Applications are now open for the OVHcloud Startup Program’s third accelerator under the Partner Network for Scaleups brand (formerly known as Fast Forward Accelerator), this time dedicated to healthcare scaleups.

Following the success of the AI and Blockchain accelerators launched last year, the Healthcare Accelerator will support healthtech and medtech scaleups looking to grow with secure, scalable and compliant cloud infrastructure. The 10-week program will run from September to November 2026, with applications open until July 7, 2026.

Healthcare scaleups often face a specific challenge, and building innovative technology is only part of the journey. To grow, they also need to navigate complex healthcare ecosystems, data requirements, infrastructure needs and go-to-market barriers. The OVHcloud Healthcare Accelerator is designed to help them move through those challenges with cloud credits, mentoring, technical support and access to relevant partners.

Key partners supporting the accelerator include APHP, Guy’s and St Thomas’ NHS Foundation Trust, Dräger, Global Good, and Empact Ventures.

“The OVHcloud Startup Program is excited to move the Healthcare Accelerator under the Partner Network brand, offering a dedicated program for our scaleup customers that includes go-to-market assistance as well as migration support, financial incentives, and training and certification for cloud solutions,” says Philip Marais, Global Startup Program Director, OVHcloud.

The Healthcare Accelerator brings together OVHcloud’s core strengths — data sovereignty, price-performance, energy efficiency, technical freedom, personal support and secure cloud services — with dedicated go-to-market support for healthcare scaleups.

The 10-week accelerator specifically offers:

• €50k in free cloud credits to use on our Public Cloud solutions. This is in addition to Startup Program credits but the maximum total credits that can be allocated remains €100k.
• Deep-dives into healthcare technology, GTM strategies, sales training, etc.
• Workshops on GTM, sales, investor readiness, and marketing to boost growth
• 1-on-1 mentoring from experts
• Engagement with corporates for possible POCs, including a POC opportunity with Guy’s and St Thomas’ NHS Foundation Trust
• Engagement with Venture Capitalists (VCs) for possible funding
• 15 free super connections for market access & funding provided by Empact Ventures
• An Impact Interview in Global Good promoted to its 22k+ combined social media followers

Up to 20 startups will be selected for the cohort of the Healthcare Accelerator. Applications opened on May 19, 2026, and entries close on July 7, 2026. Selected participants will be announced on July 23, 2026.

The 10-week program is divided into three phases:

• Phase I – Go-to-Market Focus on refining your product-market fit, marketing, and go-to-market strategy. You’ll work with our team to sharpen your positioning and business foundations.
• Phase II – Build Deep dive into healthcare technology and cloud integration. You’ll collaborate with our technical teams to optimize your infrastructure and unlock the full potential of OVHcloud solutions.
• Phase III – Scale Prepare for investor engagement and scalable growth. This phase includes sales strategy and investor readiness.

The accelerator program includes 1-on-1 mentoring from OVHcloud and external experts who will be matched with participants based on their needs. The program is designed to be agile, requiring only a few hours a week or less, but can scale to support you as needed.

Applications will need to meet the following criteria to be selected:

• You must be a Startup Program member that has been active in the program or as an OVHcloud customer for at least a month (not a member? Apply now)
• Your startup must be working in the healthcare industry
• Preference will be given to Scale level members of the Startup Program

We are specifically looking for healthcare scaleups (healthtechs/medtechs) for our partners that comply with healthcare data regulations and are thinking about sustainability within healthcare across these areas:

• Reducing waiting lists: Improving access to diagnosis, treatment, and surgery so patients are seen faster, especially where delays can affect outcomes such as cancer services.
• Addressing health inequalities: Reducing differences in healthcare access, quality, and outcomes between different communities, income groups, ethnicities, or regions.
• AI and automation: Using artificial intelligence and automated systems to improve efficiency, support clinical decisions, streamline administration, and enhance patient care.
• Remote patient monitoring: Using digital tools and connected devices to monitor patients safely at home instead of keeping them in hospital when appropriate.
• Medical devices: Developing or adopting equipment, tools, and technologies used to diagnose, monitor, or treat patients.
• Respiratory and cardiac areas: Innovations focused on heart, lung, and critical care services, including advanced treatments, diagnostics, and specialist pathways.
• Emergency care: Improving urgent and emergency services such as emergency departments, ambulance pathways, triage, and rapid treatment systems.
• Genomics and Cell & Gene Therapy: Using genetic science and advanced therapies to diagnose disease earlier and provide highly targeted or potentially curative treatments.

“Startups are an essential part of the healthcare ecosystem and one of the building blocks of the digital transformation economy,” says Olivier de la Boulaye, Global Sales Director Healthcare, OVHcloud. “But, getting them integrated into the healthcare system can be very challenging due to the complex regulatory and data requirements.

As a former startup, OVHcloud understands what founders and their teams need, but as a global organization which shares the ethos of innovation, transparency, and security, OVHcloud is in a unique position to help cross some of the barriers that startups face. We look forward to seeing the innovative scaleups that participate in our accelerator, and helping them with their go-to-market.”

Applications for the Healthcare Accelerator close on July 7, 2026. If your healthcare scaleup is ready to grow with secure cloud infrastructure, expert support and access to healthcare partners, apply today.

• 👤 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″

• https://www.zdnet.fr/pratique/jai-utilise-gemini-nano-banana-2-pour-creer-des-sketchnotes-voici-ce-qui-a-bien-fonctionne-et-ce-qui-a-tourne-au-comique-491797.htm
• https://www.linkedin.com/posts/katcosgrove_pull-request-process-share-7448418176419250176-k9Gh
• https://www.ifttd.io/episodes/azure-et-ia

📰 News Techs 

🤖 Intelligence Artificielle – ⏱️ 55″30

Batch mode pour AI Endpoints

• https://labs.ovhcloud.com/en/ai-endpoint-batch-api/
• https://docs.ovhcloud.com/en/guides/public-cloud/ai-machine-learning/ai-endpoints-batch-mode
• https://blog.ovhcloud.com/ovhcloud-ai-endpoints-batch-mode/

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

• https://www.ovhcloud.com/en/public-cloud/ai-endpoints/catalog/qwen-3-5-397b/
• https://blog.ovhcloud.com/extract-text-from-images-with-ocr-using-python-and-ovhcloud-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

• https://x.com/mitchellh/status/2049213597419774026
• http://updog.ai/

☁️ 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

• http://anediaz.com
• https://developers.events/

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 💡

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.

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:

🏴󠁧󠁢󠁥󠁮󠁧󠁿 Devoxx UK, Londres 🏴󠁧󠁢󠁥󠁮󠁧󠁿

Stéphane gave a talk: 🧰 Dev Containers: the ultimate toolbox for developers?

🇫🇮 KCD Helsinki, Helsinki 🏴󠁧󠁢󠁥󠁮󠁧󠁿

Aurélie Vache gave a talk: The Ultimate Kubernetes Challenge: An Interactive Trivia Game on concepts, components, usage…

🇨🇭 Devopsdays Geneva, Geneva 🇫🇷

Stéphane Philippart gave a workshop 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.

📝 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! 👋

At OVHcloud, we are proud to continuously evolve our infrastructure to help customers run their virtualized workloads with greater efficiency, flexibility and performance.

Today, we announce the availability of Premier 2027 hardware generation for Managed VMware vSphere solution, bringing significant improvements in compute power, memory capacity, storage capacity, and configuration flexibility.

The new generation improves upon its predecessors, being designed to better support enterprise virtualization environments, modern cloud workloads, as well as evolving VMware licensing models.

