opentelemetry-collector
prometheus
Our great sponsors
opentelemetry-collector | prometheus | |
---|---|---|
16 | 374 | |
3,810 | 52,380 | |
3.8% | 1.5% | |
9.9 | 9.9 | |
about 8 hours ago | about 18 hours ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
opentelemetry-collector
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OpenTelemetry Collector Anti-Patterns
But how does one monitor a Collector? The OTel Collector already emits metrics for the purposes of its own monitoring. These can then be sent to your Observability backend for monitoring.
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OpenTelemetry Journey #00 - Introduction to OpenTelemetry
Maybe, you are asking yourself: "But I already had instrumented my applications with vendor-specific libraries and I'm using their agents and monitoring tools, why should I change to OpenTelemetry?". The answer is: maybe you're right and I don't want to encourage you to update the way how you are doing observability in your applications, that's a hard and complex task. But, if you are starting from scratch or you are not happy with your current observability infrastructure, OpenTelemetry is the best choice, independently of the backend telemetry tool that you are using. I would like to invite you to take a look at the number of exporters available in the collector contrib section, if your backend tracing tool is not there, probably it's already using the Open Telemetry Protocol (OTLP) and you will be able to use the core collector. Otherwise, you should consider changing your backend telemetry tool or contributing to the project creating a new exporter.
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Building an Observability Stack with Docker
To receive OTLP data, you set up the standard otlp receiver to receive data in HTTP or gRPC format. To forward traces and metrics, a batch processor was defined to accumulate data and send it every 100 milliseconds. Then set up a connection to Tempo (in otlp/tempo exporter, with a standard top exporter) and to Prometheus (in prometheus exporter, with a control exporter). A debug exporter also was added to log info on container standard I/O and see how the collector is working.
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Amazon EKS Monitoring with OpenTelemetry [Step By Step Guide]
You can find more details on advanced configurations here.
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Go 1.21
> opentelemetry is basically a house of antipatterns
"Look on My Works Ye Mighty and Despair!"
https://github.com/open-telemetry/opentelemetry-collector/tr... -> https://github.com/open-telemetry/opentelemetry-collector-re... ... and then a reasonable person trying to load that mess into their head may ask 'err, what's the difference between go.opentelemetry.io/collector and github.com/open-telemetry/opentelemetry-collector-contrib?'
$ curl -fsS go.opentelemetry.io/collector | grep go-import
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Display CockroachDB metrics in Splunk Dashboards
There are 2 collector types: the core and the contrib. I have used the contrib as it features the splunk_hec exporter.
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Observability Mythbusters: How hard is it to get started with OpenTelemetry?
Lightstep ingests data in native OpenTelemetry Protocol (OTLP) format, so we will use the OTLP Exporter. The exporter can be called either otlp or follow the naming format otlp/. We could call it otlp/bob if we wanted to. We're calling our exporter otlp/ls to signal to us that we are using the OTLP exporter to send the data to Lightstep.
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OpenTelemetry Collector: A Friendly Guide for Devs
Then, we set up a batch processor that batches up the spans together and every 1 second sends the batch forward. In production, you would want more than 1 second, but I set this here to 1 second for instant feedback in Jaeger.
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OpenTelemetry in Dotnet
Batch allows for metrics, traces etc to be batched into bundles. The default is 8192 and then it will send, the timeout is the max time before sending regardless. I'd highly recommend utilising batches if you're dealing with high volumes of traffic.
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Prometheus Agent Mode, for Metric Forwarding
There were a bunch of alternatives to solve this before, like grafana agent [0], vm agent [1] or opentelemetry collector [2].
[0] - https://github.com/grafana/agent
[1] - https://github.com/VictoriaMetrics/VictoriaMetrics/tree/mast...
[2] - https://github.com/open-telemetry/opentelemetry-collector
prometheus
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Observability at KubeCon + CloudNativeCon Europe 2024 in Paris
Prometheus
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
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Building an Observability Stack with Docker
After that, you will set up a metrics server container. It will use Prometheus.io, an open-source monitoring and alerting toolkit designed to collect, store, and query time series data, making it a tool for monitoring your systems' performance and health through metrics.
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Root Cause Chronicles: Quivering Queue
Thankfully KEDA operator was already part of the cluster, and all Robin had to do was create a ScaledObject manifest targeting the Dispatch ScaleUp event, based on the rabbitmq_global_messages_received_total metric from Prometheus.
- Diagnósticos usando dotnet-monitor + prometheus + grafana
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Prometheus Fundamentals (Lesson-01)
$ wget https://github.com/prometheus/prometheus/releases/download/v2.48.1/prometheus-2.48.1.linux-amd64.tar.gz
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Start your server remotely
I build the Tasmota firmware for the S31's nightly, and expose the Prometheus endpoint so I can also monitor the current used by these devices in real time with the data pushed to Grafana. I have ~30 of them in my home/homelab, and servers, appliances, sump pump, fans, etc. are all monitored by my S31 fleet.
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List of your reverse proxied services
Prometheus
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PM2 module to monitoring node.js application with export to Prometheus and Grafana
In most cases, applications use the combination of Prometheus + Grafana, which allows collect data and display it in the form of graphs and also to set up alerts for changes in any metrics.
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Exploring the OpenTelemetry Collector
Prometheus is one of the primary monitoring solutions. It works on a pull-based model: Prometheus scrapes compatible endpoints of your application(s) and stores them internally.
What are some alternatives?
metrics-server - Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
skywalking - APM, Application Performance Monitoring System
Jolokia - JMX on Capsaicin
Telegraf - The plugin-driven server agent for collecting & reporting metrics.
JavaMelody - JavaMelody : monitoring of JavaEE applications
Glowroot - Easy to use, very low overhead, Java APM
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
signoz - SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool
jaeger - CNCF Jaeger, a Distributed Tracing Platform
Performance Co-Pilot - Performance Co-Pilot
uptime-kuma - A fancy self-hosted monitoring tool
Collectd - The system statistics collection daemon. Please send Pull Requests here!