High performance images processing service
Luc Debliquis
Posted on March 6, 2024
Read the full case study below
The client:
Pimalion, a leading multichannel marketing software suite
Pimalion is a comprehensive platform specifically designed to empower B2C and B2B retail businesses, particularly those managing product catalogs.
The user-friendly application offers a suite of data and media management tools that streamline marketing and communication efforts, fostering efficiency across both online and offline channels.
Notable clients include Carrefour, Socoda, Hubo, D’Ieteren, …
The Challenge: processing thousands of images in near real-time
Pimalion encountered a significant hurdle: effectively handling the processing of numerous heavy images in almost real-time for their B2C and B2B retail clients.
They required a robust solution capable of automating image preparation for multiple publication channels (print, web, etc.) while also being capable to handle various industry-standard image formats (EPS, PSD, etc.).
This automation needed to efficiently manage heavy images, ensuring timely delivery and seamless integration for their clients, while dynamically scaling to handle varying workloads and optimizing costs.
A recent Gartner study found that 42% of businesses struggle with image processing bottlenecks, impacting product launch times and marketing campaign efficiency.
Source: Gartner research report, “The State of Marketing Operations 2023”
Our solution: the IPS
net2 has developed a remarkably powerful and highly scalable Image Processing Service (IPS) leveraging Microsoft .NET technologies on Azure. This service can intelligently scale based on the workload, ensuring efficient and cost-effective image processing.
Key features
- Broad format support: Accepts a wide range of professional image formats, including JPEG, PNG, EPS, PDF, TIFF, and PSD, and handles very large files exceeding dozens of megabytes.
- Intelligent automated processing: Streamline image preparation for various publication channels with our intelligent system that can automatically resize, clip, trim and even remove backgrounds of images.
- Automatic Scaling: The service scales up or down based on the number of documents in the processing queue, optimizing resources utilization.
- High Throughput: A single instance can process thousands high-definition images per hour, making it suitable for large-scale image processing tasks.
- Seamless Integration: A custom SDK facilitates effortless integration between the IPS and the Pimalion application components.
A single instance processes 30,000 HD images/hour, with the potential to reach even higher volumes thanks to Azure’s cloud scalability (load tested to 100,000 HD images/hour).
Pimalion Empowered by the IPS
- Faster processing & effortless scaling: Handles thousands of high-definition images in near real-time, scaling seamlessly to meet growing needs.
- Streamlined Multichannel Workflow: The integration of the IPS automates the customization and adjustment of images for each channel. This process not only allows Pimalion to improve its internal efficiency but also enables Pimalion to better meet its clients’ expectations.
Technical stack
- .NET: Latest .NET 8 framework for performance and scalability.
- Azure App Service (Autoscale): Cloud platform automatically adjusting resources based on processing demands, ensuring optimal performance and cost-effectiveness.
- Azure Queues: Reliable cloud messaging for asynchronous processing of high image volumes.
- Azure DevOps with automated pipelines: Streamlined development and delivery through automated build, testing, and deployment processes across various environments.
Client testimonial
Ready to automate your images processing?
Contact net2 today to discuss how our expertise and solutions can help streamline your workflows.
Curious how image processing can revolutionize your business?
Our article A Simple Guide to Image Processing dives deeper into its benefits and applications, from creating captivating online catalogs to facial recognition software.
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