WMO information system 2.0 global meteorological data exchange monitoring method and device

Abstract

The invention discloses a WMO information system 2.0 global meteorological data exchange monitoring method and device. The WMO information system 2.0 global meteorological data exchange monitoring method comprises the following steps: automatically capturing a latest Metric index file from an end point of each GS regularly based on Prometheus, and storing the captured Metric index file in a local time sequence database; making an alarm rule according to the WMO, and evaluating the Metric index file based on a rule engine technology to obtain alarm information; according to the method, Grafana is used for carrying out visualized presentation on a Metric index file collected by Prometheus, so that display and analysis of each monitoring index of the GS are realized. According to the invention, the GS capability and the data exchange quality of the WIS2.0 can be guaranteed.

Description

Technical Field

[0001] This application relates to the technical field of meteorological data monitoring, and particularly to a method and device for monitoring global meteorological data exchange in the WMO Information System 2.0. Background Art

[0002] In February 2022, the WMO Secretariat determined four global services (GS) of WIS2.0: The Global Bulletin Hub (GB) is responsible for collecting and forwarding notification messages of data releases in real time, providing message notification services for global data exchange; The Global Discovery Catalog (GDC) is responsible for collecting metadata in real time and publishing a data catalog, providing data discovery services based on metadata catalog navigation and retrieval; The Global Cache (GC) is responsible for collecting and aggregating global data in real time and providing data sharing services; The Global Monitoring (GM) is responsible for monitoring global data exchange services and global data quality. The WIS2 node is responsible for publishing data / metadata, and during the transition from GTS to WIS2.0, provides the WIS2-GTS Gateway (WG) and the GTS-WIS2 Gateway (GW).

[0003] In related technologies, in 2024, each GS of WIS2.0 completed the functional and performance tests organized by the WMO, and global business operations began in 2025. Therefore, real-time monitoring of global data exchange capabilities is essential. However, there is currently a lack of a monitoring method for global data exchange capabilities.

[0004] Therefore, it is necessary to design a method and device for monitoring global meteorological data exchange in the WMO Information System 2.0 to overcome the above problems. Summary of the Invention

[0005] This application provides a method and device for monitoring global meteorological data exchange in the WMO Information System 2.0, which can solve the technical problem of the lack of a monitoring method for global data exchange capabilities in related technologies.

[0006] In a first aspect, an embodiment of this application provides a method for monitoring global meteorological data exchange in the WMO Information System 2.0. The method for monitoring global meteorological data exchange in the WMO Information System 2.0 includes: Automatically scrape the latest Metrics metric files from the endpoints of each GS at regular intervals based on Prometheus, and store the scraped Metrics metric files in a local time series database; Formulate alarm rules according to the WMO, and evaluate the Metrics metric files based on rule engine technology to obtain alarm information; Use Grafana to visually present the Metrics metric files collected by Prometheus, and realize the display and analysis of each monitoring index of the GS.

[0007] In combination with the first aspect, in one implementation, before automatically scraping the latest Metrics metric files from the endpoints of each GS at regular intervals based on Prometheus, it further includes: All GSs generate Metrics metric files based on the Openmetrics specification.

[0008] In combination with the first aspect, in one implementation, all GSs include: GB, GDC, GC, GM, WIS2-GTS gateway, and GTS-WIS2 gateway.

[0009] In combination with the first aspect, in one implementation, there are 41 items of Metrics metric files generated by each GS. The Metrics metric files carry extended labels, and the labels are used for classification as data basis; among them, GB generates 7 items of Metrics metric files, and each Metrics metric file carries 2 labels; GDC generates 12 items of Metrics metric files, and each Metrics metric file carries 1 - 3 labels; GC generates 8 items of Metrics metric files, and each Metrics metric file carries 2 - 3 labels; GM generates 2 items of Metrics metric files, and each Metrics metric file carries 2 labels; GTS-WIS2 gateway generates 4 items of Metrics metric files, and each Metrics metric file carries 2 labels; WIS2-GTS gateway generates 8 items of Metrics metric files, and each Metrics metric file carries 2 - 3 labels.

[0010] In combination with the first aspect, in one implementation, the Metrics metric files are divided into three major categories, including connection status metrics, performance metrics, and exception information metrics.

[0011] In combination with the first aspect, in one implementation, the alarm rules include alarm name, alarm condition, alarm level, and alarm description.

