Graphite聽vs聽Statsite

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Graphite
Graphite

283
221
+ 1
38
Statsite
Statsite

4
8
+ 1
0
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Graphite vs Statsite: What are the differences?

Developers describe Graphite as "A highly scalable real-time graphing system". Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand. On the other hand, Statsite is detailed as "C implementation of statsd". Statsite is a metrics aggregation server. Statsite is based heavily on Etsy's StatsD https://github.com/etsy/statsd, and is wire compatible.

Graphite and Statsite can be primarily classified as "Monitoring" tools.

Some of the features offered by Graphite are:

  • 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

On the other hand, Statsite provides the following key features:

  • Multiple metric types
  • Efficient summary metrics for timer data
  • Dynamic set implementation

Graphite and Statsite are both open source tools. Graphite with 4.59K GitHub stars and 1.2K forks on GitHub appears to be more popular than Statsite with 1.73K GitHub stars and 241 GitHub forks.

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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

What is Statsite?

Statsite is a metrics aggregation server. Statsite is based heavily on Etsy's StatsD https://github.com/etsy/statsd, and is wire compatible.
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            What are some alternatives to Graphite and Statsite?
            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.
            Pencil
            A web application microframework for Rust
            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.
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            Decisions about Graphite and Statsite
            StackShare Editors
            StackShare Editors
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            One size definitely doesn鈥檛 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鈥橰eilly 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鈥檚 use cases.

            At the time, Slack used a few well-known monitoring tools since it鈥檚 Technical Operations team wasn鈥檛 large enough to build an in-house solution for all of these. Nor did the team think it鈥檚 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鈥檚 needs.

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

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            Conor Myhrvold
            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber | 9 upvotes 546.1K views
            atUber TechnologiesUber Technologies
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            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鈥檚 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鈥檚 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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            Amazon CloudWatch
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            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鈥檙e looking to migrate all of these to our internal monitoring system soon).

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            Interest over time
            Reviews of Graphite and Statsite
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            How developers use Graphite and Statsite
            Avatar of Onezino Gabriel
            Onezino Gabriel uses GraphiteGraphite

            Utilizando computa莽茫o em nuvens e o modelo de pagar pelo uso com _graphite _n贸s conseguimos analisar todos os logs de informa莽茫o gerada pelo sistema.

            Avatar of Tongliang Liu
            Tongliang Liu uses GraphiteGraphite

            Great metrics visualization tool together with StatsD.

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