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Supported Monitoring Metrics

Last updated: 2023-08-22 15:46:51
    TDSQL-C for MySQL provides monitoring metrics at the instance level.

    Monitored metrics

    Note:
    You can view the following monitoring metrics in the console or through TencentCloud API as instructed in Viewing Monitoring Data.
    N in the monitoring metric unit indicates the unit of the current query time granularity. For example, if the granularity is 5 seconds, N will be second (sec); if it is 1 minute, N will be minute (min).
    Parallel query monitoring metrics are supported only for TDSQL-C for MySQL 8.0 (kernel version 3.1.8) or later.
    Category
    Monitoring Metric
    Parameter
    Unit
    Data Aggregation Method
    Resource monitoring
    CPU Utilization
    cpu_use_rate
    %
    MAX
    Memory Utilization
    memory_use_rate
    %
    MAX
    Used Memory
    memory_use
    MB
    MAX
    Storage Utilization
    storage_use_rate
    %
    MAX
    Used Storage Space
    storage_use
    GB
    MAX
    Used Data Tablespace
    data_use
    GB
    MAX
    Used Temp Tablespace
    tmp_use
    GB
    MAX
    Used Undo Tablespace
    undo_use
    GB
    MAX
    CCU
    CCU
    -
    MAX
    Total Traffic Sent to Client per Sec
    bytes_sent
    MB/s
    MAX
    Total Traffic Received from Client per Sec
    bytes_received
    MB/s
    MAX
    Engine monitoring
    Connection
    Executed Queries per Sec
    qps
    Counts/sec
    MAX
    Executed Transactions per Sec
    tps
    Counts/sec
    MAX
    Connection Utilization
    connection_use_rate
    %
    MAX
    Max Connections
    max_connections
    -
    MAX
    Open Connections
    threads_connected
    -
    MAX
    Created Threads
    threads_created
    -
    SUM
    Running Threads
    | threads_running | Running threads |
    -
    MAX
    Access
    Slow Queries
    slow_queries
    -
    SUM
    Full-Table Scans
    select_scan
    -
    SUM
    SELECT Statements
    com_select
    -
    SUM
    UPDATE Statements
    com_update
    -
    SUM
    DELETE Statements
    com_delete
    -
    SUM
    INSERT Statements
    com_insert
    -
    SUM
    REPLACE Statements
    com_replace
    -
    SUM
    Total Queries
    queries
    -
    SUM
    COMMIT Statements
    com_commit
    -
    SUM
    ROLLBACK Statements
    com_rollback
    -
    SUM
    Full-Table Scan Joins
    select_full_join
    -
    SUM
    Range Scan Joins
    select_full_range_join
    -
    SUM
    Sort Merges
    sort_merge_passes
    -
    SUM
    Qcache Hit Rate
    qcache_hit_rate
    %
    MIN
    Qcache Utilization
    qcache_use_rate
    %
    MIN
    Table
    Temp Tables
    created_tmp_tables
    -
    SUM
    Table Lock Waits
    table_locks_waited
    -
    SUM
    Open Tables
    opened_tables
    -
    MAX
    Table Locks Released Immediately
    table_locks_immediate
    -
    SUM
    Open Table Cache Hits
    table_open_cache_hits
    -
    SUM
    Open Table Cache Misses
    table_open_cache_misses
    -
    SUM
    InnoDB
    InnoDB Cache Hit Rate
    innodb_cache_hit_rate
    %
    MIN
    InnoDB Cache Utilization
    innodb_cache_use_rate
    %
    MIN
    Disk Reads
    innodb_os_file_reads
    -
    MAX
    Disk Writes
    innodb_os_file_writes
    -
    MAX
    InnoDB_fsyncs
    innodb_os_fsyncs
    -
    MAX
    Tables Opened by InnoDB
    innodb_num_open_files
    -
    MAX
    Data Read in InnoDB
    innodb_data_read
    Byte
    SUM
    Total InnoDB Reads
    innodb_data_reads
    -
    SUM
    Total InnoDB Writes
    innodb_data_writes
    -
    SUM
    Data Written in InnoDB
    innodb_data_written
    Byte
    SUM
    Rows Deleted from InnoDB Tables
    innodb_rows_deleted
    -
    SUM
    Rows Inserted to InnoDB Tables
    innodb_rows_inserted
    -
    SUM
    Rows Updated in InnoDB Tables
    innodb_rows_updated
    -
    SUM
    Rows Read from InnoDB Tables
    innodb_rows_read
    -
    SUM
    Avg Time to Get an InnoDB Row Lock
    innodb_row_lock_time_avg
    ms
    MAX
    InnoDB Row Lock Waits
    innodb_row_lock_waits
    -
    SUM
    InnoDB Dirty Pages
    innodb_buffer_pool_pages_dirty
    -
    MAX
    Writes Suspended in InnoDB
    innodb_data_pending_writes
    -
    MAX
    Reads Suspended in InnoDB
    innodb_data_pending_reads
    -
    MAX
    Waiting Writes for InnoDB Log
    innodb_log_waits
    -
    SUM
    Physical Writes for InnoDB Log
    innodb_log_writes
    -
    SUM
    Physical Write Requests for InnoDB Log
    innodb_log_write_requests
    -
    SUM
    Tmp
    Temp Tables
    created_tmp_disk_tables
    -
    SUM
    Temp Files
    created_tmp_files
    -
    SUM
    Handler
    Requests to Read Next Row
    handler_read_rnd_next
    -
    SUM
    Rollbacks Performed in Storage Engine
    handler_rollback
    -
    SUM
    Internal COMMIT Statements
    handler_commit
    -
    SUM
    Buffer
    InnoDB Free Pages
    innodb_buffer_pool_pages_free
    -
    MAX
    Total InnoDB Pages
    innodb_buffer_pool_pages_total
    -
    MAX
    InnoDB Logical Reads
    innodb_buffer_pool_read_requests
    -
    SUM
    InnoDB Physical Reads
    innodb_buffer_pool_reads
    -
    SUM
    Writes in InnoDB Buffer Pool
    innodb_buffer_pool_write_request
    -
    SUM
    Parallel qery
    Parallelly Queried Threads
    txsql_parallel_threads_currently_used
    -
    MAX
    Failed Parallel Queries
    txsql_parallel_stmt_error
    -
    SUM
    Executed Parallel Queries
    txsql_parallel_stmt_executed
    -
    SUM
    Parallel-to-Serial Queries
    txsql_parallel_stmt_fallback
    -
    SUM
    Others
    Total Opened Files
    open_files
    -
    MAX
    Deployment monitoring
    Replication Status
    replication_status
    0: Yes; 1: No
    1 will be taken if present.
    Replication Delay
    replication_delay
    ms
    MAX
    Source-Replica Replication LSN Difference
    replication_delay_distance
    Bytes
    MAX