[0012] In combination with the first aspect, in one implementation, all alarm information generated by GSs is published / subscribed through MQTT. Each GS runs an MQTT-based agent. When an alarm event is detected, all GSs publish alarm notification messages to their local agents. GB subscribes to all GSs to obtain alarm event notification messages, and GM subscribes to multiple alarm messages to receive alarm information from all GSs; among them, the alarm information includes both a topic structure and a message body; the first three layers of the topic structure use monitor / a / wis2, the publisher of the alarm is the fourth layer of the topic structure, and the alarm target is the fifth layer.

[0013] In combination with the first aspect, in one implementation, the alarm information includes an ID, a producer, an event source, a format, an alarm level, and content; wherein, the alarm levels include "info", "warning", "error", and "critical", and the levels increase one by one. When the alarm level is "critical", in addition to sending a notification message, the alarm information is also sent to the IMS.

[0014] In combination with the first aspect, in one implementation, the use of Grafana to visually present the Metrics metric files collected by Prometheus realizes the display and analysis of various monitoring metrics of GS, including: Based on different plotting techniques such as Time series, Bar chart, Stat, Gauge, State timeline, and Bar gauge, and multiple functions such as increase, delta, sort_desc, and topk, multiple types of visual monitoring page displays are provided; among them, the visual monitoring page display includes the WIS2 node perspective, the GISC perspective, and the Global Service perspective.

[0015] In a second aspect, an embodiment of the present application provides a WMO information system 2.0 global meteorological data exchange monitoring device, and the WMO information system 2.0 global meteorological data exchange monitoring device includes: A scraping module, which is used to automatically scrape the latest Metrics metric files from the endpoints of each GS at regular intervals based on Prometheus, and store the scraped Metrics metric files in a local time series database; An alarm module, which is used to formulate alarm rules according to WMO, and based on the rule engine technology, evaluate the Metrics metric files to obtain alarm information; A display module, which is used to visually present the Metrics metric files collected by Prometheus using Grafana, and realize the display and analysis of various monitoring metrics of GS.

[0016] The beneficial effects brought by the technical solutions provided by the embodiments of the present application include: By automatically fetching the latest Metrics metric files from the endpoints of each GS at regular intervals, the Metrics metric files can be evaluated according to the alarm rules to obtain alarm information, and Grafana can be used for visual presentation to ensure the stable operation of WIS2.0, monitor the connectivity, availability, and response time of each GS in WIS2.0, identify problems in the GS or WIS2 nodes, guarantee the GS capabilities and data exchange quality of WIS2.0, and solve the technical problem of the lack of a monitoring method for global data exchange capabilities in the related technology. Brief Description of the Drawings

[0017] Figure 1 It is a schematic flowchart of an embodiment of the WMO information system 2.0 global meteorological data exchange monitoring method of the present application; Figure 2 It is an architecture diagram of the WMO information system 2.0 global meteorological data exchange monitoring of the present application; Figure 3 It is a flowchart of sending an alarm for the WMO information system 2.0 global meteorological data exchange monitoring of the present application. Detailed Embodiment

[0018] In order to enable those skilled in the art of this technology to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0019] First, some technical terms in the present application are explained to facilitate the understanding of the present application by those skilled in the art.

[0020] WMO: World Meteorological Organization, that is, the World Meteorological Organization.

[0021] "WIS2.0": WMO Information System version 2.0, that is, WMO information system 2.0.

[0022] "GS": Global services, that is, global services.

[0023] "GM": Global Monitor, that is, global monitoring.

[0024] "IMS": Incident Management System, that is, incident management system.

[0025] "GB": Global Broker, which is the global notification hub.

[0026] "GDC": Global Discovery Catalogue, which is the global discovery catalogue.

[0027] "GC": Global Cache, which is the global data cache.

[0028] "WG": WIS2-to-GTS Gateway, which is the WIS2-GTS gateway.

[0029] "GW": GTS-to-WIS2 Gateway, which is the GTS-WIS2 gateway.

[0030] "MQTT": Message Queuing Telemetry Transport, which is the Message Queuing Telemetry Transport protocol.

[0031] To make the objectives, technical solutions, and advantages of this application clearer, the following will further describe the embodiments of this application in detail in conjunction with the accompanying drawings.

[0032] In a first aspect, an embodiment of this application provides a method for monitoring global meteorological data exchange in the WMO Information System 2.0.

[0033] In one embodiment, with reference to Figure 1 , Figure 1 , which is a schematic flowchart of the first embodiment of the method for monitoring global meteorological data exchange in the WMO Information System 2.0 of this application. As Figure 1 shown, the method for monitoring global meteorological data exchange in the WMO Information System 2.0 includes: S1: Automatically scrape the latest Metrics metric files from the endpoints of each GS at regular intervals based on Prometheus, and store the scraped Metrics metric files in the local time series database.

