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  1. MariaDB Server
  2. MDEV-36194

Automatic Scaling for Dynamic Environments

Details

    Description

      MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

      Current State

      1. Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
      2. Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
      3. Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
      4. Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

      *Proposed Feature Set: Automatic CPU-Based, RAM-Based Auto-Scaling and Hill-Climbing (Enterprise).
      Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.

      Attachments

        Issue Links

          is blocked by

          New Feature - A new feature of the product, which has yet to be developed. MDEV-36196 Thread Pool Auto-Scaling Based on CPU Count

          • Major - Major loss of function.
          • Open

          New Feature - A new feature of the product, which has yet to be developed. MDEV-36197 Implement Buffer Pool Auto-Scaling Based on RAM Availability

          • Major - Major loss of function.
          • Open
          relates to

          Task - A task that needs to be done. MDEV-19839 refactor --autoset

          • Major - Major loss of function.
          • Open

          Task - A task that needs to be done. MDEV-19895 Support "autoset" in SET GLOBAL for AUTO_SET system variables

          • Major - Major loss of function.
          • Open

          Activity

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            adamluciano Adam Luciano created issue -
            adamluciano Adam Luciano made changes -
            Field Original Value New Value
            adamluciano Adam Luciano made changes -
            adamluciano Adam Luciano made changes -
            adamluciano Adam Luciano made changes -
            Description MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            *Proposed Feature Set: *Automatic CPU-Based, Hill-Climbing, and RAM-Based Auto-Scaling
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.             		MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            **Proposed Feature Set: *Automatic CPU-Based, Hill-Climbing, and RAM-Based Auto-Scaling*
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.
            adamluciano Adam Luciano made changes -
            Description MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            **Proposed Feature Set: *Automatic CPU-Based, Hill-Climbing, and RAM-Based Auto-Scaling*
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.             		MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            *Proposed Feature Set: Automatic CPU-Based, Hill-Climbing, and RAM-Based Auto-Scaling*
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.
            adamluciano Adam Luciano made changes -
            Summary Hardware Automatic Scaling for Dynamic Environments Automatic Scaling for Dynamic Environments
            adamluciano Adam Luciano made changes -
            Labels server kubernetes performance server
            marko Marko Mäkelä made changes -
            marko Marko Mäkelä made changes -
            adamluciano Adam Luciano made changes -
            Description MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            *Proposed Feature Set: Automatic CPU-Based, Hill-Climbing, and RAM-Based Auto-Scaling*
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.             		MariaDB Server must adapt seamlessly to hardware resource changes (CPU, RAM) in dynamic environments like Kubernetes/Cloud, where allocations can shift online without server restarts. This story covers the development of automatic scaling mechanisms to optimize thread pool and buffer pool usage based on real-time hardware availability, reducing manual tuning and enhancing cloud-native performance.

            *Current State*
            # Thread Pool Dynamism: The thread pool adjusts active threads based on workload within thread_pool_min_threads and thread_pool_max_threads.
            # Manual CPU Scaling: thread_pool_size can be changed via SET GLOBAL, but there’s no automatic adjustment for CPU changes.
            # Buffer Pool Static Configuration: innodb_buffer_pool_size defaults to 128MB and requires manual tuning, despite recommendations of 75-80% of RAM.
            # Kubernetes & Cloud Constraints: Containerized environments dynamically scale CPU and RAM, but MariaDB relies on manual intervention or scripts to optimize resource usage.

            *Proposed Feature Set: Automatic CPU-Based, RAM-Based Auto-Scaling and Hill-Climbing (Enterprise).
            Introduce configurable auto-scaling mechanisms to dynamically adjust the thread pool and buffer pool based on resource changes.

            People

              wlad Vladislav Vaintroub
              adamluciano Adam Luciano
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              Dates

                Created:
                Updated:

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