Stéphane Philippart, Author at OVHcloud Blog

🎙️ Tranches de Tech #30 – Makers de père en fils

Stéphane Philippart — Sun, 05 Jul 2026 07:59:03 +0000

👤 Invitée : Sylvain Gougouzian
- Bluesky : @gouz.dev
- LinkedIn : https://www.linkedin.com/in/gouz
🗓️ Date d’enregistrement : 30 juin 2026
🎧 Lien vers l’épisode

👤 Présentation de Sylvain – ⏱️ 1″

📰 News Techs

🤖 Intelligence Artificielle – ⏱️ 56″03

Home assistant x OVHcloud AI Endpoints

https://rc.home-assistant.io/integrations/ovhcloud_ai_endpoints

The pressure

https://daniel.haxx.se/blog/2026/05/26/the-pressure/

La Norvège va interdire les chatbots IA aux écoliers

GitHub Copilot is moving to usage-based billing

https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing/

Is AI profitable yet?

https://isaiprofitable.com

NVIDIA announced NVCF

http://github.com/nvidia/nvcf

Le gouvernement américain interdit Fable 5 et Mythos 5 a tout non américain dans le monde

https://www.anthropic.com/news/fable-mythos-access

OpenAI acquires Ona (ex Gitpod)

https://twitter.com/i/status/2065572964062666976

☁️ Cloud – ⏱️ 1h27″40

Terraform S3 state locking with OVHcloud Object Storage

https://blog.ovhcloud.com/terraform-s3-state-locking-ovhcloud-object-storage/

🔐 Sécurité – ⏱️ 1h30″

Secure Image Signing with Cosign and OVHcloud KMS

https://blog.ovhcloud.com/secure-image-signing-cosign-ovhcloud-kms/

🎤 Conférences / meetup – ⏱️ 1h32″43

💡 Retrouvez l’ensemble des autres épisodes ici : https://smartlink.ausha.co/tranches-de-tech 💡

Discovering Docker Agent with AI Endpoints

Stéphane Philippart — Thu, 02 Jul 2026 11:50:06 +0000

What if you could build a team of AI agents, each specialized in a different task, working
together like a well-oiled pipeline, without having to build agent orchestration logic from
scratch ?
That’s exactly what Docker Agent brings to the table.

Docker Agent is an open-source framework for building collaborative multi-agent workflows.
Instead of one monolithic agent trying to do everything, you compose a team of specialized
agents. Each agent has a clear role, specific tools, and its own model, allowing them to
communicate and collaborate on complex, multi-step tasks.

In this post, we’ll explore how to wire up Docker Agent with OVHcloud AI Endpoints to create
a multi-agent coding assistant: one agent browses documentation, another writes the code.

Install/configure Docker Agent

All detailed instructions for installing and configuring Docker Agent can be found in
the official documentation.
Once installed, Docker Agent is available as the docker-agent or docker agent command line
tool.
⚠ Docker Agent does not need Docker engine to run. ⚠

Authenticate with AI Endpoints

To use Docker Agent with AI Endpoints, export your API key:

export OVH_AI_ENDPOINTS_ACCESS_TOKEN="your_api_key_here"

ℹ️ Docker Agent uses the token_key field in the provider configuration to know which environment variable holds the API token, here we name it OVH_AI_ENDPOINTS_ACCESS_TOKEN. ℹ️

Configure the provider and models

AI Endpoints is fully integrated in docker agents. That’s mean that the configuration is very easy as you can see in the official documentation.

One of the strengths of AI Endpoints is the ability to choose the right model for each task. This allows each agent to use a model optimized for its specific role rather than forcing a single model to handle every step of the workflow. Here we use gpt-oss-120b for the crawler, which handles documentation analysis, web browsing and reasoning, while Qwen3.5-397B-A17B is used for the coder due to its strong code generation capabilities.

Create a team of agents for coding

Let’s build a two-agent team: a crawler that fetches documentation from the web, and a coder that turns that documentation into working code.

The crawler uses the fetch toolset to read URLs and passes the extracted context to the coder via the sub_agents mechanism. The coder uses the filesystem toolset to create files and the shell toolset to execute or validate them when needed.

agents:
  crawler: 
    model: ovhcloud/gpt-oss-120b
    description: Documentation crawler
    instruction: |
      You are a documentation crawler.
      Step 1: use the fetch tool to read the URLs provided by the user and     extract the relevant information.
      Step 2: you MUST invoke the coder sub-agent tool with the full context you gathered, so it can write the code.
      Do NOT write the code yourself. Always invoke the coder agent.
    sub_agents: [coder]
    toolsets:
     - type: filesystem
     - type: fetch

coder:
  model: ovhcloud/Qwen3.5-397B-A17B
  description: Coder
  instruction: |
    Write code based on the context provided.
    Ensure code quality and maintainability.
    Save files to disk using the filesystem toolset, use the current path.
   toolsets:
    - type: filesystem
    - type: fetch
    - type: shell

As you can see using an OVHcloud model is very easy: get the model name from the catalog and add ovhcloud/ to the name in the configuration file.

