commit | 7f371ed5650262c5c5837f1a6a1d504969393be7 | [log] [tgz] |
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author | 吴晟 Wu Sheng <wu.sheng@foxmail.com> | Mon Aug 08 19:38:58 2022 +0800 |
committer | GitHub <noreply@github.com> | Mon Aug 08 19:38:58 2022 +0800 |
tree | c1d163dfff53dfc3052b17441e7cc20890efa183 | |
parent | fedc20991d1cae2d89741dce5788e2042da639c6 [diff] |
[Critical] Fix a low performance issue of metrics persistent in ES (#9437) [Critical] Fix a low-performance issue of metrics persistent in the ElasticSearch storage implementation. One single metric could have to wait for an unnecessary 7~10s(System Env Variable SW_STORAGE_ES_FLUSH_INTERVAL). This is a solid and critical performance issue, from the self-observability metric, we could find one metric that would need 7-10s to execute the data flush, which is not expected.
SkyWalking: an APM(application performance monitor) system, especially designed for microservices, cloud native and container-based architectures.
SkyWalking is an open source APM system, including monitoring, tracing, diagnosing capabilities for distributed system in Cloud Native architecture. The core features are following.
SkyWalking supports to collect telemetry (metrics, traces, and logs) data from multiple sources and multiple formats, including
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 for more details.
NOTICE, SkyWalking 8.0+ uses v3 protocols. They are incompatible with previous releases.
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