[0034] S2: Formulate alarm rules according to WMO, and evaluate the Metrics metric files based on rule engine technology to obtain alarm information.

[0035] S3: Use Grafana to visually present the Metrics metric files collected by Prometheus to achieve the display and analysis of each monitoring metric of GS.

[0036] In this embodiment, before step S1, all GSs generate Metrics metric files (i.e., monitoring metric files) based on the Openmetrics specification. All GSs that generate Metrics metric files include: GB (Global Notification Hub), GDC (Global Discovery Catalog), GC (Global Data Cache), GM (Global Monitoring), WIS2-GTS Gateway (WG), and GTS-WIS2 Gateway (GW). In step S2, Prometheus Alert Manager is configured according to the WMO monitoring and alerting rules. Based on the rule engine technology, the definition of rules, data evaluation, alert triggering, and alert handling can be achieved, and it supports alerting in forms such as email and webhook, and can be docked with the MQTT component and IMS to achieve the publication of alert messages and automatic submission of problems in abnormal scenarios. The specific architecture is shown in Figure 2 the figure. The permission management that supports both RBAC and PBAC policies is adopted to ensure data security; based on technologies such as caching, data preprocessing, load balancing, and personalized panels, diverse real-time displays of the global monitoring system are realized, supporting concurrent access of 200 users per second. This method is first used for the availability evaluation of GSs, and in addition, it is used to monitor the included WIS2 nodes, so as to evaluate the availability of data and services from certain NCs to ensure that WIS2.0 works as expected; secondly, this method will monitor the availability of global exchange data to support different plans of the WMO.

[0037] In this embodiment, by automatically fetching the latest Metrics metric files from the endpoints of each GS at regular intervals, the Metrics metric files can be evaluated according to the alerting rules to obtain alert information, and Grafana can be used for visual presentation to ensure the stable operation of WIS2.0, monitor the connectivity, availability, and response time of each GS of WIS2.0, identify problems in GSs or WIS2 nodes, guarantee the GS capabilities and data exchange quality of WIS2.0, and solve the technical problem of lacking a monitoring method for global data exchange capabilities in the related art.

[0038] Moreover, the WMO information system 2.0 global meteorological data exchange monitoring method provided in this embodiment can guarantee the global data exchange mechanism, ensure that meteorological, climate, and water-related data can be shared more quickly and efficiently globally, and thus contribute to coordinating meteorological services in different countries and regions, promoting international cooperation, and jointly coping with climate change and extreme weather events.