Managed VMware vSphere Welcomes a New Generation of Hardware

The Premier 2027 hardware range is replacing the previous Premier generation introduced in 2020, delivering stronger performance and broader configuration options for a wide variety of use cases.
Powered by the latest Intel Emerald Rapids processors, the new infrastructure enables customers to run demanding workloads while maintaining excellent price-performance efficiency.

Key highlights of the new generation include:

• Up to 40% more CPU cores compared to the previous Premier hardware
• Up to 1.5 TB RAM per host
• High-performance NVMe storage
• Up to 50 Gbps private bandwith included

Together, these improvements provide a more powerful and scalable foundation for virtual infrastructures hosted on OVHcloud, our latest pride and joy.

Premier 2027 Hardware Specifications

Latest Intel Emerald Rapids processors

The new servers use Intel Emerald Rapids CPUs, available in both mono-socket and bi-socket configurations, offering a flexible range from 16 to 72 cores.
This allows organizations to choose the right compute capacity for their workloads while benefiting from:

• up to 40% more cores compared to the previous Premier hardware
• up to 50% more CPU cache compared to the previous Premier hardware
• improved performance for compute-intensive applications
• broader servers’ options with global purpose (GP-x) and storage-optimized (STO-x) configurations.

Expanded memory capacity

Premier 2027 servers support up to 1.5 TB of RAM per host, enabling:

• larger virtual machines
• improved consolidation ratios
• better performance for memory-intensive applications such as databases and analytics platforms.

High-performance NVMe storage

The new hardware generation includes NVMe storage, enabling lower latency and faster data throughput.
Storage-optimized configurations (STO-x) leverage vSAN NVMe drives and can support up to 70 TB of storage per host.
This allows organizations to efficiently run storage-intensive workloads, including large databases (such as CRM), analytics platforms and enterprise applications (such as ERP).

High-speed networking

Premier 2027 servers feature up to 50 Gbps private networking included, providing a fast and reliable connectivity for virtual machines and distributed workloads.
This high bandwidth improves performance for applications requiring high data throughput, such as:

• distributed systems
• backup operations
• large-scale data processing.

View prices

Designed for a Wide Range of Enterprise Use Cases

The Premier 2027 hardware generation is designed to support a wide range of enterprise virtualization scenarios.

Cloud migration

Organizations migrating workloads from on-premises VMware environments to the cloud can benefit from performance consistency and familiar tooling, making migration simpler and reducing operational complexity.

The additional compute and memory capacity also make it easier to consolidate workloads and optimize infrastructure costs.

Disaster recovery and business continuity

For disaster recovery environments, infrastructure performance and scalability are critical.
With high-performance NVMe storage and up to 50 Gbps networking, the new hardware enables faster replication, improved recovery times and reliable failover environments.

Customers also benefit from compatible and resilient backup solutions such as Veeam Managed Backup, a managed backup solution to protect and back up their virtual machines, and/or Zerto, a replication platform installed and updated by OVHcloud, that allows them to resume activity quickly and easily.

Enterprise application hosting

Many enterprise applications require predictable performance and large memory capacity.
The Premier 2027 range allows customers to run demanding applications such as:

• large databases, such as CRM
• ERP systems
• data analytics platforms
• containerized workloads on VMware environments.

Seamless Infrastructure Evolution

Customers already running Managed VMware vSphere can integrate the Premier 2027 servers, either global purpose (GP-x) or storage-optimized (STO-x) configurations, into existing environments.

The new hardware is compatible with the current Premier generation, allowing the creation of heterogeneous clusters and enabling customers to scale their infrastructure without requiring a full migration.

This flexibility allows organizations to expand their infrastructure progressively while maintaining operational continuity.

Future-Ready Infrastructure

The Premier 2027 hardware generation provides a strong foundation for future virtualization needs.

With the latest CPU architecture, NVMe storage and high-speed networking, organizations can confidently support evolving workloads and future platform upgrades while maintaining the performance and reliability expected from enterprise VMware environments.

Conclusion

The introduction of Premier 2027 hardware for Managed VMware vSphere marks an important evolution of the OVHcloud Private Cloud platform.

With more powerful processors, increased memory and storage capacity, and flexible configurations, we are delighted to welcome this new generation of infrastructure enabling organizations to run modern workloads more efficiently, while maintaining full control of their VMware environments.

Discover the new Premier 2027 range: https://www.ovhcloud.com/en-ie/hosted-private-cloud/vmware/prices/

Find out more about VMware on OVHcloud solutions: https://www.ovhcloud.com/en-ie/solutions/vmware/

Chez OVHcloud, nous faisons évoluer en continu notre infrastructure afin de permettre à nos clients d’exécuter leurs charges de travail virtualisées avec toujours plus d’efficacité, de flexibilité et de performance.

Dans cette dynamique, nous annonçons aujourd’hui la disponibilité de la nouvelle génération de serveurs Premier 2027 pour la solution Managed VMware vSphere. Cette évolution apporte des améliorations significatives en matière de puissance de calcul, de capacité mémoire, de stockage et de flexibilité de configuration.

Conçue pour s’inscrire dans la continuité des versions précédentes, cette nouvelle génération a été pensée pour mieux répondre aux exigences des environnements de virtualisation d’entreprise, des charges de travail cloud modernes, ainsi qu’à l’évolution des modèles de licence VMware.

Managed VMware vSphere s’enrichit d’une nouvelle génération de serveurs

La gamme de serveurs Premier 2027 succède à la gamme Premier introduite en 2020. Elle propose des performances renforcées, tout en élargissant les possibilités de configuration afin de couvrir un large éventail de cas d’usage.
Grâce aux derniers processeurs Intel Emerald Rapids, cette infrastructure permet d’exécuter des charges de travail exigeantes, tout en conservant un excellent équilibre entre performance et coût.

Principaux points clés de cette évolution : jusqu’à 40 % de cœurs CPU supplémentaires par rapport aux serveurs Premier précédents

• jusqu’à 1,5 To de RAM par hôte
• stockage NVMe haute performance
• bande passante privée jusqu’à 50 Gbit/s incluse

Ensemble, ces améliorations fournissent une base plus puissante et évolutive pour les infrastructures virtuelles hébergées sur OVHcloud, notre dernière fierté.

Spécifications des serveurs Premier 2027

Derniers processeurs Intel Emerald Rapids

Les nouveaux serveurs reposent sur des CPU Intel Emerald Rapids, disponibles en configurations mono-socket et bi-socket, avec une gamme granulaire allant de 16 à 72 cœurs.
Cette diversité permet aux organisations d’ajuster précisément la capacité de calcul à leurs besoins, tout en tirant parti de plusieurs améliorations notables :

• jusqu’à 40 % de cœurs supplémentaires par rapport aux serveurs Premier précédents
• jusqu’à 50 % de cache CPU supplémentaire par rapport aux serveurs Premier précédents
• des performances accrues pour les applications intensives en calcul
• des options de serveurs élargies, avec des configurations polyvalentes (GP-x) et optimisées pour le stockage (STO-x)

Capacité de mémoire étendue

Avec une prise en charge allant jusqu’à 1,5 To de RAM par hôte, les serveurs Premier 2027 permettent :

• le déploiement de machines virtuelles de plus grande taille
• une meilleure consolidation des ressources
• des performances accrues pour les applications exigeantes en mémoire, telles que les bases de données et les plateformes analytiques

Stockage NVMe haute performance

La nouvelle génération de serveurs intègre du stockage NVMe, ce qui se traduit par une latence réduite et un débit de données nettement supérieur.
Dans ce cadre, les configurations optimisées pour le stockage (STO-x) s’appuient sur des disques NVMe vSAN et peuvent atteindre jusqu’à 70 To de capacité par hôte.
Cette architecture permet d’exécuter efficacement des charges de travail intensives en stockage, comme de grandes bases de données telles que les CRM, des plateformes analytiques, ainsi que des applications d’entreprise comme les ERP.

