Jetty VS opentelemetry-collector-contrib

The session logs show that the application loads configurations and establishes a connection with a PostgreSQL database. This involves initializing a HikariCP connection pool and Flyway for database migrations. The logs confirm that the database schema validation and migration checks were successful. The startup of the Jetty HTTP server follows, and the server becomes operational and ready to accept requests on the specified port.

As described on eclipse.dev/jetty: "Jetty provides a web server and servlet container, additionally providing support for HTTP/2, WebSocket, OSGi, JMX, JNDI, JAAS and many other integrations. These components are open source and are freely available for commercial use and distribution."

Manual instrumentation allows you to define your Spans within the code itself rather than relying on automatic instrumentation finding the entry point for a trace. Manual instrumentation is especially helpful for applications that don’t use an application server such as Tomcat, JBoss, or Jetty.

So, 9.4.48 fixes the first two CVEs, but the last one doesn't mention 9.4 at all, so I'm not sure if that's left out due to EOL status for 9.4.

Fresh off the press: https://github.com/eclipse/jetty.project/issues/8007

If you're doing something pretty simple and need something really lighweight, however, you could go with something like Javalin or even use Jetty directly (the HTTP server which powers Javalin and many other frameworks by default). It's not that hard to do that and that's what I actually would do myself for almost everything... the fewer moving parts you have in your application, the better chances you have of keeping everything up-to-date and the less chance to mess up (with a caveat: bigger frameworks may give you secure defaults that if you're not experienced enough you may not even know about, so it may be better to not go low level if you're new-ish to running web applications securely).

Example: Little Johnny was developing a Java web app and thinking about how he would configure Tomcat to listen to requests and redirect the data into his app... until he remembered this would violate Factor 7! Instead, he decided to declare Jetty as a dependency, keeping the HTTP service inside the app instead of configuring an external web server and then injecting its functionalities. Now, whenever he wants to instantiate another server for this app, all he has to do is installing dependencies and running the app, isn't it convenient?

Hi /r/java! Jetty is considering implementing dynamic Brotli compression, but the current JVM wrapper for Google's Brotli (jvm-brotli) is somewhat ... abandoned.

Multiple applications in the same JVM? Wildfly, Tomcat, Jetty.

you can add https://github.com/open-telemetry/opentelemetry-collector-co... at signoz's otel-collector which will scrape your service's endpoint periodically. If your service is down, this will give 5xx error and you can set an alert on that.

Another alternative is to use an alert to notify on a metric being absent for sometime. Both of these should work

The open telemetry collector does just that. https://github.com/open-telemetry/opentelemetry-collector-co...

There are two official distributions of the OpenTelemetry Collector: Core, and Contrib.

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.

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.

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...

A list of all metric definitions can be found here.

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]

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...