Run the agents

Once your configuration file is ready, run the team with:

docker agent run ovhcloud-agent.yml

Here is the Docker Agent in action:

Conclusion

In this post, we saw how Docker Agent makes it easy to build collaborative multi-agent teams (without requiring Docker engine) and how AI Endpoints fits in naturally thanks to its full OpenAI API compatibility.

AI Endpoints gives you the flexibility to choose the right model for each agent in a multi-agent workflow, all from a single provider configuration. Rather than relying on one model for every task, you can combine specialized models for research, reasoning, coding, content generation, or data processing.

The crawler/coder example shown here is just one illustration of this approach. The same multi-agent pattern can be applied to a wide range of workflows wherein specialized agents collaborate to complete complex tasks more efficiently.

Have questions or feedback? Join the dedicated #ai-endpoints channel on our Discord server.

To learn more about AI Endpoints, please explore our previous blog posts.

What’s new with the OVHcloud Developer Advocate team – June 2026

Stéphane Philippart — Tue, 30 Jun 2026 13:07:28 +0000

Every month, the OVHcloud Developer Advocate team creates content, shares knowledge, and connects with the tech community. Here’s a look at what we did in June 2026. 🚀

🎙️ “Tranches de Tech” – Our monthly podcast

A new episode of our French-language podcast Tranches de Tech 🥑 just dropped!

🎧 Episode 29: Dessiné c’est gagné !

This episode of “Tranche de Tech” features host Stéphane, co-host Aurélie, and guest Ane, a front-end developer at Datadog, who discuss visual thinking and sketchnoting, Ane’s experience contributing to the Chromium open-source project, and the growing impact of AI on software development practices. A significant portion of the conversation explores how AI tools are both accelerating code generation and creating challenges for open-source communities, including a flood of low-quality pull requests and security vulnerabilities being discovered (and sometimes irresponsibly disclosed) by AI systems. The episode wraps up with reflections on the instability of GitHub, the financial struggles facing tech conferences, and a shared concern about preserving the human and collaborative elements of the developer profession.

See episode shownotes

📺 Live on Twitch

We streamed live on Twitch this month! Here’s what we covered:
🎥 Stéphane Philippart discussed with Fanny Bouton about quantum computing at OVHcloud.
Catch the replay on YouTube ▶️.

🎤 Conference Talks

The team hit the road (and the stage) at several conferences this month:

🇫🇷 Paris JUG, Paris 🇫🇷

Stéphane gave a talk: Toi aussi crée ta CLI boostée à l’IA avec Picocli

🇫🇷 DevQuest Niort, Niort 🇫🇷

Aurélie Vache gave two talks:

Stéphane Philippart gave a workshop: Développer avec l’IA : et si c’était aussi simple qu’ajouter une librairie ?

🇫🇷 BreizhCamp, Rennes 🇫🇷

Stéphane Philippart gave two talks

🤝 Community Engagement

We connected with the community through more than just conferences:

🏫 Meetup Tech Speak’Her – June, 4 – Toulouse, France 🇫🇷

Aurélie was a member of the jury during the “Tremplin DevFest Toulouse” evening, organized by the Tech Speak’her association.

During ths “pitch contest” event, eight women from the region delivered their pitches, and the jury had the difficult task of selecting the winner. She will have the opportunity to give a talk at DevFest Toulouse, while the two runners-up will be invited to present their talks at a Tech Speak’her meetup.

📝 Our latest blog posts

Here are the articles our team published on the OVHcloud Blog this month.

📝 Secure Image Signing with Cosign and OVHcloud KMS – by Aurélie Vache

This article by Aurélie Vache explains how to use Cosign, a tool from the Sigstore project for signing and verifying OCI container images, together with the OVHcloud Key Management Service (KMS) through a dedicated plugin. It walks through the full workflow: generating a key pair stored securely in OVHcloud KMS, signing a container image, and verifying the signature. The main benefit is keeping cryptographic signing keys out of local environments and CI/CD variables, reducing secret sprawl and improving supply chain security.

📝 Terraform S3 state locking with OVHcloud Object Storage – by Aurélie Vache

This article by Aurélie Vache explains how to enable native S3 state locking for Terraform and OpenTofu using OVHcloud’s S3-compatible Object Storage, made possible by the recent addition of conditional writes support. When activated via the use_lockfile = true backend option, Terraform creates a .tflock file during an operation, preventing any concurrent apply from modifying the state file simultaneously and avoiding state corruption. The post walks through the full setup and demonstrates the locking mechanism in action with practical CLI examples.

