# QoS Published articles for QoS. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Kubernetes v1.37: Memory QoS Graduates to Beta DevFeed: [Kubernetes v1.37: Memory QoS Graduates to Beta]() Original publisher: [Read original article]() Author: Qi Wang; Sohan Kunkerkar Published: 2026-09-14T18:30:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [releases](), [configuration](), [Linux](), [Kernel]() Tags: [clusters](), [configuration](), [container](), [kernel](), [kubernetes](), [linux](), [memory](), [qos](), [releases](), [upgrade](), [v1]() ### AI overview Kubernetes v1.37 promotes Memory QoS to Beta and enables it by default on Linux nodes using cgroup v2. The article explains the updated defaults, configuration options for memory throttling and tiered memory protection, and upgrade behavior intended to preserve existing runtime behavior. ### Source excerpt Memory QoS has graduated to Beta in Kubernetes v1.37 and is now enabled by default. On Linux nodes running cgroup v2, the feature uses the memory controller to give the kernel better guidance on how to treat container memory. It was first introduced as Alpha in v1.22, and expanded in v1.36 with tiered memory reservation. This post covers what changed in v1.37, what the Beta promotion means for cluster operators, and how to configure the feature. What changed in v1.37Memory QoS is Beta and enabled by default The MemoryQoS feature gate is now Beta in v1.37. This means every v1.37 kubelet has the feature gate turned on without any configuration change. Turning on the feature by default is safe because the default kubelet configuration does not enable memory throttling or memory reservation. No memory.high, memory.min, or memory.low values are written to cgroups unless you explicitly configure them. You can opt into specific behaviors through kubelet configuration fields: Set memoryThrottlingFactor (for example, 0.9) to enable memory.high throttling on Burstable and BestEffort containers. The default is null, which means no throttling. Set memoryReservationPolicy to TieredReservation to enable tiered memory protection via memory.min and memory.low. The default is None, which means no memory reservation. Default memoryThrottlingFactor changed to null In earlier Alpha releases, memoryThrottlingFactor defaulted to 0.9, which meant enabling the feature gate caused the kubelet to set memory.high on containers. In v1.37, the default is null, so the kubelet does not set memory.high unless you configure a value. This change was made because, with the feature gate now on by default, an automatic memory.high could throttle workloads that were previously running without throttling. Making it null ensures that upgrading to v1.37 does not change runtime behavior for existing clusters. If your kubelet configuration file already contains an explicit memoryThrottlingFactor value, that ## On ACLs and AI-Generated Device Configurations DevFeed: [On ACLs and AI-Generated Device Configurations]() Original publisher: [Read original article]() Published: 2026-08-11T05:11:00Z Content type: opinion Language: en Sources: [ipSpace.net blog]() Topics: [Artificial Intelligence]() Tags: [ai](), [driving](), [netlab](), [qos](), [youtube]() ### AI overview The article introduces a NetworkAutoMagic episode discussing ACL complexity, QoS, and the pitfalls of AI-generated network device configurations, with related notes and video options mentioned. ### Source excerpt Last Friday, I had a lovely chat with Steinn Bjarnarson and Urs Baumann, resulting in the NetworkAutoMagic episode 11. We couldn't avoid mentioning netlab, the seven layers of ACL hell (which is still balmy compared to the QoS hell), and the gotchas of AI-generated device configurations. Fortunately, I don't have to go into more details; Steinn published extensive notes, and if you don't feel like listening to us while driving, you can waste time watching us on YouTube. ## What is the difference between latency and Jitter DevFeed: [What is the difference between latency and Jitter]() Original publisher: [Read original article]() Author: j2sw Published: 2026-06-19T15:16:46Z Content type: tutorial Language: en Sources: [Justin Wilson (j2sw)]() Topics: [Latency](), [Network]() Tags: [jitter](), [latency](), [network](), [network-operations](), [network-troubleshooting](), [perfomance](), [qos](), [wireless]() ### AI overview The article explains that latency is the time a packet takes to travel between endpoints, while jitter is variation in packet arrival times. It describes how routes, distance, transit links, wireless interference, queues, and retransmissions can affect these conditions, and why speed tests may miss