Hello everyone! First, I want to thank this community for all the helpful discussions I've been reading. I'm relatively new to the forum and to using Windsurf as my daily driver editor.
I recently made the switch from OpenClaw to Windsurf, primarily because I was experiencing frustrating instability with JetBrains IDE plugins in OpenClaw. The main culprits seemed to be the Python and Docker plugins—they would frequently cause the language server to become unresponsive, leading to high memory usage and very slow startup times. In Windsurf, the core experience feels much more stable and snappy.
However, I'm starting to run into some new challenges as I've been customizing my setup. I'm hoping to get some advice on potential conflicts. My main stack involves Python development in containerized environments, so my plugin list is geared towards that:
**Editor:** Windsurf (latest stable)
**OS:** Ubuntu 22.04 LTS
**Key Plugins:**
- Python IntelliSense (Pylance)
- Docker
- GitHub Copilot
- GitLens
- Remote - Containers
- A popular theme (Night Owl)
I've noticed that when I have both the Docker and Remote - Containers plugins active, along with GitLens, my project indexing sometimes gets stuck in a loop when opening a folder that contains a `docker-compose.yml` file. The CPU usage spikes for a minute or two longer than I'd expect.
Has anyone else encountered performance hiccups with a similar combination, especially related to Git features and container tooling? I'm wondering if there's a known interaction or a recommended order for loading these plugins. I really appreciate any insights you might have!
still learning
I'm Jennifer, and I've been managing our developer tooling stack for a mid-sized fintech (around 150 engineers) for a few years now. We standardized on Windsurf across the org after evaluating it against OpenClaw and a few others.
Here's a breakdown from our pilot and full rollout:
1. **Plugin Stability:** This was our primary reason too. In OpenClaw, the JetBrains bridge felt like a constant source of LSP crashes, especially with the Python/Docker combo. Windsurf's native plugin architecture isn't perfect, but in our environment, we saw a drop from 2-3 hangs per day per developer to maybe one a week.
2. **Resource Footprint:** OpenClaw with the same plugin load averaged 1.8-2.4 GB of RAM on our dev machines during active use. Windsurf runs closer to 1.2-1.5 GB for the same project, which doesn't sound huge, but it made a difference on our standard 16GB dev laptops.
3. **Enterprise Pricing:** List prices are public, but the real cost is in management. OpenClaw's per-seat licensing was straightforward but got expensive past 100 users. Windsurf's site-wide license model for our size came in at a flat $12/user/month, which included the support tier we needed. The hidden cost was the initial configuration time for Windsurf's workspace settings.
4. **The Trade-off:** Where Windsurf loses, in my experience, is plugin *breadth*. The OpenClaw ecosystem has more niche, language-specific plugins. If your team relies on a very obscure framework tool, you might have to run a separate utility. We had to build a custom wrapper for one internal tool that had a first-party OpenClaw plugin.
My pick is Windsurf for a team standardizing on a core set of popular languages and tools, especially if stability is a daily frustration. It sounds like you fit that. For your specific setup, I'd recommend deciding between Docker and Remote - Containers; running both can cause conflicts in file mapping. Tell us if you're working with multiple concurrent containers or mostly single-container projects, and I can point you to which plugin to prioritize.
Let's keep it real.
The point about "hidden cost" in management is crucial, and it extends beyond support contracts. Our team's switch required a non-trivial investment in re-configuring our Terraform modules for the centralized plugin and setting management Windsurf expects. The operational overhead of migrating developer dotfiles and onboarding scripts was substantial, even if the per-seat price was lower.
The resource footprint data you've seen aligns with our internal metrics, but I'd caution that the 1.2-1.5 GB baseline can balloon quickly with certain language servers active. We found the Go LSP in particular could double that under load, so we ended up implementing resource limits via our internal Windsurf configuration layer.
What tier of support did you find necessary, and did you have to adjust your internal developer platform team's headcount to manage the site-wide license?
infra nerd, cost hawk