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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Jaeger vs Metricbeat

Jaeger vs Metricbeat

OverviewDecisionsComparisonAlternatives

Overview

Metricbeat
Metricbeat
Stacks48
Followers125
Votes3
Jaeger
Jaeger
Stacks340
Followers464
Votes25
GitHub Stars22.0K
Forks2.7K

Jaeger vs Metricbeat: What are the differences?

## Key Differences between Jaeger and Metricbeat

Jaeger and Metricbeat are two different tools used for monitoring and tracing activities within an application or system. Both tools serve specific purposes and offer unique features that cater to different monitoring needs. Below are the key differences between Jaeger and Metricbeat:

1. **Purpose**: Jaeger is an open-source end-to-end distributed tracing system used for monitoring and troubleshooting microservices-based distributed systems. It helps in monitoring the performance of each microservice and tracing the flow of requests across different services. On the other hand, Metricbeat is a lightweight shipper that collects and sends system and service metrics to various monitoring systems. It focuses more on monitoring system-level metrics rather than tracing request flows.
   
2. **Data Collection**: In terms of data collection, Jaeger primarily collects distributed traces to provide insights into the flow of requests through different microservices. It captures detailed information about the duration and operations of each request, allowing for in-depth performance analysis. Metricbeat, on the other hand, collects metrics such as CPU usage, memory usage, disk utilization, and network traffic from the system and services. It provides overall system health and performance metrics rather than request-specific tracing data.
   
3. **Integration**: Jaeger is commonly integrated with application code and runtime environments to capture traces at the code level and trace requests as they move across services. It is often used by developers and DevOps teams to identify bottlenecks and optimize performance. On the contrary, Metricbeat is integrated with various monitoring systems like Elasticsearch, Prometheus, and InfluxDB to send collected metrics for visualization and alerting. It is more of a complementary tool to other monitoring systems rather than a standalone monitoring solution.
   
4. **Scalability**: Jaeger is designed to handle large volumes of trace data generated by distributed systems, making it suitable for highly complex microservices architectures. It provides mechanisms for distributed storage, sampling, and aggregation to handle trace data efficiently. Metricbeat is lightweight and efficient in collecting system metrics on individual hosts or containers, making it scalable for monitoring a large number of servers or containers in a clustered environment.
   
5. **Visualizations**: Jaeger offers interactive visualizations and dependency graphs that help visualize the flow of requests through different services, making it easier to identify performance bottlenecks and troubleshoot issues. Metricbeat, on the other hand, provides pre-built visualizations and dashboards in monitoring systems like Kibana or Grafana to display system metrics in a more structured and organized manner.

In Summary, Jaeger focuses on distributed tracing for microservices-based architectures, while Metricbeat is more geared towards collecting and sending system metrics for monitoring and analysis purposes.

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Advice on Metricbeat, Jaeger

Sunil
Sunil

Team Lead at XYZ

Jun 15, 2020

Needs adviceonPrometheusPrometheusGrafanaGrafanaLinuxLinux

Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.

Is it OK to use Metricbeat for Linux server or can we use Prometheus?

What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?

Regards, Sunil.

595k views595k
Comments

Detailed Comparison

Metricbeat
Metricbeat
Jaeger
Jaeger

Collect metrics from your systems and services. From CPU to memory, Redis to NGINX, and much more, It is a lightweight way to send system and service statistics.

Jaeger, a Distributed Tracing System

System-Level Monitoring; system-level CPU usage statistics; Network IO statistics
-
Statistics
GitHub Stars
-
GitHub Stars
22.0K
GitHub Forks
-
GitHub Forks
2.7K
Stacks
48
Stacks
340
Followers
125
Followers
464
Votes
3
Votes
25
Pros & Cons
Pros
  • 2
    Simple
  • 1
    Easy to setup
Pros
  • 7
    Open Source
  • 7
    Easy to install
  • 6
    Feature Rich UI
  • 5
    CNCF Project
Integrations
Redis
Redis
Linux
Linux
NGINX
NGINX
Windows
Windows
Golang
Golang
Elasticsearch
Elasticsearch
Cassandra
Cassandra

What are some alternatives to Metricbeat, Jaeger?

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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