📝 How to process large AI requests with Batch Mode on OVHcloud AI Endpoints – by Stéphane Philippart

This article by Stéphane Philippart introduces the Batch Mode feature (currently in beta) for OVHcloud AI Endpoints, which allows processing large volumes of LLM requests asynchronously by uploading a JSONL file, submitting a batch job, and retrieving results within up to 24 hours , at 50% lower cost than synchronous requests. The post walks through the full Python workflow using the OpenAI-compatible SDK: uploading the input file, creating and polling the batch, and downloading the results. It’s ideal for non-time-sensitive workloads like bulk classification, translation, or dataset generation, but not suited for real-time use cases like chatbots.

💻 Code Samples and Open Source

We regularly publish code samples and open-source projects to help you get started with OVHcloud products. Check out our public-cloud-examples repository on GitHub.

New this month:

🆕 New release: OVHcloud Pulumi provider v2.14.0
🆕 Contributions in the new Sigstore cosign plugin for OVHcloud KMS
🆕 Contributions in the okms-k8s-encryption-provider

🗓️ Coming up next

Here’s a sneak peek at what’s coming next.

🗓️ – July, 2 & 3 – Sunny Tech (Montpellier, France)

🎤 Aurélie Vache is giving two talks:
– Comprendre Kyverno de manière visuelle (Thursday the 2nd)
– J’ai packagé mon application en image Docker, et maintenant ? (Friday the 3rd)

🎤 Stéphane Philippart is giving one talk (Thursday the 2nd): 🧰 Les dev containers, la boîte à outils ultime pour les devs ?

🗓️ – July, 6, 7 & 8 – Riviera Dev (Sophia-Antipolis, France)

🎤 Aurélie Vache is giving two talks:
– Questions pour un conteneur – édition Supply Chain » (Tuesday the 7th)
– Comprendre Kubernetes de manière visuelle (Tuesday the 7th)

🎤 Stéphane Philippart is giving one workshop (Tuesday the 7th): Créer un assistant IA dans son terminal avec Java, Picocli et Quarkus

🗓️ – July, 8, 9 & 10 – We are developers (Berlin, Germany)

🎤 Aurélie Vache is giving one talk (Thursday the 9th): Understanding Kubernetes in a visual way

🗓️ New “Tranches de Tech” podcast episode

🎧 All episodes are available on Ausha and all your favorite podcast applications!

💬 Stay in Touch

Want to chat with us, share your thoughts, or just say hi? Here’s how to get in touch with the Developer Advocate team:

🟣 Discord: OVHcloud Discord server
🐦 X / Twitter: @OVHcloud
💼 LinkedIn: OVHcloud LinkedIn
🐙 GitHub: github.com/ovh

See you next month! 👋

🎙️ Tranches de Tech #29 – Dessiné c’est gagné !

Stéphane Philippart — Thu, 04 Jun 2026 06:40:00 +0000

👤 Invitée : Ane Diaz
- X: @ane_naiz
- Bluesky : @ane-naiz
- LinkedIn : https://www.linkedin.com/in/ane-diaz-de-tuesta-37785252
🗓️ Date d’enregistrement : 29 mai 2026
🎧 Lien vers l’épisode

👤 Présentation d’Ane – ⏱️ 1″

📰 News Techs

🤖 Intelligence Artificielle – ⏱️ 55″30

Batch mode pour AI Endpoints

Dispo du Qwen3.5-397B-A17B dans AI Endpoints

Claude Code found a 23-year-old Linux kernel bug in a bash for loop

https://edera.dev/stories/the-price-of-a-zero-day-vulnerability-is-an-api-call

👩‍💻 Développement – ⏱️ 1h06″46

Ghostty is leaving GitHub

☁️ Cloud – ⏱️ 1h12″46

Navigating OVHcloud Enterprise File Storage (EFS) with Trident CSI On Kubernetes clusters (MKS)

https://dev.to/aurelievache/understanhttps://blog.ovhcloud.com/navigating-ovhcloud-enterprise-file-storage-efs-with-trident-csi-on-kubernetes-clusters-mks/ding-kubernetes-part-61-kubernetes-136-changelog-3cak

Kubernetes 1.36 – changelog in a visual way

https://dev.to/aurelievache/understanding-kubernetes-part-61-kubernetes-136-changelog-3cak

🔐 Sécurité – ⏱️ 1h16″

Copy.fail

https://blog.ovhcloud.com/copy-fail-cve-2026-31431-how-to-rapidly-protect-ovhcloud-mks-clusters-from-the-linux-kernel-zero-day

http://updog.ai

🎤 Conférences / meetup – ⏱️ 1h22″50

Why there won’t be a devopsdays Amsterdam this year

https://www.linkedin.com/pulse/why-wont-devopsdays-amsterdam-year-devopsams-43wle

