stanza
jaeger
stanza | jaeger | |
---|---|---|
8 | 94 | |
177 | 19,544 | |
1.1% | 1.1% | |
6.6 | 9.7 | |
21 days ago | 1 day 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.
stanza
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Fluentd vs Promtail with Loki
Been a while since I looked into fluentd and elasticsearch but I heard Stanza (soon to be moved to the OpenTelemetry Collector) is meant to be a modern replacement for it, but seems it's still in it's early days.
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Cats and Clouds – There Are No Pillars in Observability with Yoshi Yamaguchi
And then they contacted some famous log collection projects such as the Fluent Bit and also others like Stanza as well as Syslog, I guess. And I didn't read the whole thread of the conversation around log collection. But now, they set the Stanza as the first implementation of OpenTelemetry logs. And in Stanza, the observIQ with Stanza is merged under the OpenTelemetry log repository, so that's the status. And then, they try to standardize the format of logs based on the Stanza format, such as what kind of information should be included in log.
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Syslog Server Recommendations
observIQ is a hosted log management platform that's powered by our FOSS log agent, Stanza: https://github.com/observIQ/stanza. Stanza is lightweight and robust (written in Go), and can be configured to act as a Syslog receiver in about a minute (guided configuration in our app).
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Monthly 'Shameless Self Promotion' thread - 2021/08
observIQ is a simple, cost-effective hosted log management platform designed with small teams in-mind. Log collection is powered by Stanza: https://github.com/observIQ/stanza , our high-performance OSS log agent. Stanza was also recently adopted as the official log agent of the CNCF's OpenTelemetry project. observIQ offers guided-installation, pre-made dashboards, threshold-based alerts, live tail and more.
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Logforwarding with syslog - namespace included
We're a new hosted log management platform with simple, native support for gathering logs from Openshift. Deployment typically takes a few minutes. We also automatically enrich Openshift logs metadata like node, namespace, pod, container - no additional configuration required. Logs are gathered with your high-performance OSS log agent, Stanza: https://github.com/observIQ/stanza
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Recommendations for syslog servers with web GUI wanted
We offer a super simple, hosted log management platform that allows you to easily ingest any syslog traffic by setting up high-speed OSS agent as a syslog receiver in just a few click (setup takes about 30 seconds). You can find more about our log agent here: https://github.com/observIQ/stanza
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Log management solution
Self-promotion alert, my apologies: Check us out at observIQ: https://observiq.com/ We provide a super-simple host log management platform powered our high-performance OSS Log Agent, Stanza (https://github.com/observIQ/stanza). Average setup time is about 5 minutes, end-to-end. Our platform is designed with start-ups and small businesses in-mind and are priced about half as much as our competitors. Lastly, we offer 14-day free trial, but also offer a completely free plan that provides 3 gigs of ingestion/day and 3 day retention - with access to the full feature set of the platform (Dashboards, Alerts, Live Tail). Shoot me a message or chat if you have any questions!
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With advancement of tools such as Sentry, do logs serve any purpose?
Similarly, our platform will be rolling out this feature soon, and will utilize our lightweight FOSS log agent Stanza - written in Go. The agent may work for your project https://github.com/observIQ/stanza
jaeger
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Observability with OpenTelemetry, Jaeger and Rails
Jaeger maps the flow of requests and data as they traverse a distributed system. These requests may make calls to multiple services, which may introduce their own delays or errors. https://www.jaegertracing.io/
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Show HN: An open source performance monitoring tool
As engineers at past startups, we often had to debug slow queries, poor load times, inconsistent errors, etc... While tools like Jaegar [2] helped us inspect server-side performance, we had no way to tie user events to the traces we were inspecting. In other words, although we had an idea of what API route was slow, there wasn’t much visibility into the actual bottleneck.
This is where our performance product comes in: we’re rethinking a tracing/performance tool that focuses on bridging the gap between the client and server.
What’s unique about our approach is that we lean heavily into creating traces from the frontend. For example, if you’re using our Next.js SDK, we automatically connect browser HTTP requests with server-side code execution, all from the perspective of a user. We find this much more powerful because you can understand what part of your frontend codebase causes a given trace to occur. There’s an example here [3].
From an instrumentation perspective, we’ve built our SDKs on-top of OTel, so you can create custom spans to expand highlight-created traces in server routes that will transparently roll up into the flame graph you see in our UI. You can also send us raw OTel traces and manually set up the client-server connection if you want. [4] Here’s an example of what a trace looks like with a database integration using our Golang GORM SDK, triggered by a frontend GraphQL query [5] [6].