Réseau haut débit

Enfin, les serveurs Premier 2027 intègrent une bande passante privée jusqu’à 50 Gbit/s, assurant une communication rapide et fiable pour les machines virtuelles et les charges de travail distribuées.
Cette bande passante élevée contribue directement à améliorer les performances des applications nécessitant des échanges de données importants, notamment :

• les systèmes distribués
• les opérations de sauvegarde 
• le traitement de données à grande échelle

Voir les prix

Conçu pour une large gamme de cas d’usages Entreprise

La nouvelle génération de serveurs Premier 2027 a été conçue pour prendre en charge un large éventail de scénarios de virtualisation d’entreprise.

Migration vers le cloud

Les organisations qui migrent leurs charges de travail depuis des environnements VMware on-premises vers le cloud bénéficient d’une continuité en matière de performances ainsi que d’outils familiers, simplifiant la migration et réduisant la complexité opérationnelle.

Par ailleurs, l’augmentation des capacités de calcul et de mémoire facilite la consolidation des charges de travail et contribue à optimiser les coûts d’infrastructure.

Reprise après sinistre et continuité d’activité

Pour les environnements de reprise après sinistre, les performances de l’infrastructure et son évolutivité jouent un rôle déterminant.
Grâce au stockage NVMe haute performance et à la connectivité réseau privé jusqu’à 50 Gbit/s, cette gamme permet d’accélérer la réplication, d’améliorer les temps de reprise et de garantir des environnements de basculement fiables.

Les clients peuvent également s’appuyer sur des solutions de sauvegarde compatibles et résilientes, telles que Veeam Managed Backup, une solution managée dédiée à la protection des machines virtuelles, ainsi que Zerto, une plateforme de réplication installée et maintenue par OVHcloud, permettant une reprise d’activité rapide et simplifiée.

Hébergement d’applications d’entreprise

De nombreuses applications d’entreprise nécessitent des performances prévisibles ainsi qu’une capacité de mémoire élevée.
La gamme Premier 2027 permet d’exécuter efficacement des applications exigeantes, telles que :

• de grandes bases de données, comme les CRM ;
• des systèmes ERP ;
• des plateformes d’analyse de données ;
• des charges de travail conteneurisées dans des environnements VMware.

Évolution fluide de l’infrastructure

Les clients utilisant déjà Managed VMware vSphere peuvent intégrer les serveurs Premier 2027, en configurations polyvalentes (GP-x) ou optimisées pour le stockage (STO-x), au sein de leurs environnements existants.

Cette nouvelle gamme de serveursest compatible avec la gamme Premier actuelle, ce qui permet de constituer des clusters hétérogènes et d’étendre l’infrastructure sans nécessiter de migration complète.

Cette approche offre la possibilité de faire évoluer progressivement l’infrastructure tout en assurant la continuité des opérations.

Une infrastructure prête pour l’avenir

La nouvelle génération de serveurs Premier 2027 constitue une base solide pour répondre aux besoins futurs en matière de virtualisation.

Grâce à une architecture CPU de dernière génération, au stockage NVMe et à une connectivité réseau haut débit, les organisations peuvent accompagner l’évolution de leurs charges de travail et de leurs plateformes, tout en maintenant les niveaux de performance et de fiabilité attendus dans des environnements VMware d’entreprise.

Conclusion

L’introduction de la gamme de serveurs Premier 2027 pour Managed VMware vSphere marque une évolution importante de l’offre Private Cloud d’OVHcloud.

Avec des processeurs plus puissants, une capacité de mémoire et de stockage accrue ainsi que des configurations flexibles, cette évolution permet aux organisations d’exécuter plus efficacement des charges de travail modernes, tout en conservant un contrôle total sur leurs environnements VMware.

Découvrez la gamme de serveurs Premier 2027 : https://www.ovhcloud.com/fr/hosted-private-cloud/vmware/prices/

En savoir plus sur les solutions VMware on OVHcloud : https://www.ovhcloud.com/fr/solutions/vmware/

Migrer vers le cloud est une étape stimulante, mais les décisions prises en amont conditionnent durablement la suite.

La véritable pression se fait sentir à mesure que les usages augmentent et que les architectures sont soumises à des charges plus soutenues. Ce qui fonctionne lors de la migration initiale ne tient pas toujours lorsque les systèmes doivent évoluer à l’échelle de plusieurs régions, équipes et charges de travail.

Les ingénieurs des Professional Services et les Customer Success Managers d’OVHcloud mettent en lumière des décisions souvent sous-estimées, mais déterminantes pour la réussite des migrations et des déploiements dans le cloud public, en posant les bases d’une croissance à la fois évolutive et durable.

Ce qui est négligé au départ, mais qui façonne l’évolutivité par la suite

Le succès à long terme d’un projet cloud se joue généralement au cours des six à douze premiers mois. C’est durant cette période que les choix d’infrastructure ont le plus d’impact et que la préparation opérationnelle devient critique. Souvent relégués au second plan lors d’une migration, le réseau, l’architecture régionale et les fondations opérationnelles s’imposent rapidement comme des éléments clés à mesure que les environnements se développent.

Les premiers déploiements peuvent fonctionner avec succès en utilisant des interfaces publiques et des configurations par défaut. Mais à mesure que les services se multiplient, le trafic interne augmente entre les API, les bases de données et les couches de traitement en arrière-plan. Sans un modèle de réseau privé, cette couche de communication peut introduire de la latence, exposer des données sensibles et entraîner, à terme, des refontes complexes.

« La sécurité doit être la priorité. Un simple ’lift and shift’, sans conception préalable d’une landing zone sécurisée et évolutive, ne suffit pas. Il est essentiel de mettre en place dès le départ une infrastructure adaptée aux besoins futurs. » – Olivier Javaux, Professional Services, OVHcloud

Construire la résilience au-delà du déploiement initial

La stratégie régionale obéit à la même logique. Le choix entre un déploiement en zone de disponibilité unique ou multiple influence directement la résilience, les mécanismes de bascule et la complexité opérationnelle. Revenir sur ces choix après le déploiement s’avère particulièrement complexe, surtout lorsque des dépendances de données et du trafic en production sont déjà en place. En intégrant dès le départ les perspectives de croissance, les exigences de disponibilité et les besoins de continuité d’activité, les organisations peuvent inscrire l’évolutivité et la durabilité au cœur même de la conception de leurs systèmes, et ainsi éviter des ajustements coûteux par la suite.

Les landing zones et les dispositifs opérationnels sont également trop souvent relégués au second plan, alors qu’ils jouent un rôle clé dans les opérations quotidiennes, la gestion des incidents et la conformité à mesure que les systèmes évoluent. L’un des enseignements majeurs réside dans un changement de posture : les équipes cloud doivent passer d’une logique centrée sur le déploiement de l’infrastructure à une approche intégrant dès le départ la visibilité, la gouvernance et le pilotage opérationnel. Les services managés et les plateformes standardisées accompagnent cette transition en réduisant la charge opérationnelle, tout en améliorant la supervision à mesure que les environnements gagnent en complexité.

La dimension humaine, enfin, ne doit pas être sous-estimée. Une intégration structurée, associée à des formations adaptées et à un alignement clair entre les parties prenantes opérationnelles, permet de limiter les incompréhensions et d’accélérer l’adoption. À l’inverse, lorsque la conduite du changement est négligée dès les premières phases, même des plateformes cloud techniquement solides peuvent être perçues comme risquées, freinant les déploiements et renforçant les résistances internes.

