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Simplify readme (#10205)

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# Abstract
**SkyWalking** is an open source APM system, including monitoring, tracing, diagnosing capabilities for distributed system
in Cloud Native architecture.
The core features are following.
- Service, service instance, endpoint(URI) metrics analysis.
- Distributed tracing.
- Metrics collecting, analysis, and customization.
- Logging collecting and extracting metrics from them.
- Distributed tracing and context propagation.
- Collaboration across metrics, traces, and logs
- Root cause analysis.
- Profile the code on the runtime powered by in-process agent and ebpf profiler.
- Network profiler for TCP, TCP/TLS, HTTP(s) traffic.
- Service topology map analysis.
- Service instance and endpoint(URI) dependency analysis.
- Slow services and endpoints detecting.
- Performance optimization.
- In memory and remote cache performance monitoring, including Read and Write performance. Detect slow Cache access with keys.
- Database performance monitoring. Detect slow SQL statements.
- Message Queue performance and consuming latency monitoring.
- Browser performance monitoring, and start tracing from browser.
- Infrastructure monitoring. Kubernetes and Linux(VM, network, disk etc.).
- Alerting.
<img src="https://skywalking.apache.org/images/home/architecture.svg?t=20220513"/>
* Distributed Tracing
* End-to-end distributed tracing. Service topology analysis, service-centric observability and APIs dashboards.
* Agents for your stack
* Java, .Net Core, PHP, NodeJS, Golang, LUA, Rust, C++, Client JavaScript and Python agents with active development and maintenance.
* eBPF early adoption
* Rover agent works as metrics collector and profiler powered by eBPF to diagnose CPU and network performance.
* Scaling
* 100+ billion telemetry data could be collected and analyzed from one SkyWalking cluster.
* Mature Telemetry Ecosystems Supported
* Metrics, Traces, and Logs from mature ecosystems are supported, e.g. Zipkin, OpenTelemetry, Prometheus, Zabbix, Fluentd
* Native APM Database
* BanyanDB, an observability database, created in 2022, aims to ingest, analyze and store telemetry/observability data.
* Consistent Metrics Aggregation
* SkyWalking native meter format and widely known metrics format(OpenCensus, OTLP, Telegraf, Zabbix, e.g.) are processed through the same script pipeline.
* Log Management Pipeline
* Support log formatting, extract metrics, various sampling policies through script pipeline in high performance.
* Alerting and Telemetry Pipelines
* Support service-centric, deployment-centric, API-centric alarm rule setting. Support forwarding alarms and all telemetry data to 3rd party.
SkyWalking supports to collect telemetry (metrics, traces, and logs) data from multiple sources
and multiple formats, including
1. Java, .NET Core, NodeJS, PHP, and Python auto-instrument agents.
2. Go, C++, and Rust SDKs.
3. [Agent profiling](https://skywalking.apache.org/docs/main/next/en/concepts-and-designs/sdk-profiling/) for Java and Python.
4. [ebpf](https://github.com/apache/skywalking-rover) network profiling and ON/OFF CPU profiling.
5. LUA agent especially for Nginx, OpenResty and Apache APISIX.
6. Browser agent.
7. Service Mesh Observability. Control plane and data plane.
8. Metrics system, including Prometheus, OpenTelemetry, Micrometer(Spring Sleuth), Zabbix.
9. Logs, including OpenTelemetry.
10. Zipkin v1/v2 trace.(No Analysis).
<img src="https://skywalking.apache.org/images/home/architecture.svg?t=20220513"/>
# Documentation
- [Official documentation](https://skywalking.apache.org/docs/#SkyWalking)
SkyWalking OAP is using the STAM(Streaming Topology Analysis Method) to analysis topology in the tracing based agent scenario
for better performance. Read [the paper of STAM](https://wu-sheng.github.io/STAM/) for more details.
# Downloads
Please head to the [releases page](https://skywalking.apache.org/downloads/) to download a release of Apache SkyWalking.
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