[0039] Furthermore, in one embodiment, all GSs can generate 41 Metrics indicator files based on the Openmetrics specification. The Metrics indicator files can reflect the operating status and performance of the system in multiple dimensions. The Metrics indicator files are subdivided into three major categories, including connection status indicators, performance indicators, and exception information indicators. The detailed indicators and indicator descriptions are as follows: GB Metrics: –wmo_wis2_gb_messages_no_metadata_total • Number of messages received without corresponding metadata from centre – wmo_wis2_gb_messages_invalid_topic_total • Number of messages received on an invalid topic from centre – wmo_wis2_gb_messages_invalid_format_total • Number of invalid messages from centre – wmo_wis2_gb_messages_published_total • Number of messages published by broker – wmo_wis2_gb_messages_received_total • Number of messages received by broker – wmo_wis2_gb_connected_flag • Connection status from broker to centre – wmo_wis2_gb_last_messages_timestamp_seconds • Timestamp of last message received from center GC Metrics: – wmo_wis2_gc_downloaded_total • Number of data items downloaded to Global Cache – wmo_wis2_gc_downloaded_errors_total • Number of download errors for Global Cache data – wmo_wis2_gc_dataserver_status_flag • Status of WIS2 Node dataserver – wmo_wis2_gc_dataserver_last_download_timestamp_seconds • Timestamp of last successful download – wmo_wis2_gc_no_cache_total • Number of data objects that GC has been requested not to cache – wmo_wis2_gc_cache_override_total • Number of messages for which the GC overrides the download request – wmo_wis2_gc_integrity_failed_total • Number of messages for which the integrity check failed – wmo_wis2_gc_last_metadata_timestamp_seconds • Timestamp of last GDC metadata package resource processed GDC Metrics: wmo_wis2_gdc_passed_total • Number of metadata records passed validation – wmo_wis2_gdc_failed_total • Number of metadata records failed validation – wmo_wis2_gdc_core_total • Number of core metadata records – wmo_wis2_gdc_recommended_total • Number of recommended metadata records – wmo_wis2_gdc_kpi_percentage_total • KPI percentage for a single metadata records – wmo_wis2_gdc_kpi_percentage_average • Average KPI percentage wmo_wis2_gdc_kpi_percentage_over80_total • Number of metadata records with KPI percentage over 80 – wmo_wis2_gdc_search_total • Number of search requests – wmo_wis2_gdc_search_terms • Most popular search terms – wmo_wis2_gdc_connected_flag • Connection status from GDC to centre – wmo_wis2_gdc_downloaded_errors_total • Number of metadata download errors GM Metrics: – wmo_wis2_gm_metricserver_status_flag • Status of the metric endpoint for centre – wmo_wis2_gm_metricserver_last_scrape_timestamp_seconds • Timestamp of last successful metric scrape GTS-WIS2 Metrics: – wmo_wis2_gw_published_total • Number of messages published; grouped by GTS CCCC code – wmo_wis2_gw_gts_received_total • Number of messages received from GTS; grouped by GTS CCCC code (variance with wmo_wis2_gw_published_total indicates processing failure) – wmo_wis2_gw_published_errors_total • Number of errors occurring while processing messages received from GTS; grouped by GTS CCCC code – wmo_wis2_gw_gts_last_received_timestamp_seconds • Timestamp of most recent message received from GTS; grouped by GTS CCCC code WIS2-GTS Metrics: – wmo_wis2_wg_downloaded_total • Number of data items downloaded by the Gateway for republication on GTS – wmo_wis2_wg_messages_total • Number of unique messages received by the Gateway – wmo_wis2_wg_messages_gtsproperties_total • Number of unique messages containing GTS properties received by the Gateway – wmo_wis2_wg_downloaded_errors_total • Number of download errors encountered – wmo_wis2_wg_dataserver_status_flag • Status of WIS2 Node dataserver (1-up and 0-down) – wmo_wis2_wg_dataserver_last_download_timestamp_seconds • Timestamp of last successful download – wmo_wis2_wg_integrity_failed_total • Number of messages for which the integrity check failed – wmo_wis2_wg_messages_gtsproperties_invalid_format_total • Number of messages received with invalid GTS properties Further, in one embodiment, there are 41 Metrics index files generated by each GS. The Metrics index files carry extended tags, and the tags are used as data bases for classification. Among them, GB generates 7 Metrics index files, and each Metrics index file carries 2 tags; GDC generates 12 Metrics index files, and each Metrics index file carries 1 - 3 tags; GC generates 8 Metrics index files, and each Metrics index file carries 2 - 3 tags; GM generates 2 Metrics index files, and each Metrics index file carries 2 tags; GTS - WIS2 gateway generates 4 Metrics index files, and each Metrics index file carries 2 tags; WIS2 - GTS gateway generates 8 Metrics index files, and each Metrics index file carries 2 - 3 tags. In this embodiment, the alertmanager server can receive alert information and use the tags as data bases for classification.

[0040] In the above - mentioned embodiment, the Prometheus server saves the collected data in the time - series database, and the Prometheus server can maintain the PrometheusRule alert rules. The alert rules are uniformly scheduled and calculated by the Prometheus service. In addition to the necessary description information, the alert content can also carry some tag information. The text information is used for problem description, and the tag information is mainly used for alert information classification. When the Prometheus server triggers the alert rules, the alert information will be uniformly sent to the Alertmanager server. The Metrics of GB and the tag information it carries are as follows:

[0041] Based on the above - mentioned technical solution, in one embodiment, there are 17 alert rules, and the alert rules include alert name, alert condition, alert level, and alert description. Among them, there are 3 rules for the Global Broadcast (GB), 3 rules for the Global Discovery Catalog (GDC), and 11 rules for the Global Data Cache (GC).

[0042] The alert rules for GB, GDC, and GC are set as follows: 1) GB sets three alert rules: ① When the connection between the WIS2 node and a single GB fails, the alert level is warning.

[0043] ② When the connection between the WIS2 node and multiple GBs fails, the alert level is error.

[0044] ③ When the connection between the WIS2 node and all GBs fails, the alert level is critical.

[0045]

[0046] 2) There are 11 alarm rules set for GC: ① One or more GCs are unable to download data from a certain WIS2 node in the past 6 hours, with the alarm level being warning.

[0047] ② All GCs are unable to download data from a certain WIS2 node in the past 6 hours, with the alarm level being error.