« Une formation adaptée doit être mise en place afin que les équipes ne perdent pas la maîtrise de leur infrastructure. » – Olivier Picquenot, Customer Success Director, OVHcloud

💡 Conseil de mise en œuvre :

Réaliser une évaluation de maturité cloud ou un proof of concept ciblé permet de valider la conception réseau et les mécanismes de résilience, et de poser ainsi les bases nécessaires à une évolutivité durable.

Le travail essentiel qui transforme des objectifs stratégiques en décisions d’architecture

La migration et le passage à l’échelle s’appuient sur des objectifs bien identifiés : améliorer les performances, maîtriser les coûts et accompagner la croissance. C’est dans la traduction de ces objectifs en décisions d’infrastructure que la complexité se révèle.

« L’évolutivité doit être étudiée dès le départ, notamment en tenant compte des profils de charge. L’un des principaux avantages du cloud réside dans sa capacité à s’adapter à la hausse ou à la baisse en fonction de la charge. » – Olivier Picquenot

Comprendre dès le départ les dépendances applicatives, les pics de charge, les exigences de conformité ou encore les écarts de compétences au sein des équipes est déterminant. Sans cette visibilité, les décisions liées à l’évolutivité deviennent réactives, prises dans l’urgence et sur la base d’informations incomplètes.

Les équipes doivent donc expliciter leurs hypothèses dès le début, en se posant des questions concrètes :

• Comment le trafic interne entre les services se comportera-t-il sous charge ?
• À quels moments les pics d’activité surviennent-ils et comment les mécanismes d’adaptation permettront-ils d’y répondre ?
• Quelles contraintes de conformité ou de localisation des données influencent le déploiement des ressources ?
• Les équipes disposent-elles des compétences nécessaires pour exploiter des plateformes complexes dans la durée ?

L’automatisation et les services managés apportent une réponse concrète à ces enjeux. L’Infrastructure as Code, les bases de données managées ou encore les services intégrés permettent de réduire la charge opérationnelle, tout en recentrant les équipes sur la création de valeur plutôt que sur la maintenance de l’infrastructure.

💡 Conseil de mise en œuvre :

Associer les objectifs métier à des indicateurs techniques mesurables permet ensuite, grâce à l’automatisation et aux services managés, de les traduire en une architecture réellement évolutive.

Les risques liés au passage à l’échelle et les fondamentaux opérationnels

Une croissance rapide introduit des risques opérationnels capables de fragiliser même des environnements bien conçus. Certaines pratiques fondamentales permettent toutefois de limiter ces dérives.

« La réponse la plus importante est l’automatisation. Avec des outils comme Terraform ou OpenTofu, les organisations sont prêtes à passer à l’échelle. » – Olivier Javaux

L’automatisation du provisionnement, de l’adaptation à la charge et du monitoring garantit des déploiements reproductibles et prépare les équipes à évoluer efficacement. En parallèle, la clarification des responsabilités, la standardisation des environnements et la réduction de la dispersion des outils facilitent le diagnostic des incidents, renforcent la conformité et contribuent à une meilleure maîtrise des coûts. À mesure que les équipes et les plateformes se développent, la cohérence devient un véritable levier d’efficacité.

La transition d’applications monolithiques vers des architectures en microservices ou vers Kubernetes reste complexe. Une approche progressive permet toutefois de sécuriser cette transformation. Commencer par un service à faible risque permet de valider les processus de migration, d’ajuster les mécanismes d’adaptation et d’étendre progressivement le périmètre, tout en renforçant la confiance des équipes.

💡 Conseil de mise en œuvre :

S’appuyer sur la reproductibilité constitue un levier clé pour accompagner l’évolution des plateformes. L’automatisation, la standardisation et le déploiement progressif permettent d’en assurer la stabilité dans la durée.

Éviter les coûts cachés

Les hypothèses héritées des systèmes existants, tout comme le surdimensionnement, constituent des pièges fréquents lors des migrations vers le cloud. Sans remise en question des modèles de conception, les équipes risquent de générer des coûts inutiles et d’alourdir la complexité opérationnelle.

Or, les environnements cloud évoluent rapidement. Une révision régulière de l’architecture permet de tirer pleinement parti des nouveaux services et d’adopter des modèles plus efficaces.

« Un modèle de tarification prédictif et transparent, dans lequel les clients paient uniquement pour les ressources réellement consommées, comme le stockage, la puissance de calcul ou la bande passante, permet de mieux anticiper les projets. » – Amarjit Toor

Conseil de mise en œuvre :

Éviter de reproduire à l’identique les modèles hérités implique d’évaluer en continu les services utilisés et d’ajuster l’architecture en fonction des usages réels.

Concevoir pour l’évolutivité

Réussir le passage à l’échelle des projets cloud suppose de concevoir dès le départ en intégrant la croissance, la sécurité et l’efficacité opérationnelle. Tout commence par les fondamentaux : automatiser de manière systématique et s’appuyer sur des expertises pour construire des bases solides en matière de réseau, d’observabilité, d’automatisation et de préparation opérationnelle.

Des équipes confiantes, concentrées sur la création de valeur plutôt que sur la gestion des incidents d’infrastructure, soutenues par une plateforme résiliente, c’est ce qui fait la différence sur le long terme.

Si vous êtes en phase de croissance et souhaitez que le cloud ne soit plus une source de complexité, découvrez des solutions cloud évolutives adaptées aux entreprises en développement.

Migrating to the cloud is exciting, but early decisions define what follows.

Real pressure emerges as usage grows and architectures are tested under sustained load. What worked for initial migration doesn’t always hold up when systems need to scale across regions, teams and workloads.

OVHcloud Professional Services Engineers and Customer Success Managers highlight the often-overlooked decisions that drive successful public cloud migrations and deployments, setting the foundations for scalable, future-ready growth.

What gets overlooked early, but shapes scaling later

The long-term success of a cloud project is defined in the first six to twelve months, where early infrastructure decisions often have the biggest impact and operational readiness is crucial. Networking, regional design and operational foundations may feel secondary during migration, but they quickly become central as environments grow.

Early deployments may run successfully using public interfaces and default configuration, but as services expand, internal traffic increases between APIs, databases and background processing layers. Without a private network model, that communication layer can introduce latency, expose sensitive traffic, and require disruptive redesign later.

“Security must be the priority. A simple ‘lift & shift’, without first designing a scalable and secure landing zone, isn’t enough. Ensure the correct infrastructure is in place at the beginning to account for future needs.” – Olivier Javaux, Professional Services, OVHcloud

Building resilience beyond initial deployment

Regional strategy follows the same pattern. Choices between single- and multi-availability zone (AZ) deployments influence resilience, failover behaviour and operational complexity. Changing these configurations after deployment is challenging, particularly when data dependencies and production traffic are already in place. By factoring in growth, availability requirements and business continuity early on, organisations can embed scalability and sustainability directly into their system design, alleviating the pressures of having to retrofit later.

Landing zones and operational systems are also common afterthoughts despite being central to day-to-day processes, incident response and compliance as systems scale. The key lesson is a necessary shift in focus: cloud teams need to move from simply deploying infrastructure to establishing visibility, governance and operational control from the outset. Managed services and standardised platforms further support this shift by reducing operational burden while improving oversight as environments expand.

The human dimension cannot be overstated. Proper onboarding, training and alignment across operational stakeholders helps reduce confusion and accelerate adoption. When change management is overlooked in the early stages, even well-architected cloud platforms can feel risky, slowing delivery and increasing resistance.

“The correct training must be in place to ensure teams don’t feel like they’re losing grip on the infrastructure.” – Olivier Picquenot, Customer Success Director, OVHcloud

💡 Implementation tip:

Conduct a cloud maturity assessment or small proof-of-concept to validate network design and resiliency. These early choices become the difference that scales later.

