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Method and system for collecting log on edge node of kubeedge
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A log and node technology, applied in the direction of transmission system, file system, file system type, etc., to achieve the effect of ensuring continuity and persistence
Inactive Publication Date: 2021-06-11
SHANDONG LANGCHAO YUNTOU INFORMATION TECH CO LTD
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This brings new challenges, that is, if the kubeedge node continues to roll and collect the log logs of the edge node when the kubeedge node is self-made, and when the kubeedge node is connected to the kubernetes cluster again, the log received when the kubeedge node is connected to the kubernetes cluster is uploaded to E (ElasticSearch) through K( Kibana) show
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Embodiment 1
[0047] A method for collecting logs on an edge node of kubeedge, the method specifically comprising:
[0048] S1 runs the log agent on the edge node to save the log of the edge node after self-made;
[0049] The container class that collects and records logs for S2 times is named log-agent;
[0050] S3log-agent submits all the logs collected by kubeedge to the backend Elasticsearch;
[0051] When the S4kubedge node is self-made, the edge node collects error logs;
[0052] When the Kubeedge node is self-made, it will not save, persist, or display log logs. When using the method of the present invention, firstly, after the Kubeedge node is self-made, kubernets runs a node-level log agent on the edge node to save the logs of the self-made Edge node. The container class that collects and records logs for the first time is named log-agent. The second container can save all container logs on all edge nodes after the edge node is self-made. Therefore, log-agent must run on each edg...
Embodiment 2
[0070] A system for collecting logs on edge nodes of kubeedge, the system specifically includes a log storage module, a log naming module, a log delivery module, and a log feedback module:
[0071] Log saving module: run the log agent on the edge node to save the log of the edge node after self-made;
[0072] Log naming module: the container class that collects and records logs for the first time is named log-agent;
[0073] Log submission module: log-agent submits all logs collected by kubeedge self-made to Elasticsearch at the back end;
[0074] Log feedback module: The edge node collects error logs when the kubedge node is self-made.
[0075] Further, the log submission module specifically includes an operation module A, a collection module A and an upload module A:
[0076] Run the module: run the log collection service on the Kubeedge node;
[0077] Collection module A: save and collect logs on the Kubeedge node when it is self-made;
[0078] Upload module A: Upload l...
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Abstract
The invention discloses a method and a system for collecting a log on an edge node of a kubeedge, and belongs to the field of kubernetes. The method specifically comprises the following steps: S1, operating a log agent at an edge node to store a log of a self-made Edge node; S2, collecting and recording a container class name of the log for the second time as a log-agent; S3, using the log-agent for sending the logs collected by all the kubeded from the system to the Elasticsearch at the rear end in a lifting mode, S4, collecting error logs by an edge node when the kubedge node is self-made; according to the mode realized by the invention, the log can be continuously collected after the kubeard node is self-made, and the collected log is uploaded to the E (ElasticSearch) when the kubeard node is accessed to the kubeards cluster again, so that the continuity and persistence of the kubeard log are ensured.
Description
technical field [0001] The invention discloses a method and system for collecting logs on an edge node of kubeedge, and relates to the technical field of kubernetes. Background technique [0002] Kubeedge self-made and independently collects logs and uploads logs after connecting to the kubernetes cluster: it is a software architecture technology that realizes how to continue to collect logs after the edge is offline and self-made, and upload the saved logs to the kubernetes cluster after reconnecting to the kubernetes cluster E (Elasticsearch) is displayed through K (Kibana). [0003] Elasticsearch is a distributed, highly scalable, high real-time search and data analysis engine. It can easily enable large amounts of data to be searched, analyzed and explored. Taking full advantage of the horizontal scalability of Elasticsearch can make data more valuable in the production environment. [0004] Kibana is a web interface for log analysis provided by Logstash and ElasticSe...
Claims
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