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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Netflix FlameScope vs Thanos

Netflix FlameScope vs Thanos

OverviewComparisonAlternatives

Overview

Netflix FlameScope
Netflix FlameScope
Stacks6
Followers16
Votes0
GitHub Stars3.1K
Forks176
Thanos
Thanos
Stacks100
Followers126
Votes0

Netflix FlameScope vs Thanos: What are the differences?

# Introduction
Netflix FlameScope and Thanos are powerful tools used for analyzing and visualizing performance data for distributed systems. They both provide different features and functionalities to help developers and system administrators understand the behavior of their systems.

1. **Scope of Visualization**: FlameScope focuses on providing visualizations for CPU flame graphs, while Thanos specializes in visualizing monitoring and observability data for distributed systems, including metrics, logs, and traces.
2. **Data Sources**: FlameScope primarily works with profiling data from individual machines, focusing on performance optimization at a low level. In contrast, Thanos consolidates and visualizes data from various sources, making it suitable for analyzing complex interactions across multiple components in a distributed system.
3. **Integrations**: Thanos offers integrations with popular monitoring systems like Prometheus, Grafana, and Cortex, allowing users to easily combine different types of data for holistic analysis. FlameScope, on the other hand, is more independent and can be used with various data sources, but may require additional setup to integrate with other systems.
4. **Scalability**: Thanos is designed to handle large amounts of monitoring data and can scale horizontally to accommodate growing system requirements. FlameScope, while efficient for individual machine profiling, may face limitations when dealing with extensive data sets from multiple sources.
5. **Query Capabilities**: Thanos provides powerful query functionalities that enable users to perform complex queries on monitoring data to extract valuable insights. FlameScope, while effective for visual representation, may lack advanced querying capabilities that are essential for in-depth analysis of distributed systems.
6. **Community and Support**: Thanos has a larger active community of users and contributors, resulting in more frequent updates, improvements, and support resources. FlameScope, being more specialized in CPU flame graph visualization, may have a smaller user base and limited community support for addressing issues and enhancing functionalities.

In Summary, Netflix FlameScope and Thanos offer distinct features for analyzing performance data, with FlameScope focusing on CPU flame graph visualization for individual machines, while Thanos specializes in monitoring and analyzing data from distributed systems with integrations, scalability, and advanced query capabilities.

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Detailed Comparison

Netflix FlameScope
Netflix FlameScope
Thanos
Thanos

FlameScope begins by displaying the input data as an interactive subsecond-offset heat map. This shows patterns in the data. You can then select a time range to highlight on different patterns, and a flame graph will be generated just for that time range.

Thanos is a set of components that can be composed into a highly available metric system with unlimited storage capacity. It can be added seamlessly on top of existing Prometheus deployments and leverages the Prometheus 2.0 storage format to cost-efficiently store historical metric data in any object storage while retaining fast query latencies. Additionally, it provides a global query view across all Prometheus installations and can merge data from Prometheus HA pairs on the fly.

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Global querying view across all connected Prometheus servers; Deduplication and merging of metrics collected from Prometheus HA pairs; Seamless integration with existing Prometheus setups; Any object storage as its only, optional dependency; Downsampling historical data for massive query speedup; Cross-cluster federation; Fault-tolerant query routing; Simple gRPC "Store API" for unified data access across all metric data; Easy integration points for custom metric providers
Statistics
GitHub Stars
3.1K
GitHub Stars
-
GitHub Forks
176
GitHub Forks
-
Stacks
6
Stacks
100
Followers
16
Followers
126
Votes
0
Votes
0
Integrations
No integrations available
Prometheus
Prometheus

What are some alternatives to Netflix FlameScope, Thanos?

Grafana

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

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

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

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

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