The vital work turning high-level goals into architecture decisions

Migration and scaling begin with clear objectives: improve performance, control costs, and support growth. Translating these into infrastructure decisions is where complexity creeps in.

“Scalability must be studied from the start, including load patterns. One of the main advantages of the cloud is the capacity to scale up or down depending on the load.” – Olivier Picquenot

Understanding dependencies, peak load patterns, compliance requirements and team skills gaps early on is essential. Without this visibility, scaling decisions are made reactively using incomplete information.

Teams should clarify assumptions from the start by asking practical questions early:

• How will internal traffic between services behave under load?
• What are the peak times, and how will scaling respond?
• Which compliance or data residency requirements affect where resources are provisioned?
• Does the team have the skills to operate complex platforms long term?

Automation and managed services help bridge the gap. Infrastructure-as-code, managed databases and integrated systems reduce operational overhead and frees teams to focus on building value, rather than maintaining infrastructure.

💡 Implementation tip:

Map business goals to measurable technical outcomes. Automation and managed services turn intent into scalable architecture.

Scaling risks and operational fundamentals

Rapid growth introduces operational risks that can destabilise even well-designed environments. Foundational practices can prevent these issues.

“The most important answer is automation. Using tools like Terraform or OpenTofu, organisations are ready to scale.” – Olivier Javaux

Automating provisioning, scaling and monitoring ensures repeatable deployments and prepares teams to scale efficiently. Meanwhile, defining ownership, standardising environments and reducing tool sprawl simplify troubleshooting and improve compliance as costs lower. Consistency becomes a force multiplier as teams and platforms grow.

Moving from monolithic applications to microservices or Kubernetes is complex, however, a phased migration approach helps to avoid failure. Starting with a low-risk service allows teams to validate the migration process, tune scaling and gradually expand while building confidence.

💡 Implementation tip:

Scale through repeatability. Automation, standardisation and phased delivery create stability as platforms grow.

Avoiding hidden costs

Legacy assumptions and over-provisioning are common traps in cloud migration. Without rethinking design patterns, teams risk creating unnecessary cost and operational complexity.

Cloud environments evolve rapidly. Reviewing architecture regularly ensures teams benefit from improved services and efficient patterns.

“A predictive, transparent pricing model where customers are charged only for the resources they consume, such as storage, compute power or bandwidth, allows for greater confidence in forecasting projects” – Amarjit Toor

💡 Implementation tip:

Avoid lifting legacy patterns unchanged. Continuously assess services and adjust architecture to match real-world demand.

Designing for scale

Scaling cloud projects successfully means designing for growth, security and operational efficiency from day one. Start with the fundamentals – automate relentlessly and leverage expertise when building the foundations for networking, observability, automation and operational readiness.

This is the difference that scales, resulting in a resilient platform and a confident team focused on value, rather than troubleshooting infrastructure.

If you’re navigating growth and want cloud to be one less thing to worry about, explore scalable cloud solutions for growing businesses.

Over the past few years, the speed at which teams can build infrastructure has changed dramatically. Models that once took weeks to train can now be iterated in days. Tooling has improved, workflows have matured, and the overall friction in getting from idea to working output has reduced significantly.

But this acceleration often stops the moment teams try to deploy — and this can make AI deployment frustrating. In this blog, you will learn how Facets can help teams accelerate migration to OVHcloud by making deployment more structured, repeatable and predictable.

What first begins as a fast, iterative process slows down when it enters the infrastructure layer. The work is no longer about models or code. It shifts to provisioning environments, configuring pipelines, managing permissions, setting up networking, and ensuring that everything works reliably outside a controlled development setting. This phase is not inherently complex, but it is fragmented, and that introduces delay.

As a result, there is now a visible gap between how quickly teams can build and how slowly they can move to production. The model may be ready in hours, but the surrounding system required to run it still takes days, weeks, or in some cases even months, to put together.

AI deployment is slow because infrastructure is inconsistent, not because AI is limited

It is tempting to assume that deployment delays are still a technical limitation but, in most cases, that is no longer true. The bottleneck is not the model itself. It is everything around it.

Infrastructure is rarely standardised across teams. Each project tends to define its own setup, its own pipeline, and its own configuration. Even when teams use the same tools, the way those tools are applied differs just enough to create inconsistency.

Over time, these differences accumulate. Environments are recreated, pipelines are reconfigured, dependencies are re-evaluated, and access is managed manually. What should be a repeatable process becomes a fresh effort every time.

This is where deployment slows down. Not because teams cannot build quickly, but because the systems around deployment are not structured for reuse.

Faster deployment starts with reusable infrastructure

Teams that deploy faster do not necessarily rely on fundamentally different tools. They change how infrastructure is organised.

Instead of treating infrastructure as something that needs to be set up for every project, they define it once and reuse it. Environments are created from standard definitions rather than being handcrafted. Deployment workflows follow consistent patterns instead of being recreated each time. Access, policies and guardrails are built into the system rather than handled separately.

This does not eliminate complexity, but it contains it. Systems become easier to understand, easier to operate and easier to extend. Most importantly, they become predictable.

Once infrastructure behaves predictably, deployment stops being a recurring source of delay.

AI improves operations only when infrastructure is already structured as a system

There is growing interest in applying AI to DevOps and infrastructure management, but its role is often misunderstood.

AI does not fix fragmented systems. If the underlying setup is inconsistent, AI will only automate that inconsistency. It may reduce effort in specific tasks, but it does not create structure on its own.

AI becomes valuable when it operates on top of a well-defined system. It can help teams understand system state, identify issues faster, assist with debugging, and reduce manual operational work. But it works best when the infrastructure beneath it is already standardised, reusable and consistent.

Infrastructure needs to shift from project-level setup to a standardised system

As AI accelerates development, the limitations of infrastructure become more pronounced. Teams are able to build faster than they can deploy, and that imbalance introduces friction.

This is not a temporary phase. As development continues to speed up, deployment will remain the limiting factor unless the underlying structure changes.

A different approach is needed. Instead of treating infrastructure as a series of isolated setups, teams need systems that standardise how infrastructure is created, managed and reused.

Facets turns infrastructure into a reusable deployment system

Facets is designed around this model. It brings infrastructure, CI/CD, environments, workflows and guardrails into a single operating system for deployment. It brings infrastructure, CI/CD, environments, workflows and guardrails into a single operating system for deployment. Teams can create environments on demand, follow predefined deployment workflows and retain operational context within the platform instead of relying on scattered documentation or individual knowledge.

This changes how teams interact with infrastructure. The focus shifts from repeatedly setting things up to using a system that is already structured to work.

Choosing the right cloud matters once infrastructure is standardised

Once infrastructure is structured as a system, the choice of where to run it becomes more important.

For AI workloads, teams need reliable compute, predictable cost structures and control over how environments are configured. OVHcloud provides a strong foundation for this, with access to GPU infrastructure, cost predictability, and flexibility in how environments are managed.

However, infrastructure alone does not remove friction. The real advantage comes when teams can move to that infrastructure quickly and operate it consistently without rebuilding their setup.

OVHcloud + Facets: Accelerating Deployment Through Standardisation

OVHcloud provides reliable, on-demand infrastructure for modern workloads. Facets helps teams make that infrastructure deployment-ready.

Together, they address both sides of the problem. OVHcloud provides the cloud foundation, while Facets defines how environments, workflows, policies and guardrails are created and operated on top of it.

Facets.cloud introduces reusable infrastructure blueprints that can be applied across projects. These blueprints define environments, workflows and operational guardrails in advance, allowing teams to deploy standardised systems instead of assembling infrastructure manually each time.

