Jaeger vs Telegraf

Overview

Telegraf

Stacks289

Followers321

Votes16

GitHub Stars16.4K

Forks5.7K

Jaeger

Stacks342

Followers464

Votes25

GitHub Stars22.0K

Forks2.7K

Jaeger vs Telegraf: What are the differences?

Data Collection: Jaeger specializes in distributed tracing by collecting data on the flow of requests through various services in an application, providing valuable insights into performance bottlenecks and latency issues. On the other hand, Telegraf is designed for gathering metrics data from systems, services, and databases, allowing for monitoring of resource usage, system health, and other performance metrics.
Data Presentation: Jaeger offers a comprehensive visual representation of the traced requests, showing the entire flow and timings of requests across different services and components. In contrast, Telegraf provides customizable dashboards and graphs for the metrics it collects, allowing users to analyze and understand the performance of their systems based on the gathered data.
Use Case: Jaeger is primarily used for in-depth performance optimization and troubleshooting in microservices architectures, helping developers pinpoint issues and optimize service communication. Telegraf, on the other hand, is more commonly used for monitoring infrastructure and applications at scale, providing valuable insights for resource allocation and capacity planning.
Integration: Jaeger seamlessly integrates with Kubernetes and other container orchestration systems, making it suitable for monitoring applications running in containerized environments. Telegraf, on the other hand, offers a wide range of plugins for integration with various data sources, enabling users to collect metrics from diverse systems and services.
Community Support: Jaeger is an open-source project maintained by the Cloud Native Computing Foundation (CNCF), with an active community contributing to its development and providing support. Telegraf, as part of the broader TICK Stack, also benefits from a strong community and ecosystem of plugins for integration with different monitoring tools and systems.

In Summary, Jaeger excels in distributed tracing for microservices performance optimization, while Telegraf focuses on collecting metrics data for monitoring infrastructure at scale.

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CLI (Node.js)

Manual

Detailed Comparison

Telegraf	Jaeger
It is an agent for collecting, processing, aggregating, and writing metrics. Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics.	Jaeger, a Distributed Tracing System
Statistics
GitHub Stars 16.4K	GitHub Stars 22.0K
GitHub Forks 5.7K	GitHub Forks 2.7K
Stacks 289	Stacks 342
Followers 321	Followers 464
Votes 16	Votes 25
Pros & Cons
Pros 5 Cohesioned stack for monitoring 5 One agent can work as multiple exporter with min hndlng 2 Metrics 2 Open Source 1 Many hundreds of plugins	Pros 7 Easy to install 7 Open Source 6 Feature Rich UI 5 CNCF Project
Integrations
No integrations available	Golang Elasticsearch Cassandra

What are some alternatives to Telegraf, Jaeger?

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.

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

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

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

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).

Related Comparisons

Jaeger vs Telegraf: What are the differences?

Data Collection: Jaeger specializes in distributed tracing by collecting data on the flow of requests through various services in an application, providing valuable insights into performance bottlenecks and latency issues. On the other hand, Telegraf is designed for gathering metrics data from systems, services, and databases, allowing for monitoring of resource usage, system health, and other performance metrics.
Data Presentation: Jaeger offers a comprehensive visual representation of the traced requests, showing the entire flow and timings of requests across different services and components. In contrast, Telegraf provides customizable dashboards and graphs for the metrics it collects, allowing users to analyze and understand the performance of their systems based on the gathered data.
Use Case: Jaeger is primarily used for in-depth performance optimization and troubleshooting in microservices architectures, helping developers pinpoint issues and optimize service communication. Telegraf, on the other hand, is more commonly used for monitoring infrastructure and applications at scale, providing valuable insights for resource allocation and capacity planning.
Integration: Jaeger seamlessly integrates with Kubernetes and other container orchestration systems, making it suitable for monitoring applications running in containerized environments. Telegraf, on the other hand, offers a wide range of plugins for integration with various data sources, enabling users to collect metrics from diverse systems and services.
Community Support: Jaeger is an open-source project maintained by the Cloud Native Computing Foundation (CNCF), with an active community contributing to its development and providing support. Telegraf, as part of the broader TICK Stack, also benefits from a strong community and ecosystem of plugins for integration with different monitoring tools and systems.

In Summary, Jaeger excels in distributed tracing for microservices performance optimization, while Telegraf focuses on collecting metrics data for monitoring infrastructure at scale.

Jaeger vs Telegraf

Overview