[0048] ③ All GCs have not downloaded data in the past 1 hour, with the alarm level being critical.

[0049] ④ One or more GCs have 10 download errors within 1 hour, and the anomaly lasts for 6 hours, with the alarm level being warning.

[0050] ⑤ All GCs have 10 download errors in the past 1 hour, and the anomaly lasts for 6 hours, with the alarm level being error.

[0051] ⑥ One or more GCs have download errors from 10 WIS2 nodes in the past 1 hour, and the anomaly lasts for 1 hour, with the alarm level being error.

[0052] ⑦ One or more GCs have download errors from 20 WIS2 nodes in the past 1 hour, and the anomaly lasts for 1 hour, with the alarm level being critical.

[0053] ⑧ One GC is unable to connect to the download server in the past 24 hours, with the alarm level being warning.

[0054] ⑨ All GCs are unable to connect to the download server in the past 24 hours, with the alarm level being error.

[0055] ⑩ One or more GCs are unable to connect to 10 download servers in the past 1 hour, with the alarm level being error.

[0056] ⑪ One or more GCs are unable to connect to 20 download servers in the past 1 hour, with the alarm level being critical.

[0057]

[0058] 3) There are 3 alarm rules set for GDC.

[0059] ① GDC fails to connect to one or more GBs within the past 10 minutes, with the alarm level being critical.

[0060] ② The GDC failed to download metadata from the GC within the past 1 hour, with a warning level of warning.

[0061] ③ The GDC failed to download metadata from the GC for more than 24 hours, with a warning level of warning.

[0062]

[0063] Furthermore, in one embodiment, in step S2, all the alarm messages generated by the GSs are published / subscribed through MQTT. Each GS (Global Service) runs an MQTT-based broker. When an alarm event is detected, all the GSs publish alarm notification messages to their local brokers. The GB (Global Notification Hub) subscribes to all the GSs to obtain the notification messages of the alarm events. The GM subscribes to multiple alarm messages and receives the alarm messages from all the GSs. Among them, all the alarm messages include a topic structure and a message body. The first three layers of the topic structure use monitor / a / wis2, the publisher of the alarm is used as the fourth layer of the topic structure, and the alarm target is used as the fifth layer. In this embodiment, when a new alarm event occurs, all the GSs should publish alarm notification messages to their local brokers. The GB subscribes to all the GSs to obtain the notification messages of the alarm events. The GM subscribes to the alarm messages of multiple GBs and receives the alarm messages from all the GSs. Among them, the first three layers of the topic structure of the alarm message use monitor / a / wis2, the publisher of the alarm is used as the fourth layer of the topic structure, and the alarm target is used as the fifth layer: monitor / a / wis2 / {center-id-producer} / {center-id-target}.

[0064] For example: monitor / a / wis2 / de-dwd-global-cache / ca-eccc-msc represents the alarm generated by the German GC for ca-eccc-msc.

[0065] Further, in some alternative embodiments, the alarm information includes ID, producer, event source, format, alarm level, and content; among which, the alarm levels include "info", "warning", "error", and "critical", with the level increasing successively. When the alarm level is "critical", in addition to sending notification messages, multiple GMs also send the alarm information to the IMS. In this embodiment, further, the GM checks whether it has received a notification message related to this event from another Global Monitor. If not, then the GM should create a Jira ticket; if so, the GM will compare the notification message IDs of all received messages for this event; the GM with the lowest message ID in the same event will be responsible for creating the Jira ticket and sending the alarm information to the IMS system. The flowchart is as Figure 3 shown.

[0066] Further, in one embodiment, in step S3, the use of Grafana to visually present the Metrics index files collected by Prometheus to realize the display and analysis of each monitoring index of GS may include: providing various types of visual monitoring page displays based on different plotting techniques such as Timeseries, Bar chart, Stat, Gauge, State timeline, and Bar gauge, as well as various functions such as increase, delta, sort_desc, and topk; among which, the visual monitoring page display includes the WIS2 node perspective, GISC perspective, and Global Service perspective; the main monitoring content of the WIS2 node perspective includes connectivity and error topic message metadata; the main monitoring content of the GISC perspective is the connectivity of the countries in its own responsible area and error topic message metadata, and after entering the GICS monitoring page, the responsible area country of the GISC is selected; the main monitoring content of the Global Service perspective includes connectivity, GS service capabilities, metadata quality, and key error information.