Pas d’Agile Tour Toulouse cette année – Annulation

https://www.linkedin.com/posts/apr%C3%A8s-plusieurs-%C3%A9changes-nous-avons-d%C3%A9cid%C3%A9-share-7457517909318430720-6AdX

💡 Retrouvez l’ensemble des autres épisodes ici : https://smartlink.ausha.co/tranches-de-tech 💡

How to process large AI requests with Batch Mode on OVHcloud AI Endpoints

Stéphane Philippart — Mon, 01 Jun 2026 12:26:07 +0000

Let’s say you have 20,000 support tickets to classify before tomorrow morning, or a full product catalog to translate without manually sending each request one by one. That kind of workload can quickly become slow, repetitive and difficult to manage.

Batch Mode is designed to help in exactly this type of scenario.

What is Batch Mode?

When working with LLMs, you often send requests one by one through synchronous endpoints like /v1/chat/completions or /v1/responses. This works fine for real-time use cases, but what can you do if you need to process hundreds or thousands of prompts? Sending them individually is slow, and you’re limited by rate limits.

Batch mode solves this problem. Instead of sending requests one at a time, you upload a file containing all your requests, submit a batch job, and get the results back asynchronously, within a maximum of 24 hours. And here’s the cherry on top: batch mode is 50% cheaper than synchronous requests. Since the platform can schedule your workload more efficiently, you benefit from a significant cost reduction.

This is ideal for:

📊 Bulk classification or summarization tasks
🌍 Large-scale translation jobs
📝 Generating descriptions for a product catalog
🧪 Evaluating model outputs on a test dataset

ℹ️ The Batch API is compatible with the OpenAI Batch API format, so you can use the official OpenAI SDK to interact with it.

When not to use Batch Mode!

Batch Mode is designed for large workloads that do not need an immediate response. This being said, it is not the right choice for real-time use cases such as chatbots, live customer support, interactive assistants or applications where users expect an answer within seconds. For those scenarios, synchronous endpoints remain more appropriate. Use Batch Mode when your requests can be processed asynchronously and retrieved later.

ℹ️ The Batch API is currently in beta. You can find more information about the beta on the dedicated page.

Prerequisites for using Batch Mode

Before getting started, you’ll need:

An AI Endpoints API key
Python 3.10+ installed
The openai Python package

⚠️ You can generate your API key from the AI Endpoints console.

Install the dependency:

pip install openai

Set up your environment variables:

export OVH_AI_ENDPOINTS_ACCESS_TOKEN='your_api_key'
export OVH_AI_ENDPOINTS_BASE_URL='https://oai.endpoints.kepler.ai.cloud.ovh.net/v1'

Step 1: Prepare the Input File

The input file uses the JSON Lines format (.jsonl). Each line is a self-contained request with a unique custom_id that lets you match results to their original requests.

Here’s an example requests.jsonl:

{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-oss-20b", "messages": [{"role": "user", "content": "Summarise the plot of Hamlet in two sentences."}]}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-oss-20b", "messages": [{"role": "user", "content": "Translate 'Good morning' into French, Spanish and German."}]}}

Key points:

Each custom_id must be unique within a batch
The model field must reference a model available in the AI Endpoints catalog
The url field indicates which endpoint to call

Step 2: Upload the File and Create the Batch

Here’s the complete Python code that handles the full workflow: upload, create, poll, and download:

import os
import time

from openai import OpenAI

# Load environment variables
_OVH_AI_ENDPOINTS_ACCESS_TOKEN = os.environ["OVH_AI_ENDPOINTS_ACCESS_TOKEN"]
_OVH_AI_ENDPOINTS_BASE_URL = os.environ["OVH_AI_ENDPOINTS_BASE_URL"]

# Initialize the OpenAI-compatible client targeting OVHcloud AI Endpoints
client = OpenAI(
    base_url=_OVH_AI_ENDPOINTS_BASE_URL,
    api_key=_OVH_AI_ENDPOINTS_ACCESS_TOKEN,
)

# 1. Upload the input JSONL file with purpose="batch"
print("📤 Uploading input file...")
batch_input_file = client.files.create(
    file=open("requests.jsonl", "rb"),
    purpose="batch",
)
print(f"✅ Uploaded file id: {batch_input_file.id}")

# 2. Create the batch referencing the uploaded file
print("🚀 Creating batch...")
batch = client.batches.create(
    input_file_id=batch_input_file.id,
    endpoint="/v1/chat/completions",
    completion_window="24h",
    metadata={"description": "Batch mode example - OVHcloud AI Endpoints"},
)
print(f"✅ Batch created: {batch.id} (status: {batch.status})")