jitter that harms VoIP calls. ### Source excerpt Latency is the time a packet takes to make the trip. Jitter is the swing between packets. One makes the path feel far away. The other makes voice, video, gaming, and remote desktop feel broken. Tags: jitter, latency, network troubleshooting, packet loss, QoS, ISP networks, wireless networks, network The post What is the difference between latency and Jitter appeared first on Justin Wilson (j2sw). ## Worth Exploring: LibreQoS DevFeed: [Worth Exploring: LibreQoS]() Original publisher: [Read original article]() Published: 2024-05-08T06:46:00Z Content type: article Language: en Sources: [ipSpace.net blog]() Topics: [Network](), [Open Source](), [Networks](), [Software](), [x86]() Tags: [network](), [networks](), [open-source](), [platforms](), [qos](), [software](), [switching](), [worth-reading](), [x86]() ### AI overview The article highlights LibreQoS, an open-source software solution that provides quality of service through software switching on many-core x86 platforms. Designed as a bump-in-the-wire system, it can be placed near network congestion points to manage packet dropping and prioritization. ### Source excerpt Erik Auerswald pointed me to an interesting open-source project. LibreQoS implements decent QoS using software switching on many-core x86 platforms. It's implemented as a bump-in-the-wire software solution, so you should be able to plug it into your network just before a major congestion point and let it handle the packet dropping and prioritization. Obviously, the concept is nothing new. I wrote about a similar problem in xDSL networks in 2009. ## Stop the Network-Based Application Recognition Nonsense DevFeed: [Stop the Network-Based Application Recognition Nonsense]() Original publisher: [Read original article]() Published: 2024-04-24T06:35:00Z Content type: opinion Language: en Sources: [ipSpace.net blog]() Topics: [Networks](), [Cisco](), [Optimization](), [client]() Tags: [cisco](), [network](), [opinion](), [optimization](), [qos](), [traffic-engineering]() ### AI overview The article argues that service providers should prioritize simple, fair congestion management based on individual-user link utilization instead of relying on application recognition and Cisco Ultra Traffic Optimization AI. It also places current concerns about QUIC in the context of earlier claims that UDP, BitTorrent, or video would overwhelm networks. ### Source excerpt One of my readers sent me an interesting update on the post-QUIC round of NBAR whack-a-mole (TL&DR: everything is better with Bluetooth AI): Cloudflare (and the other hyperscalers) are full into QUIC, as it gives them lots of E2E control, taking a lot of choice away from the service providers on how they handle traffic and congestion. It is quite well outlined by Geoff Huston in an APNIC podcast. So far, so good. However, whenever there's a change, there's an opportunity for marketing FUD, coming from the usual direction. Read more ... ## Worth Reading: Things We Know about Network Queues DevFeed: [Worth Reading: Things We Know about Network Queues]() Original publisher: [Read original article]() Published: 2024-03-23T08:41:00Z Content type: opinion Language: en Sources: [ipSpace.net blog]() Topics: [Network](), [datacenter]() Tags: [article](), [data-center](), [network](), [qos](), [take](), [worth-reading]() ### AI overview The article recommends Avery Pennarun's piece on what is known about network queues and cautions readers to be skeptical of expensive big-buffer data center switches. ### Source excerpt Every time someone tries to persuade you to buy (expensive) big-buffer data center switches, take an antidote: the Things we (finally) know about network queues article by Avery Pennarun. ## Kubernetes Resource Planning with Requests and Limits DevFeed: [Kubernetes Resource Planning with Requests and Limits]() Original publisher: [Read original article]() Author: info@goteleport.com (HD) Published: 2019-05-16T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Kubernetes](), [configuration](), [Containers](), [cpu]() Tags: [configuration](), [cpu](), [deploy](), [kubernetes](), [memory](), [qos](), [workflow]() ### AI overview This tutorial explains how Kubernetes resource requests and limits help manage CPU and memory as clusters grow. It describes how unbounded pod resources can contribute to application degradation, pod eviction, and throttling, and explains how defined values affect scheduling and Quality of Service. ### Source excerpt As your Kubernetes cluster grows, stability issues surface. Learn how defined resource values ensure critical apps get the Quality of Service they deserve.