[0067] In the above embodiments, when performing visual presentation, various types of Dashboards display forms are provided based on different plotting techniques such as Time series, Bar chart, Stat, Gauge, State timeline, Bar gauge, etc., as well as various functions such as increase, delta, sort_desc, and topk.

[0068] First, the Dashboards display is divided into three user perspectives: the WIS2 node perspective, the GISC perspective, and the GlobalService perspective.

[0069] WIS2 node perspective: The main monitoring contents include connectivity, erroneous topic message metadata, etc.

[0070] GISC perspective: The main monitoring content is the connectivity of the countries in the area of ​​responsibility, erroneous subject message metadata, etc. After entering the GICS monitoring page, you can bind the countries in the area of ​​responsibility by selecting GISC.

[0071] Global Service perspective: The main monitoring contents include connectivity, GS service capabilities, metadata quality and key error information.

[0072] Secondly, configure Prometheus as a data source in Grafana to query and display the monitoring data in Prometheus. Apply the functions in Grafana to display the above indicators.

[0073] 1) Use defined label calculations in the function. For example: — centre_id: the centre id of the affected centre — report_by: own center id — metadata_id: The affected metadata ID (GDC only).

[0074] — top: most popular search terms (top=1..5, GDC only) — dataserver: Data server to which the metrics apply (GC only) sum by (centre_id) (increase(wmo_wis2_gb_messages_no_metadata_total {centre_id=~'$centre_id',report_by=~'$gb_report_id'}[$__range]))>0 2) GM uses increase / delta etc. to account for differences in how different GSs reset counters, for example: (wmo_wis2_gb_messages_published {report_by = " fr-meteofrance-global- broker "}[15m]); sort_desc(sum by (centre_id) (delta(wmo_wis2_gc_integrity_failed_ total{centre_id=~"$centre_id", report_by=~"cn-cma-global-cache"}[24h]))) 3) GM uses the time function to convert the timestamps in the connectivity metrics into time differences. For example: time()- wmo_wis2_gc_dataserver_last_download_timestamp_seconds{report_by=~"$gc_ report_id",centre_id!~"io-wis2dev.*",centre_id=~"$centre_id"} 4) GM uses sort_desc and topk to perform quick sort and selection sort. For example: topk($TopN,sum by(centre_id,dataserver) (sort_desc(wmo_wis2_gc_ downloaded_total{report_by=~"cn-cma-global-cache"}))) sort_desc(wmo_wis2_gdc_kpi_percentage_average{centre_id=~"$centre_ id",report_by=~"cn-cma-global-discovery-catalogue"}) The WMO Information System 2.0 global meteorological data exchange monitoring method provided by the embodiments of the present application realizes the monitoring of the functions and service levels of future WMO international data exchange, including two types. First, the availability of WIS2 services, which covers the overall functions of WIS2 and requires ensuring the functions and expected service levels. This type of monitoring is used to evaluate the availability of global services (Broker, Cache, Discovery Catalogue, Gateway, etc.) and the availability of WIS2 node data and services. Second, WIS monitoring will monitor the availability of data on the network. The first monitoring method is used to ensure that WIS2 works as expected, while the second monitoring method will be used to support different WMO programs to monitor the expected availability of data. For this purpose, WMO programs can define requirements, which are then supervised by WIS monitoring.

[0075] In a second aspect, the embodiments of the present application further provide a WMO Information System 2.0 global meteorological data exchange monitoring device.

[0076] In one embodiment, the WMO Information System 2.0 global meteorological data exchange monitoring device includes: a scraping module, which is used to automatically scrape the latest Metrics metric files from the endpoints of each GS at regular intervals based on Prometheus and store the scraped Metrics metric files in the local time series database; an alarm module, which is used to formulate alarm rules according to WMO and evaluate the Metrics metric files based on the rule engine technology to obtain alarm information; a display module, which is used to visualize the Metrics metric files collected by Prometheus using Grafana to realize the display and analysis of each monitoring index of GS.

[0077] Furthermore, in one embodiment, the WMO Information System 2.0 global meteorological data exchange monitoring device further includes a monitoring index generation module, which is used to generate Metrics metric files based on the Openmetrics specification.

[0078] Furthermore, in one embodiment, all GSs include: GB, GDC, GC, GM, WIS2-GTS gateway, and GTS-WIS2 gateway.