# 3. Poll the batch status until it reaches a terminal state
print("⏳ Polling batch status...")
while True:
    current = client.batches.retrieve(batch.id)
    print(f"   status={current.status} counts={current.request_counts}")
    if current.status in ("completed", "failed", "expired", "cancelled"):
        break
    time.sleep(30)

# 4. Download the results (and errors if any)
final = client.batches.retrieve(batch.id)

if final.output_file_id:
    print("📥 Downloading results.jsonl...")
    output = client.files.content(final.output_file_id)
    with open("results.jsonl", "wb") as f:
        f.write(output.read())
    print("✅ Results written to results.jsonl")

if final.error_file_id:
    print("🐛 Downloading errors.jsonl...")
    errors = client.files.content(final.error_file_id)
    with open("errors.jsonl", "wb") as f:
        f.write(errors.read())
    print("🐛 Errors written to errors.jsonl")

print(f"🏁 Final batch status: {final.status}")

Let’s break down the key steps:

Upload the input file

batch_input_file = client.files.create(
    file=open("requests.jsonl", "rb"),
    purpose="batch",
)

The purpose=”batch” parameter tells the API that this file will be used as batch input.

Create the batch

batch = client.batches.create(
    input_file_id=batch_input_file.id,
    endpoint="/v1/chat/completions",
    completion_window="24h",
)

The completion_window=”24h” means the batch will be stopped after 24 hours if not completed.

Poll the batch status

while True:
    current = client.batches.retrieve(batch.id)
    print(f"   status={current.status} counts={current.request_counts}")
    if current.status in ("completed", "failed", "expired", "cancelled"):
        break
    time.sleep(30)

The client.batches.retrieve(batch.id) call returns the current state of the batch. The request_counts field gives you a breakdown of how many requests are completed, failed, or still in progress, useful for monitoring large batches.

The possible terminal states are:

completed: all requests have been processed successfully
failed: the batch encountered a fatal error
expired: the batch exceeded the completion_window duration
cancelled: the batch was manually cancelled via the API

We poll every 30 seconds here, but you can adjust this interval depending on your use case. For very large batches, a longer interval (e.g., 60–120 seconds) is more appropriate.

Download the results

final = client.batches.retrieve(batch.id)

if final.output_file_id:
    output = client.files.content(final.output_file_id)
    with open("results.jsonl", "wb") as f:
        f.write(output.read())

Once the batch is complete, the output_file_id field contains the ID of the results file. You download it using client.files.content() which returns the raw file content.

Download the errors (if any)

if final.error_file_id:
    errors = client.files.content(final.error_file_id)
    with open("errors.jsonl", "wb") as f:
        f.write(errors.read())

If some requests in your batch failed (e.g., invalid model name, malformed input, token limit exceeded), their details will be available in a separate error file. The error_file_id will be None if all requests succeeded. Each line in errors.jsonl contains the custom_id of the failed request along with the error details, making it easy to identify and retry only the failed ones.

Step 3: Read the Results

The output file (results.jsonl) contains one JSON object per line. Each object includes:

The custom_id matching your original request
The full response body (same format as a synchronous /v1/chat/completions responses)

Here’s what a result looks like:

{
  "id": "964e007472a557240221910ba143bb03",
  "custom_id": "request-1",
  "response": {
    "status_code": 200,
    "body": {
      "id": "chatcmpl-9879ebff777795a3",
      "choices": [
        {
          "index": 0,
          "message": {
            "role": "assistant",
            "content": "Hamlet, the Prince of Denmark, is driven to madness and vengeance after learning that his father was murdered by his uncle Claudius..."
          },
          "finish_reason": "stop"
        }
      ],
      "model": "gpt-oss-20b",
      "usage": {
        "prompt_tokens": 78,
        "completion_tokens": 297,
        "total_tokens": 375
      }
    }
  },
  "error": null
}

If some requests fail, the errors.jsonl file will contain details about what went wrong for each failed request.

Other Examples Available

The AI Endpoints – Batch mode guide also contains examples in:

JavaScript: using the OpenAI Node.js SDK
Pure HTTP requests: using curl without any framework, if you prefer a language-agnostic approach

These examples demonstrate that you can use the Batch API from any language or tool that can make HTTP requests, since it follows the standard OpenAI-compatible API format.

Conclusion

Batch mode is a powerful feature when you need to process large volumes of repetitive, non time-sensitive inference requests, without worrying about rate limits or timeout issues. Upload your file, submit the batch, and come back later for the results, it’s as simple a solution as that.

The OpenAI-compatible API makes it straightforward to integrate into existing workflows, and with examples available in Python, JavaScript, and raw HTTP, you can use whichever approach fits your stack best.

You have a dedicated Discord channel (#ai-endpoints) on our Discord server, see you there!