This shifts deployment from a configuration-heavy process to a repeatable, system-driven approach. Teams can reduce the time spent on setup, avoid recreating the same deployment patterns and move workloads onto OVHcloud with greater consistency.

The result is a faster path from migration planning to production-ready environments — helping teams migrate in days, not weeks.

AI speed is ultimately limited by how fast infrastructure can be deployed and operated

AI has already compressed the time it takes to build. The next bottleneck is AI deployment.

And that bottleneck is not solved by adding more tools or more people—it is solved by changing how infrastructure is structured. Because in practice, the speed of AI is defined not by how quickly models are built, but by how quickly they can be deployed and run.

Discover Facets.cloud

Aurélie Vache and Stéphane Philippart attended as dit 19 other OVHcloud employees. In this blog post, they share their thoughts and feedback from this 14th edition of Devoxx France.

Devoxx France 2026: The AI Edition

Devoxx France 2026 is one of Europe’s biggest independent developer conferences. Formerly focused centrally on Java, over the past few years, the conference has also focused on Architecture, Data & Analytics, Development practices, Front-end & UX, Java/JVM, Security & Privacy, Cloud and non-technical talks about people and culture.

Key figures from the 2026 edition:

• 4,980 attendees (The largest attendance on record)
• 307 speakers
• 259 talks
• 70+ sponsors

As might be expected, AI was the central theme of this edition, with a large number of the talks focused on AI topics. Indeed, there were 65 sessions out of 259 about AI and Agentic Systems, the most discussed topic!

Notably this year, and perhaps even more than in previous years, we could clearly see attendees arriving early to secure seats for their favorite talks. Even so, there ended up being a lot of disappointment – especially on the first day – as several sessions were already at full capacity minutes before they even started.

This was particularly true for sessions featuring multiple OVHcloud speakers 💪.

Keynotes

The keynote sessions (“plenary sessions”) were also heavily centered on Artificial Intelligence, but with a notably broader lens beyond pure technology. Rather than focusing only on tools or LLM implementation, the talks explored AI through the intersecting dimensions of power, governance, cybersecurity, human transformation, and geopolitics.

Some highlights from the keynotes:

• “In 50 years, AI has multiplied its power, along with the challenges of governance and cybersecurity” – Laurence Devillers (@lau_devil)

• Jean-Gabriel Ganascia (@Quecalcoatle) questioned the promise of AI as a force that could free humans from effort, raising deeper reflections on what this means for our relationship with work and meaning.

• Loup Cellard (@CellardLoup) examined the implications of foreign investments in AI infrastructure, shedding light on the geopolitical and strategic stakes behind these technologies.

Meet & Greet

Devoxx France consists of three days of conferences, sponsor booths to discover, and Thursday evening’s unmissable annual tradition: the Meet & Greet.

Thursday night’s Meet & Greet is a major community event built around networking and social sessions like BOFs (Birds of a Feather) and seed networking. It’s one of the signature traditions of the conference, beyond talks and sponsor booths.

This evening event is free, open to the public with pre-registration, and offers a genuine moment for connection, sharing, and conversation over a drink and a plate of charcuterie and cheese 😇.

It’s also the opportunity to discover the fun of “Voxx Jam”, the community-party, music-oriented side of Devoxx/Voxxed culture 🎸.

OVHcloud Presence

At the OVHcloud booth, we were a team of 8 speakers and 11 colleagues from Tech, HR, and Sales, and their dynamic presence really made a difference. Engaging in topics like AI, Public Cloud, Domain Names, Observability, Quantum technologies, and more, we had many insightful conversations throughout the event.

We also discussed AI topics at the booth, which was of course the main theme of the conference, but not the only one.

A lot of conversations also focused on sovereignty. Three years ago, people were saying: “I don’t care about sovereignty, I’ll just choose the cheapest option.” This year, the tone has clearly changed, “How can we use your sovereign products?”

There is a real shift happening, and once again, being present at events like this is essential to witness and take part in these evolving discussions.

It was truly a top-tier booth experience for all of us💪.

Of course, the goal of our booth was so attendees could discuss with our teams, but also so we could engage them through our very own video game, “Gaming Camp: Beat Cloud Villains!”. The specially designed video game’s description: “Join the fight against the villains of the cloud. Take on Hidden Cost, Jailor Stack, and Autonomous Zero, and prove yourself as a true Guardian of the Cloud.”

Players were welcomed to step into a two-player fighting game inspired by the style of Street Fighter, where strategy and skill are your best weapons. Game on!

We also wanted to say a word about the success of our Schrödinger cat (Quantum) swag – socks, keychains, badges – they were a huge hit, and often sparked great conversations throughout the event.

OVHcloud Speakers & Talks

Getting accepted to Devoxx France is not easy, so we were proud to be included with 8 speakers and 11 talks! We were the most represented company in terms of talks at Devoxx France 2026, and ranked in the top 3 by number of speakers 💪.

Congratulations to Benoit Masson, Fanny Bouton, Mathieu Busquet, Sébastien Ferrer, Théo Bougé, and Héla Ben Khalfallah, Stéphane Philippart & Aurélie Vache for their talks 👏. A large number of attendees joined, and the sessions were all very high quality.

Find here the topics of their talks:

“Question pour un cluster Kubernetes : Quiz sur Kubernetes & ses concepts”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “The Ultimate Kubernetes Challenge: An Interactive Trivia Game on concepts, components, usage…”

🎤 Speaker: Aurélie Vache

“Kubernetes est devenu le standard de facto pour déployer et exploiter des applications conteneurisées. Nous l’utilisons, ainsi que son ecosystème, au quotidien, mais le connaît-on si bien ?

Tout au long de ce talk, avec un mix de quiz et de démos en live, vous découvrirez (ou redécouvrirez) les concepts clés de Kubernetes (pods, secrets, services, namespaces…), les composants interne mais aussi les bonnes pratiques d’utilisation.

Un format original avec un quiz, du fun et des démos, qui conviendra aussi bien aux débutants qu’aux confirmés, afin d’apprendre, réviser et challenger vos connaissances du merveilleux monde de Kubernetes et de son écosystème, tout en s’amusant.

Soyez là ou le plus rapide pour tenter de gagner des cadeaux !”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 Kubernetes has become the de facto standard for deploying and operating containerized applications. We use it, as well as its ecosystem, on a daily basis, but do we know them as well as we think we do?

With a mix of quiz and live demos, come learn and/or improve your knowledge. You will discover (or rediscover) the key concepts of Kubernetes (pods, secrets, services…), internal components but also best practices.

In this fun and dynamic talk, come compete throughout the quiz and explore the wonderful world of Kubernetes.
Icing on the cake: the first will win some swags.

🎥 Replay.

“QR Codes : suivez les points sans vous perdre !”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “QR codes: follow the dots without getting lost!“

🎤 Speaker: Benoît Masson & Sébastien Chedor (OnePoint)

“Les QR Codes, tout le monde connaît et les utilise régulièrement. Mais savez-vous vraiment comment ils fonctionnent, pourquoi c’est aussi rapide et fiable, même avec une caméra de faible qualité ou un code en partie caché ou détérioré ?

Nous vous proposons de coder ensemble un lecteur de QR Codes, avec un minimum d’outils :
* capture et analyse de la vidéo issue de la webcam pour détecter la position du code, à l’aide d’OpenCV
* extraction et décodage du contenu, avec correction d’erreur grâce à l’algorithme de Reed-Solomon.

À la fin de cette session, vous devriez être capables de décoder un QR Code à l’oeil nu 🕵️ (et un brouillon…)”.

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Everyone knows QR codes and uses them regularly. But do you really know how they work, and why they are so fast and reliable, even with a low-quality camera or a partially hidden or damaged code?