In terms of how it's built, we continue to rely heavily on ClickHouse as our time-series storage engine. Given that traces require that we also query based on an ID for specific groups of spans (more akin to an OLTP db), we’ve leveraged the power of CH materialized views to make these operations efficient (described here [7]).
To try it out, you can spin up the project with our self hosted docs [8] or use our cloud offering at app.highlight.io. The entire stack runs in docker via a compose file, including an OpenTelemetry collector for data ingestion. You’ll need to point your SDK to export data to it by setting the relevant OTLP endpoint configuration (ie. environment variable OTEL_EXPORTER_OTLP_LOGS_ENDPOINT [9]).
Overall, we’d really appreciate feedback on what we’re building here. We’re also all ears if anyone has opinions on what they’d like to see in a product like this!
[1] https://github.com/highlight/highlight/blob/main/LICENSE
[2] https://www.jaegertracing.io
[3] https://app.highlight.io/1383/sessions/COu90Th4Qc3PVYTXbx9Xe...
[4] https://www.highlight.io/docs/getting-started/native-opentel...
[5] https://static.highlight.io/assets/docs/gorm.png
[6] https://github.com/highlight/highlight/blob/1fc9487a676409f1...
[7] https://highlight.io/blog/clickhouse-materialized-views
[8] https://www.highlight.io/docs/getting-started/self-host/self...
[9] https://opentelemetry.io/docs/concepts/sdk-configuration/otl...
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Kubernetes Ingress Visibility
For the request following, something like jeager https://www.jaegertracing.io/, because you are talking more about tracing than necessarily logging. For just monitoring, https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack would be the starting point, then it depends. Nginx gives metrics out of the box, then you can pull in the dashboard like https://grafana.com/grafana/dashboards/14314-kubernetes-nginx-ingress-controller-nextgen-devops-nirvana/ , or full metal with something like service mesh monitoring which would provably fulfil most of the requirements
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Migrating to OpenTelemetry
Have you checked out Jaeger [1]? It is lightweight enough for a personal project, but featureful enough to really help "turn on the lightbulb" with other engineers to show them the difference between logging/monitoring and tracing.
[1] https://www.jaegertracing.io/
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The Road to GraphQL At Enterprise Scale
From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.
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OpenTelemetry Exporters - Types and Configuration Steps
Jaeger is an open-source, distributed tracing system that monitors and troubleshoots the flow of requests through complex, microservices-based applications, providing a comprehensive view of system interactions.
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Fault Tolerance in Distributed Systems: Strategies and Case Studies
However, ensuring fault tolerance in distributed systems is not at all easy. These systems are complex, with multiple nodes or components working together. A failure in one node can cascade across the system if not addressed timely. Moreover, the inherently distributed nature of these systems can make it challenging to pinpoint the exact location and cause of fault - that is why modern systems rely heavily on distributed tracing solutions pioneered by Google Dapper and widely available now in Jaeger and OpenTracing. But still, understanding and implementing fault tolerance becomes not just about addressing the failure but predicting and mitigating potential risks before they escalate.
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Observability in Action Part 3: Enhancing Your Codebase with OpenTelemetry
In this article, we'll use HoneyComb.io as our tracing backend. While there are other tools in the market, some of which can be run on your local machine (e.g., Jaeger), I chose HoneyComb because of their complementary tools that offer improved monitoring of the service and insights into its behavior.
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Building for Failure
The best way to do this, is with the help of tracing tools such as paid tools such as Honeycomb, or your own instance of the open source Jaeger offering, or perhaps Encore's built in tracing system.
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Distributed Tracing and OpenTelemetry Guide
In this example, I will create 3 Node.js services (shipping, notification, and courier) using Amplication, add traces to all services, and show how to analyze trace data using Jaeger.
What are some alternatives?
fluent-bit - Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows
Sentry - Developer-first error tracking and performance monitoring
raider - DEPRECATED, please use the new repository from OWASP: https://github.com/OWASP/raider
skywalking - APM, Application Performance Monitoring System
loki - Like Prometheus, but for logs.
prometheus - The Prometheus monitoring system and time series database.
SquadJS - Squad Server Script Framework
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
helm-charts - Helm charts for Vector.
Pinpoint - APM, (Application Performance Management) tool for large-scale distributed systems.
opentracing-javascript - OpenTracing API for Javascript (both Node and browser). 🛑 This library is DEPRECATED! https://github.com/opentracing/specification/issues/163