For more info on AI Endpoints, find our previous blog posts.

Find the full code example in the GitHub repository: public-cloud-examples/ai/ai-endpoints/batch-mode.

What’s new with the OVHcloud Developer Advocate team – May 2026

Stéphane Philippart and Aurélie Vache — Wed, 27 May 2026 14:06:16 +0000

Every month, the OVHcloud Developer Advocate team creates content, shares knowledge, and connects with the tech community. Here’s a look at what we did in May 2026. 🚀

🎙️ “Tranches de Tech” – Our monthly podcast

A new episode of our French-language podcast Tranches de Tech 🥑 just dropped!

🎧 Episode 28: La dream team au complet

In this episode of Tranche de Tech, Stephane and Aurelie welcome former team member Thierry for a wide-ranging conversation on tech, conferences, and community.
They reflect on recent events like Devoxx France and MiXiT, sharing highlights from talks, trends, and the growing role of AI in today’s software landscape.
The discussion explores how AI is evolving from pure model innovation toward software patterns, developer tooling, and more practical, structured usage.
Thierry also introduces CALM, his weekly Twitch show, and revisits the inspiring story behind Mixtine, a kids’ tech initiative that brings programming and digital culture to younger generations.
More than a tech recap, this episode is a celebration of curiosity, knowledge sharing, and the importance of building inclusive communities around technology.

See episode shownotes

📺 Live on Twitch

We streamed live on Twitch this month! Here’s what we covered:
🎥 Rémy Vandepoel discussed with Magali De Labareyre about ou human resource management and the OVHcloud culture.
Catch the replay on YouTube ▶️.

🎤 Conference Talks

The team hit the road (and the stage) at several conferences this month:

📝 Our latest blog posts

Here are the articles our team published on the OVHcloud Blog this month.

📝 Devoxx France 2026: feedback and highlights – by Aurélie Vache

This blog post explains what stood out at Devoxx France 2026, from major conference highlights to the key technology trends shaping the developer ecosystem.
It shows how AI dominated the event, with strong attention on agentic systems, governance, production use cases, and the broader impact of AI on software engineering.
The article also highlights OVHcloud’s strong presence through its booth, community engagement, and a large number of accepted talks and speakers.
Beyond AI, it captures wider themes such as platform engineering, security, cloud resilience, developer experience, open source, and digital sovereignty.
Overall, it offers both a conference recap and a clear snapshot of where the industry is heading in 2026.

📝 Navigating OVHcloud Enterprise File Storage (EFS) with Trident CSI On Kubernetes clusters (MKS) – by Aurélie Vache

This blog post explains how to connect OVHcloud Enterprise File Storage (EFS) to Managed Kubernetes Service (MKS) clusters using NetApp Trident CSI.
It walks readers through provisioning the required OVHcloud resources with Terraform, including EFS, OAuth2 credentials, IAM policies, and vRack Services networking.
The article then shows how to install Trident, configure the backend securely, and integrate EFS as dynamic shared storage for Kubernetes workloads.
It highlights key capabilities such as high availability, predictable performance, and ReadWriteMany access for production-ready persistent storage.
Overall, it serves as a practical step-by-step guide for teams that need scalable shared file storage in OVHcloud Kubernetes environments.

📝 Copy.Fail (CVE-2026-31431): How to Rapidly Protect OVHcloud MKS Clusters from the Linux Kernel Zero-Day – by Aurélie Vache

This blog post explains how the Copy.Fail (CVE-2026-31431) Linux kernel zero-day can rapidly compromise systems through reliable privilege escalation.
It shows how the flaw abuses the algif_aead crypto module to hijack trusted binaries in memory without changing files on disk, making detection harder.
The article highlights the risks for Kubernetes clusters, CI/CD runners, shared environments, and multi-tenant infrastructure.
It also provides an immediate DaemonSet-based mitigation that OVHcloud MKS users can deploy while waiting for patched cluster versions.
Overall, it serves as a practical guide to reducing exposure quickly, while reminding readers that the official security patch is the proper long-term fix.

🎙️ Podcasts / Videos 📺

Aurélie was invited in the podcast “Biztrot Café #2 – IA Gen or not IA Gen ?“.
During this second episode of the podcast, Marian, Julien, Jean-Phi and Aurélie discussed about a recurring question: “AI Gen or not AI Gen?” and the growing use of generative AI in the tech community. Together, they discuss how AI is being used to create conference talks, presentation slides, blog posts, and even sketchnotes. They share both the benefits and the limitations of these tools, highlighting how generative AI can accelerate content creation while still requiring careful review, creativity, and significant iteration to achieve high-quality results.
Watch the replay on YouTube ▶️.

🗓️ Coming up next

Here’s a sneak peek at what’s coming next.