We propose coding a QR code reader together, using a minimum number of tools:
* capturing and analysing webcam video to detect the position of the code, using OpenCV
* extracting and decoding the content, with error correction using the Reed-Solomon algorithm

By the end of this session, you should be able to decode a QR code with the naked eye 🕵️— and a rough sheet of paper…”

🎥 Replay.

“Noms de domaines : la grande histoire des petites extensions”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Domain names: the big story behind small extensions”

🎤 Speakers: Benoît Masson & Theo Bougé

“Derrière les quelques lettres qui suivent un point (.com, .fr, .ai…) se cache un univers riche de stratégies techniques, d’enjeux géopolitiques et de batailles commerciales.

À l’approche du nouveau round de l’ICANN prévu en 2026 qui va autoriser de nouvelles extensions, il est temps de revenir sur les fondations techniques du DNS, ainsi que sur les grands épisodes de cette aventure méconnue. Des TLD historiques aux extensions détournées, des dramas autour du .web aux ambitions du Web3, nous explorerons l’évolution d’un système devenu central dans les logiques de souveraineté numérique et d’innovation commerciale.

Une plongée dans les coulisses d’un Internet en perpétuelle transformation.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Behind the few letters that follow a dot — .com, .fr, .ai and others — lies a rich world of technical strategies, geopolitical issues and commercial battles.

As the new ICANN round planned for 2026 approaches, which will authorise new extensions, it is time to revisit the technical foundations of DNS, as well as the major episodes in this little-known story. From historic TLDs to repurposed extensions, from the drama around .web to the ambitions of Web3, we will explore the evolution of a system that has become central to digital sovereignty and commercial innovation.

A deep dive behind the scenes of an Internet in constant transformation.”

🎥 Replay.

“Informatique quantique, ce coup-ci on vous dit tout !”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Quantum computing: this time, we tell you everything!”

🎤 Speaker: Fanny Bouton, Olivier Ezrati (Quantum Energy Initiative) & Guillaume Schurck (Alice & Bob)

“Informatique quantique pour développeurs : comprendre, coder, passer à l’échelle

L’informatique quantique sort du laboratoire et devient progressivement accessible aux développeurs via des SDK open source, des notebooks, des simulateurs et des QPU disponibles dans le cloud. En 2026, la question n’est plus « qu’est-ce que le quantique ? » mais « comment un développeur peut-il s’en emparer concrètement ? »

Nous commencerons par poser les bases essentielles pour comprendre le modèle de calcul quantique : qubit, superposition, intrication, et ce que ces concepts impliquent pour un développeur.
Nous passerons ensuite au code : écrire et exécuter des circuits quantiques, utiliser des SDK modernes, travailler dans des notebooks, tester sur simulateur puis sur de vrais QPU. Vous verrez à quoi ressemble un workflow quantique aujourd’hui.

Enfin, nous aborderons les cas d’usage concrets, illustrés par le retour d’expérience d’un grand compte : ce qui fonctionne déjà, les limites actuelles, et comment les équipes tech expérimentent le quantique de manière réaliste et industrielle.

Une session technique pensée pour les développeurs qui veulent anticiper la prochaine évolution majeure du calcul.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Quantum computing for developers: understand, code and scale up.
Quantum computing is moving out of the laboratory and becoming progressively accessible to developers through open source SDKs, notebooks, simulators and QPUs available in the cloud. In 2026, the question is no longer ‘What is quantum?’ but ‘How can developers make practical use of it?’

We will begin by laying out the essential foundations needed to understand the quantum computing model: qubits, superposition, entanglement, and what these concepts mean for developers.

We will then move on to code: writing and running quantum circuits, using modern SDKs, working in notebooks, testing on simulators and then on real QPUs. You will see what a quantum workflow looks like today.

Finally, we will address concrete use cases, illustrated by the experience of a large account: what already works, the current limitations, and how tech teams are experimenting with quantum computing in a realistic and industrial way.

A technical session designed for developers who want to anticipate the next major evolution in computing.”

🎥 Replay.

“Développer avec l’IA : et si c’était aussi simple qu’ajouter une librairie ?”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Developing with AI: what if it were as simple as adding a library?”

🎤 Speakers: Mathieu Busquet & Stéphane Philippart

“Intégrer de l’intelligence artificielle (IA) dans nos développements peut nous paraître plus complexe que de les utiliser dans notre quotidien.

Dois-je apprendre un nouveau langage ou une nouvelle stack ?
Durant ce workshop nous vous proposons de vous donner tous les éléments pour intégrer l’IA sans quitter votre langage de prédilection : Java 😍. Ce sera l’occasion de découvrir les Frameworks du moments : LangChain4j, Quarkus, …

Nous vous invitons à découvrir toutes les facettes d’un chatbot avec l’IA générative (customiser un prompt, rajouter vos données (RAG), appeler des outils locaux ou distants (MCP) et créer des agents) mais aussi parce que l’IA ne se limite pas aux chatbots : faire de la transcription, créer de l’audio ou même faire un traducteur.

Et, toujours pour vous simplifier la vie, venez juste avec votre ordinateur et un navigateur Internet, on se charge du reste pour vous construire un environnement de développement aux petits oignons grâce aux CDE.

À la suite de ce talk vous repartirez avec une boîte à outils vous permettant d’intégrer simplement la puissance des modèles d’IA au sein de vos développements de tous les jours.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Integrating artificial intelligence into our developments can seem more complex than using it in our daily lives.

Do I need to learn a new language or a new stack?

During this workshop, we will give you all the tools you need to integrate AI without leaving your favourite language: Java 😍. It will be an opportunity to discover some of today’s key frameworks, including LangChain4j and Quarkus.

We invite you to explore all the facets of a chatbot with generative AI — customising a prompt, adding your own data with RAG, calling local or remote tools with MCP, and creating agents — but also to see that AI is not limited to chatbots: it can also be used for transcription, audio creation and even translation.

And to make your life even easier, just bring your computer and an internet browser. We will take care of the rest, building a polished development environment for you thanks to CDEs.

After this talk, you will leave with a toolkit that will allow you to integrate the power of AI models into your everyday development work.”

“Détectives de la prod : résoudre l’enquête avant le crash”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Production detectives: solve the case before the crash”

🎤 Speaker: Sébastien Ferrer

“Saviez-vous que, derrière les coulisses de vos outils de travail, se cachent des équipes prêtes à intervenir à tout moment ?

Ces équipes, souvent discrètes mais essentielles, gèrent des dizaines de projets avec des effectifs réduits. Mais quand une alerte survient, elles doivent réagir vite. Très vite. Comment réussir à diagnostiquer et résoudre un incident en pleine production, sans perdre une précieuse seconde ?

Dans ce talk je vous emmène au cœur de l’action, où je partage notre méthodologie pour transformer chaque crise en une enquête méthodique et efficace. Nous explorerons comment des outils bien pensés, une organisation affûtée, et un soupçon d’intuition transforment la gestion d’incidents en une véritable enquête… parfois aussi palpitante qu’une partie de Cluedo.

Au programme : bonnes pratiques de troubleshooting, logging et monitoring, pour que vous repartiez avec des clés concrètes pour dompter les incidents dans vos propres projets.

Vous verrez qu’en production, chaque problème cache une histoire… à résoudre en équipe !”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Did you know that behind the scenes of your work tools, there are teams ready to intervene at any moment?

These teams, often discreet but essential, manage dozens of projects with limited staff. But when an alert occurs, they need to react quickly. Very quickly. How can they diagnose and resolve a production incident without losing precious seconds?

In this talk, I will take you into the heart of the action, where I share our methodology for turning every crisis into a structured and efficient investigation. We will explore how well-designed tools, a well-honed organisation and a touch of intuition can transform incident management into a real investigation — sometimes as thrilling as a game of Cluedo.