    Performance monitoring data analysis

    You can set alarm policies to monitor and analyze performance metrics. Below are some examples:
    CPU utilization: It describes how the CPU in the database server is used while running. If the CPU load is high, there will be problems such as slow response of the database system and query delay. Therefore, you can set a threshold alarm for this monitoring metric as needed. Generally, if the CPU utilization exceeds 90%, you need to check the request volume and query performance, and make timely adjustments. If the CPU utilization meets the application or database requirements such as throughput and concurrency and is expected, then it is appropriate.
    Used storage space: If the used storage space is always greater than or equal to 85% of the total disk space, you need to check how the storage space is used and whether the data can be deleted from the instance or archived to another system to free up space. If the amount of stored data is too large, the disk is about to be full, and you can solve the problem of insufficient disk space through capacity expansion.
    Traffic inbound to/outbound from client: You can check the fluctuations of these metrics in Resource Monitoring to determine whether the problem is caused by the business peak or database, and then optimize the business or adjust the database configuration.
    Max connections: max_connections is one of the parameters in TDSQL-C for MySQL, which is used to specify the maximum number of connections allowed by the database. When the database process opens a new connection, the number of currently connected clients will be queried. If the number has reached the set value of max_connections, a new connection cannot be established. If there is a large number of connections, the instance performance drops, and the response time increases, you need to consider restricting the maximum number of connections to the database. If the value of max_connections is set too high, it may cause problems such as insufficient memory and thread crash in the system. Therefore, you should carefully evaluate your application needs and set an appropriate value. The value generally falls between 200 and 500. You can also adjust the maximum number of connections based on the connection conditions of applications and databases.
    When a performance metric exceeds the configured alarm threshold, you may need to modify relevant parameters to optimize the database to improve its performance and availability.
    
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