🗓️ – June, 3 – 1h PM CET – Very Tech Talk Twitch about Quantum

📺 OVHcloud Twitch channel

🗓️ – June, 11 & 12 Dev Quest Niort (Niort, France)

🎤 Aurélie Vache is giving one talk (Thursday the 11th at 2h30 PM): Comprendre Kubernetes de manière visuelle

🎤 Stéphane Philippart is giving one workshop (Friday the 12th at 10h AM): Ajouter de l’IA à nos applications : et si c’était aussi simple qu’ajouter une librairie ?

🗓️ – June, 24, 25 & 26 – BreizhCamp (Rennes, France)

🎤 Stéphane Philippart is giving two talks:
– JBang, un fichier Java pour les gouverner tous ? 💍 (Thurdsay the 25th at 5h PM)
– 🧰 Les dev containers, la boîte à outils ultime pour les devs ? (Friday the 26th at 4h PM)

🗓️ New “Tranches de Tech” podcast episode

🎧 All episodes are available on Ausha and all your favorite podcast applications!

💬 Stay in Touch

Want to chat with us, share your thoughts, or just say hi? Here’s how to get in touch with the Developer Advocate team:

🟣 Discord: OVHcloud Discord server
🐦 X / Twitter: @OVHcloud
💼 LinkedIn: OVHcloud LinkedIn
🐙 GitHub: github.com/ovh

See you next month! 👋

🎙️ Tranches de Tech #28 – La dream team au complet

Stéphane Philippart — Mon, 11 May 2026 10:13:46 +0000

👤 Invitée : Thierry CHANTIER
- Bluesky : @titimoby
- LinkedIn : https://www.linkedin.com/in/thierrychantier/
🗓️ Date d’enregistrement : 30 avril 2026
🎧 Lien vers l’épisode

👤 Présentation de Thierry – ⏱️ 1″15s

📰 News Techs

🤖 Intelligence Artificielle – ⏱️ 43″35s

Anthropic Claude Code leak

https://www.reddit.com/r/ClaudeAI/comments/1s9d9j9/claude_code_source_leak_megathread/

Qwen 3.6

Quantization from the ground up

https://ngrok.com/blog/quantization

MCP is dead. Long live the CLI

https://ejholmes.github.io/2026/02/28/mcp-is-dead-long-live-the-cli.html

👩‍💻 Développement – ⏱️ 1h07″26s

Thoughts on OpenAI acquiring Astral and uv/ruff/ty

https://simonwillison.net/2026/Mar/19/openai-acquiring-astral

SpaceX is working with Cursor and has an option to buy the startup for $60B

https://techcrunch.com/2026/04/21/spacex-is-working-with-cursor-and-has-an-option-to-buy-the-startup-for-60-billion/

☁️ Cloud – ⏱️ 1h15″15s

OVHcloud Kubernetes Review: Europe’s Quiet Powerhouse

https://www.eucloudcost.com/blog/ovhcloud-cluster

Discovering the External Secrets Operator (ESO) OVHcloud provider to manage your Kubernetes secrets

https://blog.ovhcloud.com/discover-the-external-secret-operator-eso-ovhcloud-provider-to-manage-your-kubernetes-secrets-%f0%9f%8e%89/

Secure your Software Supply Chain with OVHcloud Managed Private Registry (MPR)

https://blog.ovhcloud.com/secure-your-software-supply-chain-with-ovhcloud-managed-private-registry-mpr/

🎤 Conférences / meetup – ⏱️ 1h21″25s

https://developers.events/

Le prochain Riviera Dev

https://www.rivieradev.fr

💡 Retrouvez l’ensemble des autres épisodes ici : https://smartlink.ausha.co/tranches-de-tech 💡

What’s new with the OVHcloud Developer Advocate team – April 2026

Stéphane Philippart — Wed, 29 Apr 2026 12:03:38 +0000

Every month, the OVHcloud Developer Advocate team creates content, shares knowledge, and connects with the tech community. Here’s a look at what we did in April 2026. 🚀

🎙️ “Tranches de Tech” – Our monthly podcast

A new episode of our French-language podcast Tranches de Tech 🥑 just dropped!

🎧 Episode 27: Tranches de Tech 26 – Poppy au service des autres

This episode of Tranches de Tech features Annabelle Koster, who shares her journey from tech recruiter to community ambassador, highlighting how she overcame impostor syndrome by actively learning and engaging with developers. She emphasizes the importance of community, conferences, and volunteering in building meaningful connections and personal growth. The discussion also explores the evolving role of AI as a productivity tool in her daily work. Ultimately, the episode underlines that, despite technological advances, human interaction, sharing, and mutual support remain at the heart of the tech ecosystem.

