Apache Tomcat VS opentelemetry-collector-contrib

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.

99% is a huge exaggeration. Two essential deployment tools off the top of my head: https://tomcat.apache.org/ https://docs.jboss.org/author/display/AS71/Developer%20Guide.html

To download, enter the Apache website in the address bar: http://tomcat.apache.org/

Do we still enjoy it? We are running many Vaadin apps in production since that first one. If there are not any specific requirements we use a “modular monolith” concept, which fits our stack best. We pack applications as WAR and deploy them under Apache Tomcat. And yes, we enjoy the development process. It’s very straightforward and Vaadin and SpringBoot fit together well.

JasperReports Server Community requires a Java application server and a database to create a repository in order to work properly. After downloading JRS, the installation process can install Tomcat server and PostgreSQL database automatically for us and the services will run depending on the Jasper server. It's also possible to connect JRS to services already installed on the server. Moreover, while the free version supports the MySQL server, with the paid version you can also use commercial databases, for example, ORACLE Database, as a data repository.

Regarding the venerable Tomcat, they [somewhat] recently added support for Unix domain sockets.

* https://github.com/apache/tomcat/pull/402

* https://github.com/apache/tomcat/pull/532

We fronted the server with haproxy LTS. Our initial testing showed roughly and order of magnitude [10x] increase in the number of requests the server could handle.

It's not completely plug-and-play; we still had a write a custom valve to set the request remote ip address and some other TCPish stuff, but nevertheless the capacity far outstripped our need for the technology.

Official Website :- https://tomcat.apache.org/

Don't use an installed copy of Tomcat. The layout can be different than expected and permission problems can appear at the worst time. For one, it needs to be able to write to that conf directory. Download a non-platform-specific "core" zip file from tomcat.apache.org instead.

Anytime you use dependencies you make use of code for a purpose that was not originally intended. The apachee web server was named after a patchwork quilt. Many contributors had useful code from commercial projects they contributed to the cause. In networking protocols packets are discarded after a set number of hops, or an expiration date so the internet does not have zombie packets wondering around. The tcp/ip traceroute command uses TTL to find all the collision domains in a request.

If you plan on a full enterprise solution apache server has built in roles, users and corporate tools. It integrates well with Java. Express is much easier in my opinion. You may use xml instead of json. Other than that the front end and backend don't matter. Since ERP is what you are dealing with maybe that is the way to go?

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...

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