[0079] Further, in one embodiment, 41 Metrics index files are generated by each GS. The Metrics index files carry extended tags, and the tags are used as data bases for classification. Among them, GB generates 7 Metrics index files, and each Metrics index file carries 2 tags; GDC generates 12 Metrics index files, and each Metrics index file carries 1 - 3 tags; GC generates 8 Metrics index files, and each Metrics index file carries 2 - 3 tags; GM generates 2 Metrics index files, and each Metrics index file carries 2 tags; GTS-WIS2 gateway generates 4 Metrics index files, and each Metrics index file carries 2 tags; WIS2-GTS gateway generates 8 Metrics index files, and each Metrics index file carries 2 - 3 tags.

[0080] Further, in one embodiment, the Metrics index files are divided into three categories, including connection status indicators, performance indicators, and exception information indicators.

[0081] Further, in one embodiment, the alarm rules include alarm name, alarm condition, alarm level, and alarm description.

[0082] Further, in one embodiment, all alarm information generated by GS is published / subscribed through MQTT. Each GS runs an MQTT-based agent. When an alarm event is detected, all GSs publish alarm notification messages to their local agents. GB subscribes to all GSs to obtain notification messages of alarm events. GM subscribes to multiple alarm information and receives alarm information from all GSs. Among them, the alarm information includes both a topic structure and a message body. The first three layers of the topic structure use monitor / a / wis2, the publisher of the alarm is the fourth layer of the topic structure, and the alarm target is the fifth layer.

[0083] Further, in one embodiment, the alarm information includes ID, producer, event source, format, alarm level, and content. Among them, the alarm levels include "info", "warning", "error", and "critical", and the levels increase one by one. When the alarm level is "critical", in addition to sending a notification message, the alarm information is also sent to IMS.

[0084] Further, in one embodiment, the display module is used to provide various types of visual monitoring page displays based on different plotting techniques such as Time series, Bar chart, Stat, Gauge, State timeline, and Bar gauge, as well as multiple functions such as increase, delta, sort_desc, and topk; among them, the visual monitoring page display includes the WIS2 node perspective, the GISC perspective, and the Global Service perspective; The main monitoring content from the WIS2 node perspective includes connectivity and error topic message metadata; The main monitoring content from the GISC perspective is the connectivity and error topic message metadata of the countries within its own responsibility area. After entering the GICS monitoring page, the responsible area country can be selected through GISC binding; The main monitoring content from the Global Service perspective includes connectivity, GS service capabilities, metadata quality, and critical error information.

[0085] Among them, the functional implementation of each module in the above WMO Information System 2.0 global meteorological data exchange monitoring device corresponds to each step in the above WMO Information System 2.0 global meteorological data exchange monitoring method embodiment, and its functions and implementation processes will not be elaborated here one by one.

[0086] The embodiments of this application provide a method and device for monitoring the global meteorological data exchange of the WMO Information System 2.0. Among them, the method includes: Global services (hereinafter referred to as "GS") generate a monitoring metric file (Metrics) based on the Openmetrics specification; Global Monitor (hereinafter referred to as "GM") regularly fetches the latest Metrics from the Metrics endpoints exposed by each GS; According to the WMO monitoring and alerting rules, based on the rule engine technology, the definition of rules, data evaluation, alert triggering, and alert handling are realized, supporting alerts in forms such as emails and webhooks, and docking with the MQTT component and the WMO Incident Management System (hereinafter referred to as "IMS") to realize the publication of alert messages for abnormal scenarios and automatic submission of problems; Based on different plotting technologies such as Time series, Bar chart, Stat, Gauge, Statetimeline, and Bar gauge, as well as various functions such as increase, delta, sort_desc, and topk, multiple types of Dashboards are presented, and multiple types of Dashboards are presented with various functions such as increase, delta, sort_desc, and topk.

[0087] The method for monitoring the global meteorological data exchange of the WMO Information System 2.0 provided by the embodiments of this application can realize the monitoring of the functions and service levels of future WMO international data exchanges, and is used to evaluate the availability of global services (Broker, Cache, Discovery Catalogue, Gateway, etc.) and WIS2 node data; Ensure the functions and expected service levels of WIS2.0, ensure that WIS2.0 works as expected, and support different WMO plans; And based on technologies such as caching, data preprocessing, load balancing, and personalized panels, diverse presentations of metrics are realized, supporting concurrent access of 200 users per second for the global monitoring system. This method meets the monitoring requirements of WIS2.0 business operations.

[0088] It should be noted that the serial numbers of the above embodiments of this application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0089] In the description of the specification, claims and the above-mentioned drawings of this application, the terms "comprising", "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products or devices. The descriptions such as "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit that "first", "second" and "third" are different types.