📺 Live on Twitch

We streamed live on Twitch this month! Here’s what we covered:
🎥 Rémy Vandepoel discussed with Antonin Anchisi and Aurélie Vache about our Manages Kubernetes Service (MKS) and some feedbacks about the KubeCon Europe 2026.
Catch the replay on YouTube ▶️.

🎤 Conference Talks

The team hit the road (and the stage) at several conferences this month:

🇫🇷 MiXiT – Lyon, France 🇫🇷

Aurélie Vache gave a talk: Comprendre Kubernetes de manière visuelle

Stéphane Philippart gave a workshop: Développer avec l’IA : et si c’était aussi simple qu’ajouter une librairie ?

🇫🇷 Devoxx France – Paris, France 🇫🇷

Aurélie Vache gave a talk: Question pour un cluster Kubernetes : Quiz sur Kubernetes & ses concepts

Stéphane Philippart gave a talk and a workshop (with Mathieu Busquet):
– 🤖 Apprendre à notre IA à … apprendre 🧠
– Développer avec l’IA : et si c’était aussi simple qu’ajouter une librairie ?

📝 Our latest blog posts

Here are the articles our team published on the OVHcloud Blog this month.

📝 Extract Text from Images with OCR using Python and OVHcloud AI Endpoints — by Stéphane Philippart

This blog post explains how to perform OCR (Optical Character Recognition) using a vision-capable language model via AI Endpoints and Python. It shows that, instead of traditional OCR tools, developers can send images directly to a multimodal model using the OpenAI-compatible API to extract text while preserving layout. The tutorial walks through a simple Python script, including environment setup, image encoding in base64, and API calls. Overall, it highlights how modern vision LLMs simplify OCR workflows, making text extraction more flexible and easier to implement.

📝 Discover the External Secret Operator (ESO) OVHcloud Provider to manage your Kubernetes secrets 🎉 – by Aurélie Vache

This blog post introduces a new provider for the External Secrets Operator (ESO) that integrates directly with OVHcloud Secret Manager, simplifying how secrets are handled in Kubernetes. It explains how ESO works by synchronizing secrets from external systems into Kubernetes and automatically updating them when changes occur. The tutorial walks through the full setup, including creating a secret in OVHcloud, configuring authentication, and deploying resources like ClusterSecretStore and ExternalSecret. Overall, the article highlights how this new provider streamlines secret management and improves integration between OVHcloud services and Kubernetes environments.

📝 KubeCon + CloudNativeCon Europe 2026 in Amsterdam: feedback and highlights by Aurélie Vache and Rémy Vandepoel

The post highlights KubeCon + CloudNativeCon Europe 2026 as strongly shaped by the rise of AI, pushing cloud-native toward an “AI-native” paradigm. OVHcloud emphasizes sovereign cloud principles, focusing on openness, reversibility, and performance. The event featured rich technical discussions, demos, and exchanges around Kubernetes and demanding workloads. It also underscored the importance of open-source collaboration within the CNCF ecosystem. Finally, OVHcloud’s booth and activities aimed to make these topics more accessible and tangible.

🗓️ Coming up next

Here’s a sneak peek at what’s coming next.

🗓️ – May, 6 & 7 – Devoxx UK, in London

🎤 Stéphane Philippart is giving one talk (Wednesday the 6th at 6PM): 🧰 Dev Containers: the ultimate toolbox for developers?

🗓️ – May, 13 – 1h PM CET – Very Tech Talk Twitch about Human Resources

📺 OVHcloud Twitch channel

🗓️ – May, 19 & 20 – Kubernetes Community Days in Helsinki

🎤 Aurélie Vache is giving one talk (Wednesday the 20th at 2h30 PM): The Ultimate Kubernetes Challenge: An Interactive Trivia Game on concepts, components, usage…

🗓️ – May, 21 & 22 – Devops days in Geneva

🎤 Stéphane Philippart is giving one workshop (Thursday the 21th at 2h55 PM): Développer avec l’IA : et si c’était aussi simple qu’ajouter une librairie ?

🗓️ New “Tranches de Tech” podcast episode

🎧 All episodes are available on Ausha and all your favorite podcast applications!

💬 Stay in Touch

Want to chat with us, share your thoughts, or just say hi? Here’s how to get in touch with the Developer Advocate team:

🟣 Discord: OVHcloud Discord server
🐦 X / Twitter: @OVHcloud
💼 LinkedIn: OVHcloud LinkedIn
🐙 GitHub: github.com/ovh

See you next month! 👋

🎙️ Tranches de Tech #27 – Poppy au service des autres

Stéphane Philippart — Tue, 07 Apr 2026 10:11:07 +0000

👤 Invitée : Annabelle KOSTER
- X : @AnnabelleKoster
- LinkedIn : https://www.linkedin.com/in/annabelle-koster/
🗓️ Date d’enregistrement : 20 mars 2026
🎧 Lien vers l’épisode