Integrations¶

Alibaba Cloud KafKa
Alibaba Cloud KafKa includes instance disk usage, instance and topic message production volume, message production frequency, message consumption volume, message consumption frequency, etc. These metrics reflect the reliability of Kafka in handling large-scale message transmission and real-time data streams.

Alibaba Cloud MongoDB
Alibaba Cloud MongoDB Replica Set Metrics Display, including CPU usage, memory usage, disk usage, data disk space occupied, log disk space occupied, number of statements executed per second, request count, connection count, network traffic, replication delay, QPS, etc.
Alibaba Cloud MongoDB Sharded Cluster Metrics Display, including CPU usage, memory usage, disk usage, data disk space occupied, log disk space occupied, number of statements executed per second, request count, connection count, network traffic, replication delay, QPS, etc.
Alibaba Cloud MongoDB Single Node Instance Metrics Display, including CPU usage, memory usage, disk usage, data disk space occupied, number of statements executed per second, request count, connection count, network traffic, QPS, etc.

Alibaba Cloud DDoS New BGP High Defense
The displayed Metrics of Alibaba Cloud DDoS New BGP High Defense include attack protection capability, cleaning capability, response time, and reliability. These Metrics reflect the performance and credibility of the New BGP High Defense service when dealing with large-scale DDoS attacks.

AWS Simple Queue Service
The displayed metrics of AWS Simple Queue Service include the approximate Exist time of the oldest un-deleted message in the queue, the number of delayed messages that cannot be read immediately, the number of messages in flight state, the number of messages that can be retrieved from the queue, etc.

AWS Timestream
The displayed metrics of AWS Timestream include the number of system errors (internal service errors), the total number of invalid requests for the current AWS region and account, the elapsed time and sample count of successful requests, the amount of data stored in memory, and the amount of data stored on magnetic storage, etc.

Lark and Exception Tracking Integration
To get new issues from exception tracking more timely and conveniently, we can create a Lark, DingTalk or WeChat Work bot in the internal group to receive new issue alerts from exception tracking, or new reply alerts. This can help us handle issues in a timely manner. We can also quickly respond to issues by @bot, which can improve our exception handling efficiency.

Huawei Cloud FunctionGraph
The displayed metrics for Huawei Cloud FunctionGraph include the number of calls, number of errors, number of rejections, concurrency count, reserved instance count, and run time (including maximum run time, minimum run time, and average run time), which reflect the operational status of the FunctionGraph function.

Huawei Cloud GaussDB-Cassandra
The displayed Metrics for Huawei Cloud GaussDB-Cassandra include read/write throughput, latency, data consistency, and scalability. These Metrics reflect the performance and reliability of GaussDB-Cassandra when handling large-scale distributed data storage and access.

Huawei Cloud SYS.DDMS Monitoring View
The Huawei Cloud SYS.DDMS monitoring view displays indicators including message throughput, latency, concurrent connections, and reliability, which reflect the performance and reliability assurance of DDMS in handling large-scale message delivery and real-time data flow.

Incident Events Integration with Jira
When our applications or systems experience incidents, they usually need to be handled promptly to ensure normal system operation. To better manage and track incident events, we can send these events to Jira to create issues, allowing us to track, analyze, and resolve these problems within Jira. By quickly sending incident events to Jira to create issues, we gain better capabilities for managing and tracking incident events, thereby ensuring smoother system operations. Additionally, this method also helps us better analyze and solve problems, enhancing the stability and reliability of the system.

Incident Events Integration with PagerDuty
When our applications or systems experience incidents, they typically need to be addressed promptly to ensure normal system operations. To better manage and track incident events, we can send these events to PagerDuty to create incidents, allowing us to track, analyze, and resolve these issues within PagerDuty. By quickly sending incident events to PagerDuty to create incidents, we gain better capabilities for managing and tracking incident events, thereby ensuring the normal operation of the system more effectively. Additionally, this method helps us better analyze and resolve problems, enhancing the stability and reliability of the system.