Search Results for "ns-2"

As on-the-ground microservice practitioners are quickly realizing, the majority of operational problems that arise when moving to a distributed architecture are ultimately grounded in two areas: networking and observability. It is simply an orders of magnitude larger problem to network and debug a set of intertwined distributed services versus a single monolithic application. Jaeger, inspired by Dapper and OpenZipkin, is a distributed tracing system released as open source by Uber Technologies. It is used for monitoring and troubleshooting microservices-based distributed systems. ...

...It is very simple and easy to operate as opposed to Elasticsearch which requires a couple of dozen knobs to understand and tune which you can get up and running in under 2 minutes. It is a drop-in replacement for Elasticsearch if you are just ingesting data using APIs and searching using Kibana (Kibana is not supported nor required with OpenObserve. OpenObserve provides its own UI which does not require separate installation unlike Kibana). You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. ...

Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts...

Envoy is an open source, high-performance edge/middle/service proxy designed for cloud-native applications. It was built by Lyft to solve the common problem of networking and observability when moving to a distributed architecture. Envoy is a proxy designed for single services and applications. Aside from that it is also a communication bus and “universal data plane” designed for large microservice “service mesh” architectures. It runs right along with every application, and abstracts the...

...Pixie uses eBPF to automatically collect telemetry data such as full-body requests, resource and network metrics, application profiles, and more. Pixie collects, stores and queries all telemetry data locally in the cluster. Pixie uses less than 5% of cluster CPU and in most cases less than 2%. PxL, Pixie’s flexible Pythonic query language, can be used across Pixie’s UI, CLI, and client APIs.

...Thirty-nine probes read the machine (hardware, storage and SMART, Windows, network) and one hundred and forty-nine rules turn that into plain sentences. A quick pass takes ten seconds, a full one takes two to four minutes. It then writes three documents: a detailed technician report, a jargon-free summary for the customer, and a JSON snapshot so two visits can be compared. One rule decided the rest: never state what was not measured. A value that could not be read is shown as missing, with the reason. A check that could not run is excluded from the score instead of lowering it. ...