opentelemetry-collector
Grafana
opentelemetry-collector | Grafana | |
---|---|---|
16 | 380 | |
3,892 | 60,503 | |
2.1% | 0.8% | |
9.9 | 10.0 | |
5 days ago | 3 days ago | |
Go | TypeScript | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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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Options Pattern in Golang
open-telemetry/opentelemetry-collector: OpenTelemetry Collector (github.com)
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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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OpenTelemetry Collector on Kubernetes – Part 1
We are setting the deployment to have exactly 1 replica and setting the container CPU and memory limits according to the minimum that was checked for performance in their docs.
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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.
Grafana
- Grafana: From Dashboards to Centralized Observability
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.
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Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.
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Monitoring, Observability, and Telemetry Explained
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
- Grafana: Open and composable observability and data visualization platform
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The Mechanics of Silicon Valley Pump and Dump Schemes
Grafana
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Reverse engineering the Grafana API to get the data from a dashboard
Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.
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Building an Observability Stack with Docker
So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:
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How to collect metrics from node.js applications in PM2 with exporting to Prometheus
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:
What are some alternatives?
go-sql-driver/mysql - Go MySQL Driver is a MySQL driver for Go's (golang) database/sql package
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
GORM - The fantastic ORM library for Golang, aims to be developer friendly
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
jaeger - CNCF Jaeger, a Distributed Tracing Platform
Heimdall - An Application dashboard and launcher
go-ethereum - Go implementation of the Ethereum protocol
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
argo-cd - Declarative Continuous Deployment for Kubernetes
Thingspeak - ThingSpeak is an open source “Internet of Things” application and API to store and retrieve data from things using HTTP over the Internet or via a Local Area Network. With ThingSpeak, you can create sensor logging applications, location tracking applications, and a social network of things with status updates.
prometheus - The Prometheus monitoring system and time series database.
uptime-kuma - A fancy self-hosted monitoring tool