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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Network Monitoring
  5. Metricbeat vs Packetbeat

Metricbeat vs Packetbeat

OverviewDecisionsComparisonAlternatives

Overview

Packetbeat
Packetbeat
Stacks15
Followers44
Votes4
Metricbeat
Metricbeat
Stacks48
Followers125
Votes3

Metricbeat vs Packetbeat: What are the differences?

# Introduction

Key differences between Metricbeat and Packetbeat:

1. **Data Type Monitored**:
Metricbeat collects system-level metrics, while Packetbeat focuses on network traffic monitoring.
   
2. **Metrics vs Packets**:
Metricbeat collects numeric data metrics like CPU usage, memory consumption, and disk utilization, while Packetbeat captures and analyzes actual network packets allowing for deep network traffic insights.

3. **Application Focus**:
Metricbeat is more focused on monitoring infrastructure metrics for systems and applications, while Packetbeat is specifically geared towards network traffic analysis for troubleshooting and security purposes.

4. **Protocols Supported**:
Metricbeat typically supports collecting metrics from various platforms like Docker, Apache, MySQL, and others, whereas Packetbeat focuses on capturing, decoding, and analyzing data from protocols like HTTP, DNS, MySQL, etc.

5. **Granularity of Data**:
Metricbeat provides aggregated metrics about the system and applications, while Packetbeat offers detailed insights into network traffic capturing individual packets and their contents.

6. **Use Cases**:
Metricbeat is commonly used for infrastructure monitoring, performance analysis, and capacity planning, while Packetbeat is utilized for network troubleshooting, identifying application performance issues, and detecting security threats in real-time.

In Summary, Metricbeat and Packetbeat differ in the type of data monitored, focus on metrics vs packets, supported protocols, granularity of data, application focus, and use cases.

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Advice on Packetbeat, Metricbeat

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.

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Comments

Detailed Comparison

Packetbeat
Packetbeat
Metricbeat
Metricbeat

Packetbeat agents sniff the traffic between your application processes, parse on the fly protocols like HTTP, MySQL, Postgresql or REDIS and correlate the messages into transactions.

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.

Packetbeat Statistics: Contains high-level views like the network topology, the application layer protocols repartition, the response times repartition, and others;Packetbeat Search: This page enables you to do full text searches over the indexed network messages;Packetbeat Query Analysis: This page demonstrates more advanced statistics like the top N slow SQL queries, the database throughput or the most common MySQL erro
System-Level Monitoring; system-level CPU usage statistics; Network IO statistics
Statistics
Stacks
15
Stacks
48
Followers
44
Followers
125
Votes
4
Votes
3
Pros & Cons
Pros
  • 2
    Easy setup
  • 2
    Works well with ELK stack
Pros
  • 2
    Simple
  • 1
    Easy to setup
Integrations
No integrations available
Redis
Redis
Linux
Linux
NGINX
NGINX
Windows
Windows

What are some alternatives to Packetbeat, Metricbeat?

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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