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Scale Prometheus

SCALING WITH PROMETHEUS MONITORING EXPLAINED AND HOW TO ADAPT

While Prometheus is the best starting place for cloud native metrics, many organizations struggle with running their own Prometheus instances as they scale. Learn what these common challenges are and how you can overcome them.

Prometheus Monitoring: The Backstory

Since it was first developed by SoundCloud in 2012, Prometheus has grown into the de-facto standard for monitoring in cloud-native environments. It was the second project, after Kubernetes, to be graduated by the Cloud Native Computing Foundation (CNCF).

When Prometheus first emerged, most companies were relying on StatsD and Graphite for monitoring, but as the world shifted to microservices-oriented architecture on container-based infrastructure, companies found these legacy tools insufficient.

What is Prometheus Monitoring?

Prometheus monitoring was designed to be simple to operate, quick to set up and provide immediate value out of the box, but it also offered a label-based approach to monitoring data. This allows users to pivot, group and explore their data along many dimensions which is far better suited for modern cloud-native architectures than the flat hierarchy structure implemented by statsD and Graphite. Largely for those reasons — and the backing of the CNCF — Prometheus has become the clear leader in open source cloud-native monitoring.

The widespread adoption of Prometheus has also changed some of the core dynamics in the monitoring industry. Today, most technologies in the cloud-native landscape provide instrumentation out of the box in the open source Prometheus format. It’s not just the instrumentation either, the standardization of PromQL as the monitoring query language means everyone benefits from the broader community of shared Grafana dashboards and Prometheus alert definitions.

A modern user of software no longer needs to depend on the black box magic of the monitoring vendor’s agent for instrumentation or be locked in to vendor specific dashboarding and alerting. All of this is now provided and maintained by the producers of the software and the broader community – and it’s all open.

Prometheus Management: It’s No Longer So Simple

Prometheus’ single binary implementation for ingestion, storage, and querying makes it ideal as a lightweight metrics and monitoring solution with quick time to value — perfect for cloud-native environments.

But simplicity and ease have their trade-offs: as organizations inevitably scale up their infrastructure footprint and number of microservices, you need to stand up multiple Prometheus instances, which requires significant management overhead.

Free up developer time and headspace
Abnormal Security partnered with Chronosphere when they realized their Prometheus + Grafana monitoring solution had reached its limits. They were unable to scale with the usage of its fast-growing cloud-native application. Chronosphere helped them to cut observability costs, boost platform reliability & performance.

The challenges of Prometheus scaling and monitoring

Prometheus was originally designed in the early days of cloud-native architectures — before organizations were seriously scaling their cloud-native applications. At scale, using Prometheus starts to introduce pain and problems for both the end users of the data as well as the team that manages it.

Here are some of the ways that Prometheus management starts to break down at scale:

Management Overhead

A typical scenario that many users run into is starting out with one Prometheus instance to scrape services. As the number of instances per service or the number of services increases, data can no longer fit in a single Prometheus instance. Organizations usually spin up another instance of Prometheus, leading to separate instances with data split between them, creating challenges such as additional management overhead from sharding and complex design decisions.

Reduced productivity

Running multiple Prometheus instances burdens developers with cognitive load. Users must remember which instance to query, causing significant slowdowns as environments scale. Historical data may not transition properly across instances, complicating data retrieval.

Slower to diagnose upstream/downstream issues

Having multiple Prometheus instances makes achieving a unified view nearly impossible, complicating debugging for upstream or downstream services. Setting up federated instances can provide some visibility but is complex and often unsuccessful.

The risk of flying blind

When running Prometheus on a single node, you risk losing real-time visibility. Running multiple instances may lead to inconsistent results, necessitating duplicate alert configurations, which complicates management and increases overhead.

Uncontrollable metrics storage growth

Prometheus lacks built-in downsampling capabilities, causing storage costs to grow linearly with retention. Users typically store only a week or two of monitoring data, making it difficult to analyze historical trends over longer periods, potentially missing significant insights.

Next steps on your Prometheus scaling and monitoring journey

If any of this sounds familiar, it’s important to know you’re not alone. Many organizations have faced the limitations of Prometheus monitoring at scale and found better solutions. Chronosphere allows you to leverage existing Prometheus and Grafana investments while addressing scaling, visibility, and cost issues. Get started with Chronosphere for more reliable, long-term, scalable monitoring.

How Chronosphere helps

Prometheus FAQs

What is Prometheus?

Prometheus is the de-facto standard for monitoring cloud native environments, allowing users to explore metrics along many dimensions with a pull-based data collection model.

What is PromQL?

PromQL is the functional query language used in Prometheus to select and aggregate time series data in real time.

What are the primary types of Prometheus metrics?

The four primary types of Prometheus metrics are:

Is OpenTelemetry a replacement for Prometheus?

Prometheus and OpenTelemetry are interoperable and both part of the CNCF. Prometheus provides a standard format and storage system, enabling it to ingest and store OpenTelemetry metrics in version 3.0.

More Prometheus Resources

  1. 4 Signs It’s Time to Level Up your Prometheus
  2. Inside Prometheus: An Open Source System That Changed Technology

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