly scrapes these servers, gathering data like CPU usage, memory utilization, and more. This data is then stored temporarily within Prometheus.
• Ingestion into Cortex: Now, you link Prometheus with Cortex to guarantee scalability and long-term storage. Metric data can be seamlessly ingested by Cortex, which functions as an extension of Prometheus. Cortex saves metrics in its distributed storage backend as they are received from Prometheus.
• Scalability and High Availability: The more popular your e-commerce firm gets, the more servers you need, and the amount of metrics data you collect explodes. You may use Cortex to simply scale horizontally by adding more Cortex nodes. These nodes work together to distribute the load and offer high availability. In this manner, in the event that one node fails, the other ones will take over and keep your monitoring system operational.
• Long-Term Storage and Querying: Cortex excels at long-term storage. History records can be kept for as long as needed because all metrics and data are safely retained. This is useful for forecasting, trend analysis, and troubleshooting previous issues. PromQL’s powerful querying capabilities let you extract meaningful information from this data. To improve resource allocation, for instance, you could look for patterns in network traffic. Alternatively, you could look at past CPU spikes to predict future capacity needs.
• Visualization with Grafana: All of this data may be visualized, and some sense may be made of using tools such as Grafana. Create custom dashboards and visualizations with Grafana thanks to its easy interaction with Cortex and Prometheus. You can set up alerts to be informed of any anomalies, in addition to monitoring vital metrics in real-time and following historical trends.

In our example, Prometheus Cortex serves as the backbone of your monitoring infrastructure, providing scalable, long-term storage and advanced querying capabilities. It ensures that you have a complete picture of your system’s health, enabling you to make informed decisions and keep your e-commerce platform running smoothly, even as it scales to new heights.

Prometheus Cortex is essentially more than just a tool; for anyone navigating the rough seas of contemporary IT infrastructure, it is a ray of hope. By using its strength, you can navigate your ship through choppy waters and come out on top, your systems moving smoothly in the direction of achievement.

Can I use Prometheus Cortex without Prometheus?

Nope, Cortex is like the Robin in Prometheus’s Batman. It relies on Prometheus for collecting metrics, so you’ll need both to make the magic happen.

How does Cortex ensure high availability?

Cortex spreads its wings by replicating and distributing data across multiple nodes, ensuring that even if one node goes down, your monitoring setup remains rock-solid.

Can Cortex play nice with cloud storage solutions?

Absolutely! Cortex can cozy up to cloud storage giants like Amazon S3, Google Cloud Storage, and Azure Blob Storage, giving you the flexibility to store your metrics data wherever suits you best.

Is Prometheus Cortex only for large-scale deployments?

While Cortex shines in large-scale environments, it’s just as comfy in smaller setups. Whether you’re monitoring a handful of servers or a sprawling cloud infrastructure, Cortex has your back.

What makes Prometheus Cortex stand out from the crowd?

Cortex’s secret sauce lies in its scalability, long-term storage capabilities, and seamless integration with Prometheus. It’s like having a Swiss army knife for your monitoring needs.