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A highly scalable real-time graphing system
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What is Graphite?

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
Graphite is a tool in the Monitoring Tools category of a tech stack.
Graphite is an open source tool with 4.6K GitHub stars and 1.2K GitHub forks. Here’s a link to Graphite's open source repository on GitHub

Who uses Graphite?

Companies
112 companies use Graphite in their tech stacks, including Uber, Twitch, and hike.

Developers
143 developers use Graphite.

Graphite Integrations

Geckoboard, Hosted Graphite, Scalyr, Grafana, and SignalFx are some of the popular tools that integrate with Graphite. Here's a list of all 12 tools that integrate with Graphite.

Why developers like Graphite?

Here’s a list of reasons why companies and developers use Graphite
Graphite Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Graphite in their tech stack.

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 8 upvotes · 154.9K views
atUber TechnologiesUber Technologies
Nagios
Grafana
Graphite
Prometheus

Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:

By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.

To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...

https://eng.uber.com/m3/

(GitHub : https://github.com/m3db/m3)

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Trey Tacon
Trey Tacon
Amazon CloudWatch
PagerDuty
Grafana
Graphite
StatsD
Sentry

A huge part of our continuous deployment practices is to have granular alerting and monitoring across the platform. To do this, we run Sentry on-premise, inside our VPCs, for our event alerting, and we run an awesome observability and monitoring system consisting of StatsD, Graphite and Grafana. We have dashboards using this system to monitor our core subsystems so that we can know the health of any given subsystem at any moment. This system ties into our PagerDuty rotation, as well as alerts from some of our Amazon CloudWatch alarms (we’re looking to migrate all of these to our internal monitoring system soon).

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StackBot 🤖
StackBot 🤖
Icinga
Graphite
Logstash
Elasticsearch
Grafana
Kibana

One size definitely doesn’t fit all when it comes to open source monitoring solutions, and executing generally understood best practices in the context of unique distributed systems presents all sorts of problems. Megan Anctil, a senior engineer on the Technical Operations team at Slack gave a talk at an O’Reilly Velocity Conference sharing pain points and lessons learned at wrangling known technologies such as Icinga, Graphite, Grafana, and the Elastic Stack to best fit the company’s use cases.

At the time, Slack used a few well-known monitoring tools since it’s Technical Operations team wasn’t large enough to build an in-house solution for all of these. Nor did the team think it’s sustainable to throw money at the problem, given the volume of information processed and the not-insignificant price and rigidity of many vendor solutions. With thousands of servers across multiple regions and millions of metrics and documents being processed and indexed per second, the team had to figure out how to scale these technologies to fit Slack’s needs.

On the backend, they experimented with multiple clusters in both Graphite and ELK, distributed Icinga nodes, and more. At the same time, they’ve tried to build usability into Grafana that reflects the team’s mental models of the system and have found ways to make alerts from Icinga more insightful and actionable.

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Graphite

Utilizando computação em nuvens e o modelo de pagar pelo uso com _graphite _nós conseguimos analisar todos os logs de informação gerada pelo sistema. Graphite

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Graphite's features

  • carbon - a Twisted daemon that listens for time-series data
  • whisper - a simple database library for storing time-series data (similar in design to RRD)
  • graphite webapp - A Django webapp that renders graphs on-demand using Cairo

Graphite Alternatives & Comparisons

What are some alternatives to Graphite?
Graphene
Graphene is a Python library for building GraphQL schemas/types fast and easily.
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
Kibana
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Nagios
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
See all alternatives

Graphite's Stats