On the agenda: troubleshooting best practices, logging and monitoring, so you leave with concrete keys to taming incidents in your own projects.

You will see that in production, every problem hides a story… one to solve as a team!”

🎥 Replay.

“Et si écrire du SQL redevenait cool ?”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “What if writing SQL became cool again?”

🎤 Speaker: Sébastien Ferrer

“On nous l’a répété maintes fois : “écrire du SQL dans du code source, c’est dépassé”.

Les ORMs sont partout. Ils ont facilité notre quotidien en nous permettant de manipuler nos bases de données sans nous soucier du SQL. Mais parfois, on aimerait un peu plus de contrôle, un peu plus de performance… sans pour autant revenir aux longues heures de mapping manuel et de requêtes préparées à la main.

SQLC offre une autre approche. Initialement conçu pour du Go, langage dans lequel cette technologie sera présentée dans ce talk, il permet d’écrire des requêtes SQL tout en générant du code type-safe et performant, sans ajouter de lourdeur ni de dépendances. Pas question ici de rejeter les ORMs, mais plutôt d’explorer un nouvel outil qui vient enrichir notre palette de solutions.

Dans ce talk, nous verrons comment SQLC fonctionne, dans quels cas il brille, et comment il s’intègre parfaitement dans un stack moderne. Vous aimez le SQL ? Vous voulez juste un peu plus de maîtrise sur vos requêtes ? Venez, vous risquez d’être agréablement surpris.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “We have been told many times: ‘Writing SQL in source code is outdated.’

ORMs are everywhere. They have made our daily lives easier by allowing us to manipulate databases without worrying about SQL. But sometimes, we would like a little more control, a little more performance — without going back to long hours of manual mapping and hand-written prepared queries.

SQLC offers another approach. Initially designed for Go, the language in which this technology will be presented during the talk, it allows you to write SQL queries while generating type-safe and high-performance code, without adding heaviness or dependencies. The goal here is not to reject ORMs, but rather to explore a new tool that enriches our range of solutions.

In this talk, we will see how SQLC works, where it shines, and how it integrates perfectly into a modern stack. Do you like SQL? Do you simply want more control over your queries? Come along — you may be pleasantly surprised.”

🎥 Replay.

“🤖 Apprendre à notre IA à … apprendre 🧠”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “🤖 Teaching our AI to… learn 🧠”

🎤 Speaker: Stéphane Philippart

“RAG, MCP, tooling, function calling, agents, fine tuning, training, …
Que de termes barbares mais qui ont tous le même objectif : faire en sorte que le modèle d’intelligence artificielle que vous utilisez réponde correctement à vos questions et attentes 😅.
Et pour ça il va falloir ajouter de la connaissance, des données (privée ou publiques, …).

Durant ce talk je vous propose d’y voir un peu plus clair dans cette jungle des acronymes puis, fort de connaître les différences, vous proposer comment l’implémenter en tant que développeuses et développeurs.

Chaque approche a ses spécificités, ses avantages et ses inconvénients.
A la fin de ce talk, non seulement vous saurez choisir la bonne approche, mais aussi ajouter dans vos développements quotidiens la dose d’IA utile.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “RAG, MCP, tooling, function calling, agents, fine tuning, training…

So many intimidating terms, but they all have the same goal: ensuring that the artificial intelligence model you use responds correctly to your questions and expectations 😅.

And to do that, you need to add knowledge and data — private, public or otherwise.

During this talk, I will help you see more clearly through this jungle of acronyms, and once you understand the differences, I will show you how to implement them as developers.

Each approach has its own specificities, advantages and disadvantages.

By the end of this talk, you will not only know how to choose the right approach, but also how to add the right dose of useful AI into your daily development work.”

🎥 Replay.

“Refactorer sans tout casser: anatomie des patterns de modernisation incrémentale”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “Refactoring without breaking everything: anatomy of incremental modernisation patterns”

🎤 Speaker: Héla Ben Khalfallah

“Cette session répond à un problème extrêmement courant mais rarement traité de façon structurée : comment moderniser un système legacy sans big bang, sans freeze de la prod, et sans multiplier les régressions. Plutôt que de parler “microservices” ou “rewrite from scratch” de manière abstraite, la session propose un playbook de modernisation incrémentale, articulé autour de patterns éprouvés : Strangler Fig, Parallel Change (Expand/Contract), Branch by Abstraction, décomposition par capacités métier / sous-domaines / transactions, et les patterns de conception (Facade, Adapter, Proxy, Mediator) utilisés comme briques concrètes de migration.

Le contenu est ancré dans la pratique : il synthétise à la fois des retours d’expérience industriels (Netflix, Khan Academy, etc.) et des travaux de recherche / rédaction. L’objectif n’est pas de présenter un catalogue de patterns, mais de montrer comment les combiner pour construire une trajectoire de migration observable, réversible et livrable en continu.

Vous repartirez avec une grille de lecture concrète pour garder des migrations observables, réversibles et compatibles avec le rythme produit.”

🏴󠁧󠁢󠁥󠁮󠁧󠁿 “This session addresses an extremely common problem that is rarely handled in a structured way: how to modernise a legacy system without a big bang, without a production freeze, and without multiplying regressions. Rather than talking abstractly about microservices or rewriting from scratch, the session offers an incremental modernisation playbook built around proven patterns: Strangler Fig, Parallel Change — Expand/Contract — Branch by Abstraction, decomposition by business capabilities, subdomains and transactions, as well as design patterns such as Facade, Adapter, Proxy and Mediator used as concrete building blocks for migration.

The content is rooted in practice: it brings together both industrial feedback from companies such as Netflix and Khan Academy, and research and written work. The goal is not to present a catalogue of patterns, but to show how they can be combined to build a migration path that is observable, reversible and continuously deliverable.

You will leave with a concrete framework for keeping migrations observable, reversible and compatible with the pace of product development.”

🎥 Replay.

📺 Devoxx France published the 232 videos (keynotes, conferences, tools in action, lunch talks & deep dives) on the Devoxx France YouTube channel.

Podcast

Devoxx France was also an opportunity for OVHcloud’s Aurélie Vache, Stéphane Philippart, and Magali De Labareyre to be interviewed in the Press space for the “Tech en Pratique” podcast.

The episodes will be available on YouTube starting in September! 🙂

Key Trends

• AI moved from hype to production
  The focus shifted toward agentic systems, RAG, observability, governance, and enterprise integration, with more emphasis on shipping useful AI than experimenting.

• Java evolved for modern AI and cloud workloads
  LangChain4j, GraalVM, native image, and JDK modernization reinforced Java’s role as a serious platform for AI-enabled enterprise systems.

• Platform engineering became a core priority
  CI/CD maturity, OpenRewrite, modernization, and developer productivity all reflected one goal: faster delivery without losing control.

• Security moved deeper into developer workflows
  Shift-left security, AppSec, authorization, Software Supply Chain Security and secure-by-design approaches gained importance, especially with AI-generated code increasing governance needs.

• Cloud & architecture focused on operational resilience
  Kubernetes, containers, observability, and scalable systems remained central, with a stronger focus on practical engineering over hype.

• Front-end discussions matured
  Accessibility, performance, reactivity, and maintainability took priority over framework wars.

• Open source and European digital sovereignty gained traction
  Open models, self-hosted tooling, privacy, and vendor independence became increasingly important themes.

• Developer experience (DX) became strategic
  Tooling, automation, terminal workflows, and reducing cognitive load were seen as key drivers of productivity and competitiveness.

Conclusion

This Devoxx France edition was a raging success for the speakers, sponsors, and attendees alike ♥️.

💬 Stay in Touch

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

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