[0090] In the description of the embodiments of this application, "exemplary", "for example" or "for instance" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary", "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary", "for example" or "for instance" is intended to present relevant concepts in a specific manner.

[0091] In the description of the embodiments of this application, unless otherwise specified, " / " means "or". For example, A / B may mean A or B; "and / or" in the text is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "a plurality of" means two or more than two.

[0092] In some processes described in the embodiments of this application, there are a plurality of operations or steps that appear in a specific order. However, it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of this application or may be executed in parallel. The serial numbers of the operations are only used to distinguish different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in order or in parallel, and these operations or steps may be combined.

[0093] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) and includes several instructions to enable a terminal device to execute the methods described in the various embodiments of this application.

[0094] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present application.

Claims

1. A WMO Information System 2.0 global meteorological data exchange monitoring method, characterized in that: The WMO Information System 2.0 global meteorological data exchange monitoring method includes: Based on Prometheus, the latest Metrics files are automatically captured from each GS endpoint at a fixed time, and the captured Metrics files are stored in the local time series database; According to the WMO alarm rules, the metrics indicator files are evaluated based on the rule engine technology to obtain alarm information; Use Grafana to visualize the metrics files collected by Prometheus to display and analyze various GS monitoring indicators.

2. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: Before automatically grabbing the latest Metrics indicator files from each GS endpoint based on Prometheus, it also includes: All GS generate metrics files based on the Openmetrics specification.

3. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: All GS include: GB, GDC, GC, GM, WIS2-GTS Gateway and GTS-WIS2 Gateway.

4. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 3, characterized in that: Each GS generates 41 Metrics files, which carry extended tags. Tags are used as the basis for data classification. Among them, GB generates 7 Metrics files, each carrying 2 tags; GDC generates 12 Metrics files, each carrying 1 to 3 tags; GC generates 8 Metrics files, each carrying 2 to 3 tags; GM generates 2 Metrics files, each carrying 2 tags; GTS-WIS2 gateway generates 4 Metrics files, each carrying 2 tags; WIS2-GTS gateway generates 8 Metrics files, each carrying 2 to 3 tags.

5. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: The metrics file is divided into three categories, including connection status metrics, performance metrics, and abnormal information metrics.

6. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: The alarm rules include alarm name, alarm condition, alarm level and alarm description.

7. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: All alarm information generated by GS is published / subscribed through MQTT. Each GS runs an MQTT-based agent. When an alarm event is detected, all GSs publish alarm notification messages to their local agents. GB subscribes to all GSs to obtain notification messages of alarm events. GM subscribes to multiple alarm information and receives alarm information from all GSs. Among them, alarm information includes topic structure and message body. The first three layers of the topic structure use monitor / a / wis2, the publisher of the alarm is the fourth layer of the topic structure, and the alarm target is the fifth layer.

8. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 7, characterized in that: The alarm information includes ID, producer, event source, format, alarm level and content; wherein the alarm level includes "info", "warning", "error" and "critical", and the levels increase one by one. When the alarm level is "critical", in addition to sending a notification message, the alarm information is also sent to IMS.

9. The WMO Information System 2.0 global meteorological data exchange monitoring method according to claim 1, characterized in that: The use of Grafana to visualize the metrics files collected by Prometheus enables the display and analysis of various GS monitoring indicators, including: Based on different drawing technologies such as Time series, Bar chart, Stat, Gauge, State timeline and Bar gauge, as well as multiple functions such as increase, delta, sort_desc and topk, various types of visual monitoring page displays are provided; among which, the visual monitoring page displays include WIS2 node perspective, GISC perspective and Global Service perspective; The main monitoring contents from the WIS2 node perspective include connectivity and erroneous topic message metadata; The main monitoring content of the GISC perspective is the connectivity of the countries in its own area of ​​responsibility and the metadata of the wrong subject messages. After entering the GICS monitoring page, select GISC to bind the countries in the area of ​​responsibility; The Global Service perspective mainly monitors connectivity, GS service capabilities, metadata quality, and key error information.

10. A WMO Information System 2.0 global meteorological data exchange monitoring device, characterized in that: The WMO Information System 2.0 global meteorological data exchange monitoring device includes: The crawling module is used to automatically crawl the latest Metrics index files from each GS endpoint based on Prometheus timing, and store the crawled Metrics index files in the local time series database; The alarm module is used to formulate alarm rules according to WMO and evaluate the Metrics indicator file based on the rule engine technology to obtain alarm information; The display module is used to use Grafana to visualize the Metrics files collected by Prometheus, and to display and analyze various GS monitoring indicators.

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