ProxLB Blog
ProxLB Release 1.0.3 [2024-09-12]
ProxLB just got released in its maintenance version 1.0.3. With the new version, it comes with some new smaller features and fixes. The new ProxLB upgrade can be obtained by:The whole changelog can be found here:
Added:
Add a convert function to cast all bool alike options from configparser to bools. [#53]
Add a config parser options for future features. [#53]
Add a config versio schema that must be supported by ProxLB. [#53]
Add feature to allow the API hosts being provided as a comma separated list. [#60]
Add storage balancing function. [#51]
Add doc how to add dedicated user for authentication. (by @Dulux-Oz)
Add cli arg -b to return the next best node for next VM/CT placement. [#8]
Fixed:
Fix documentation for the master_only parameter placed in the wrong config section. [#74]
Fixed master_only function by inverting the condition.
Improved the overall validation and error handling. [#64]
Fix bug in the proxlb.conf in the vm_balancing section.
Fix handling of unset ignore_nodes and ignore_vms resulted in an attribute error. [#71]
Fix anti-affinity rules not evaluating a new and different node. [#67]
Changed:
Provide a more reasonable output when HA services are not active in a Proxmox cluster. [#68]
Improve the underlying code base for future implementations. [#53]
More details can be found on the GitHub project site right here.
ProxLB Release 1.0.2 [2024-08-13]
ProxLB just got released in its maintenance version 1.0.2. With the new version, it comes with some new smaller features and fixes. The new ProxLB upgrade can be obtained by:The whole changelog can be found here:
Added:
Add option to run migration in parallel or sequentially. [#41]
Add option to run ProxLB only on the Proxmox's master node in the cluster. [#40]
Fixed:
Fix daemon timer to use hours instead of minutes. [#45]
Fix CMake packaging for Debian package to avoid overwriting the config file. [#49]
Fix some wonkey code style.
More details can be found on the GitHub project site right here.
ProxLB Release 1.0.0 [2024-08-01]
ProxLB just got released in its first version 1.0.0. With the new version, ProxLB is now also available as:The new releases also comes with several new features. The whole changelog can be found here:
Added:
Add feature to prevent VMs from being relocated by defining a wildcard pattern. [#7]
Add feature to make log verbosity configurable [#17].
Add option_mode to rebalance by node's free resources in percent (instead of bytes). [#29]
Add option to rebalance by assigned VM resources to avoid over provisioning. [#16]
Add Docker/Podman support. [#10 by @daanbosch]
Add exclude grouping feature to rebalance VMs from being located together to new nodes. [#4]
Add feature to prevent VMs from being relocated by defining the 'plb_ignore_vm' tag. [#7]
Add dry-run support to see what kind of rebalancing would be done. [#6]
Add LXC/Container integration. [#27]
Add include grouping feature to rebalance VMs bundled to new nodes. [#3]
Changed:
Adjusted general logging and log more details.
More details can be found on the GitHub project site right here.
ProxLB: Introducing ProxLB - a Load Balancer for Proxmox [2024-07-20]
ProxLB - the Prox Load Balancer, is an advanced tool designed to enhance the efficiency and performance of Proxmox clusters by optimizing the distribution of virtual machines (VMs) or Containers (CTs) across the cluster nodes by using the Proxmox API. ProxLB meticulously gathers and analyzes a comprehensive set of resource metrics from both the cluster nodes and the running VMs. These metrics include CPU usage, memory consumption, and disk utilization, specifically focusing on local disk resources.PLB collects resource usage data from each node in the Proxmox cluster, including CPU, (local) disk and memory utilization. Additionally, it gathers resource usage statistics from all running VMs, ensuring a granular understanding of the cluster's workload distribution.
Intelligent rebalancing is a key feature of ProxLB where it re-balances VMs based on their memory, disk or CPU usage, ensuring that no node is overburdened while others remain underutilized. The rebalancing capabilities of PLB significantly enhance cluster performance and reliability. By ensuring that resources are evenly distributed, PLB helps prevent any single node from becoming a performance bottleneck, improving the reliability and stability of the cluster. Efficient rebalancing leads to better utilization of available resources, potentially reducing the need for additional hardware investments and lowering operational costs. Automated rebalancing reduces the need for manual actions, allowing operators to focus on other critical tasks, thereby increasing operational efficiency. You can also find more about it at the GitHub project site here.