opentelemetry-collector-contrib
logs-benchmark
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opentelemetry-collector-contrib | logs-benchmark | |
---|---|---|
43 | 11 | |
2,546 | 75 | |
5.8% | - | |
10.0 | 10.0 | |
5 days ago | over 1 year ago | |
Go | Shell | |
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-contrib
- OpenTelemetry at Scale: what buffer we can use at the behind to buffer the data?
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All you need is Wide Events, not "Metrics, Logs and Traces"
The open telemetry collector does just that. https://github.com/open-telemetry/opentelemetry-collector-co...
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OpenTelemetry Collector Anti-Patterns
There are two official distributions of the OpenTelemetry Collector: Core, and Contrib.
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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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Spotlight: Sentry for Development
Thanks for the reply. Would the Spotlight sidecar possibly be able to run independently and consume spans emitted by the Sentry exporter[0] or some other similar flow beyond strictly exporting directly from the Sentry SDK provided by Spotlight?
This tooling looks really cool and I'd love to play around with it, but am already pretty entrenched into OTel and funneling data through the collector and don't want to introduce too much additional overhead for devs.
[0] https://github.com/open-telemetry/opentelemetry-collector-co...
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Amazon EKS Monitoring with OpenTelemetry [Step By Step Guide]
A list of all metric definitions can be found here.
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Spring Boot Monitoring with Open-Source Tools
receivers: otlp: protocols: grpc: endpoint: 0.0.0.0:4317 http: endpoint: 0.0.0.0:4318 hostmetrics: collection_interval: 60s scrapers: cpu: {} disk: {} load: {} filesystem: {} memory: {} network: {} paging: {} process: mute_process_name_error: true mute_process_exe_error: true mute_process_io_error: true processes: {} prometheus: config: global: scrape_interval: 60s scrape_configs: - job_name: otel-collector-binary scrape_interval: 60s static_configs: - targets: ["localhost:8889>"] - job_name: "jvm-metrics" scrape_interval: 10s metrics_path: "/actuator/prometheus" static_configs: - targets: ["localhost:8090>"] processors: batch: send_batch_size: 1000 timeout: 10s # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md resourcedetection: detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure. # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels. timeout: 2s system: hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback extensions: health_check: {} zpages: {} exporters: otlp: endpoint: "ingest.{region}.signoz.cloud:443" tls: insecure: false headers: "signoz-access-token": logging: verbosity: normal service: telemetry: metrics: address: 0.0.0.0:8888 extensions: [health_check, zpages] pipelines: metrics: receivers: [otlp] processors: [batch] exporters: [otlp] metrics/internal: receivers: [prometheus, hostmetrics] processors: [resourcedetection, batch] exporters: [otlp] traces: receivers: [otlp] processors: [batch] exporters: [otlp] logs: receivers: [otlp] processors: [batch] exporters: [otlp]
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Migrating to OpenTelemetry
If you are using the prometheus exporter, you can use the transform processor to get specific resource attributes into metric labels.
With the advantage that you get only the specific attributes you want, thus avoiding a cardinality explosion.
https://github.com/open-telemetry/opentelemetry-collector-co...
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Exploring the OpenTelemetry Collector
OpenTelemetry Operators
logs-benchmark
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OpenObserve: Elasticsearch/Datadog alternative in Rust.. 140x lower storage cost
I am a maintainer at SigNoz. Nice to see OpenObserve's belief that the future of Observability should be OpenSource. We chose clickhouse rather than building a database as it takes multi-year effort to move a db to maturity and clickhouse has been battle-tested at Yandex, Uber and Cloudflare. Clickhouse also provides native integration with s3 and other blob storages. Our users have been using disk as hot storage for a week and moving the data to s3 after that. Tiered storage is really cool in terms of query performance.
We have also seen logs data of our users at a compression ratio of 30x/40x. We have published a logs benchmark (https://github.com/SigNoz/logs-benchmark) where the data is very high-cardinal (causing a compression factor of only 2.5x). Would love to see how does OpenObserve perform in that dataset someday.
Wishing you best for the journey ahead.
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Elastic vs Loki vs SigNoz : A Performance Benchmark of self hosted & open source logging platforms
Did you update the benchmark after you got feedback from this user at Hacker News or after you got the feedback that including Loki here is kinda pointless?
- Elastic vs Loki vs SigNoz : A Perf Benchmark of open source logging platforms
- FLiP Stack Weekly 28 Jan 2023
- FLiP Stack Weekly 28-Jan-2023
- Elastic, Loki and SigNoz – A Perf Benchmark of Open-Source Logging Platforms
What are some alternatives?
uptrace - Open source APM: OpenTelemetry traces, metrics, and logs
opentelemetry-collector-co
cockpit-podman - Cockpit UI for podman containers
openobserve - 🚀 10x easier, 🚀 140x lower storage cost, 🚀 high performance, 🚀 petabyte scale - Elasticsearch/Splunk/Datadog alternative for 🚀 (logs, metrics, traces, RUM, Error tracking, Session replay).
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
carbonyl - Chromium running inside your terminal
podman-compose - a script to run docker-compose.yml using podman
shite - The little hot-reloadin' static site maker from shell.
traefik - The Cloud Native Application Proxy
clamshell - experimenting with a python based shell
serilog-sinks-seq - A Serilog sink that writes events to the Seq structured log server
FLiPN-Py-Stocks - finnhub stocks