How to set up Cortex with Prometheus?

You need to configure Prometheus to remote-write metrics to Cortex ingesters, and deploy Cortex components like distributors and queriers. The getting started guide provides step-by-step instructions for integration.

Cortex vs Thanos: which is better for scalable Prometheus?

Cortex excels in multi-tenant, cloud-native environments with built-in support for object storage and high availability, while Thanos might be simpler for single-tenant setups with its sidecar approach. Both offer scalability but differ in architecture and operational model.

What storage backends does Cortex support?

Cortex supports cloud object stores like Amazon S3, Google Cloud Storage, Swift, and Microsoft Azure for long-term metric retention, as listed in the features. Local storage is used for caching but not for durable long-term data.

How does Cortex handle multi-tenancy?

It isolates data and queries through tenant IDs, allowing multiple independent Prometheus sources to share a cluster without data leakage. This is a core feature mentioned in the README for enterprise-scale monitoring.

Can I use Cortex without Kubernetes?

Yes, Cortex can be deployed standalone, but it's optimized for cloud-native environments and often run on Kubernetes. The documentation includes configuration options for various deployment scenarios.

What are the performance implications of using Cortex?

While scalable, Cortex may introduce latency due to network calls and distributed processing. The README references talks like 'Blazin' Fast PromQL' for optimization tips, but performance varies with scale and setup.

How to monitor Cortex itself?

Cortex exposes Prometheus-compatible metrics that can be scraped by another Prometheus instance. The documentation includes security and operational guides for monitoring and maintaining the system.

Open-Awesome

cortex

Apache-2.0Gov1.21.1

A horizontally scalable, highly available, multi-tenant, long-term storage solution for Prometheus and OpenTelemetry Metrics.

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5.9k stars877 forks0 contributors

What is cortex?

Cortex is a horizontally scalable, highly available, long-term storage solution for Prometheus and OpenTelemetry Metrics. It solves the problem of running Prometheus at massive scale by providing multi-tenancy, durable storage, and cluster-wide scalability while maintaining full Prometheus compatibility.

Target Audience

Site reliability engineers (SREs), DevOps teams, and platform engineers who need to operate Prometheus at scale in multi-tenant, cloud-native environments.

Value Proposition

Developers choose Cortex because it extends Prometheus to enterprise-scale deployments without breaking compatibility, offering built-in multi-tenancy, horizontal scalability, and long-term storage integration with cloud object stores.

Overview

A horizontally scalable, highly available, multi-tenant, long term Prometheus.

Use Cases

Best For

Storing Prometheus metrics long-term in cloud object storage like S3 or GCS
Running Prometheus as a multi-tenant service for multiple teams or customers
Scaling Prometheus beyond single-node limitations in large Kubernetes clusters
Ensuring high availability for Prometheus metrics through replication
Ingesting and querying OpenTelemetry metrics alongside Prometheus data
Building a centralized, scalable monitoring platform for cloud-native applications

Not Ideal For

Small-scale deployments with a single Prometheus instance and no multi-tenancy needs
Projects that cannot or refuse to use cloud object storage like S3 or GCS for long-term retention
Environments with ultra-low latency requirements for real-time metric queries
Teams lacking the expertise to operate and troubleshoot complex distributed systems

Pros & Cons

Pros

Horizontal Scalability

Cortex can run across multiple machines in a cluster, exceeding the throughput and storage limits of a single Prometheus instance, as explicitly stated in the README's features.

Built-in Multi-tenancy

It isolates data and queries from multiple independent Prometheus sources within a single cluster, enabling centralized monitoring for different teams or customers without interference.

Cloud Storage Integration

Supports long-term storage with S3, GCS, Swift, and Azure, providing durable, cost-effective retention for metrics, as highlighted in the key features.

High Availability

When deployed in a cluster, Cortex replicates data between machines to ensure reliability and fault tolerance, making it suitable for production environments.

Cons

Operational Complexity

As a distributed system, Cortex requires significant setup and management effort, with multiple components to configure and monitor, which is evident from the detailed architecture and configuration documentation.

Cloud Vendor Lock-in

Long-term storage is tightly coupled with specific cloud object stores, potentially tying users to those platforms and adding dependency on external services.

Query Latency Overhead

The distributed nature can introduce higher latency for queries compared to local Prometheus, which might impact real-time monitoring scenarios, a trade-off mentioned in scalability discussions.

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