Toyota Motor North America (TMNA) began using Amazon Web Services (AWS) in 2015 to simplify and standardize application development in the cloud and improve time to market. However, the team lacked a consistent monitoring tool, which created reliability concerns. Some developers used open source tools, others used log management tools, and some didn't use anything. As a result, team members often spent multiple hours trying to get to the bottom of an outage because they didn’t know what to look for or where. With 1,600 total applications (300 in the cloud) and more than 100 teams, that was a challenging task. On top of gaining unified visibility, the cloud platform team also sought to improve mean time to detection (MTTD) and ensure they could meet SLAs for 99.9 percent uptime while simultaneously reducing costs and helping engineers become more efficient.

Glovo, an on-demand courier service operating in 25 countries, was facing a significant challenge as its database resource consumption couldn't keep pace with its projected growth. As the company launched a migration to microservices, it needed better visibility into its databases to reduce CPU usage and prevent costly downtime. With an increased number of databases and queries running, they found databases were provisioned incorrectly and would often reach CPU capacity. This resulted in outages adding up to three or four hours of downtime in 2022. The existing monitoring products Glovo used didn’t provide the insight they needed. Limited access to real-time monitoring and alerting hindered the team’s response to issues. They also lacked the ability to track and compare current and historical performance data, making investigations manual and tedious.

Denver Machine Shop, a family-owned heavy industrial repair and prototype machine shop, was facing challenges in managing their operations due to their paper-based system. The system was inefficient and made it difficult to track jobs, billing, and costs accurately. The company was also concerned about missing out on important details such as the actual time taken to complete a job. As the company grew, it became increasingly difficult to keep track of all the operations. For instance, there were instances where jobs were shipped without being billed, and the company had no way of knowing this without a comprehensive system in place.

Before the implementation of the E2 ERP system, Automation Outfitters was struggling with their previous software, Global Shop. The software was used by everyone in the company, leading to bottlenecks that slowed down or completely halted their computers. This constant disruption was backing up their entire process, making their jobs more difficult instead of easier. The company quickly realized the need for a replacement ERP system that would streamline their operations and eliminate these bottlenecks.

In 2009, Boston University began the implementation of a new ERP system for human resources, procurement, and finance. With a go-live date of July 2011 for the new SRM system, the BU Sourcing and Procurement team was confronted with both a challenge and a unique opportunity. The team viewed the looming implementation as an opportunity to further improve efficiency and enhance their service to the University community. However, it soon became apparent that a new supplier management strategy had to be deployed prior to the ERP go-live date. With over 5,000 primary suppliers paid via legacy systems in 2009, decentralized processes continuously fostered data quality issues with BU’s supplier information. Initial supplier data reviews quickly highlighted supplier duplication, contradictory payment terms, and incomplete records. Further review illustrated that obtaining data from suppliers was an entirely manual process with few verifications for accuracy. Because of the overwhelming number of suppliers that needed to be managed with such a small staff, no effort to correct, update, or validate supplier data had ever been initiated.

GE faced a complex challenge of managing over 700,000 global suppliers due to the highly complex supply chain. The vendor master in disparate systems lacked schema hierarchies, supplier certifications, compliance data, and contracts. There was rapid vendor proliferation without appropriate controls and a lack of spend visibility across the enterprise due to inaccurate supplier information and categorization processes. The company needed a solution that could provide a single globally-deployed vendor master management solution that creates one “source of truth” for suppliers across the entire organization.

StubHub, the world’s largest ticket marketplace, was facing challenges as it evolved from a lightweight website to one that was rich with images, videos and custom views from seat locations at event venues around the world. The company needed a way to streamline image management, ensuring that the key focal points of each image were viewable in more than 30 viewports across a multitude of devices. Additionally, StubHub had to address digital asset management, since it worked with licensed content from partners and often had requests by third-party marketers to use the site’s images. The company also had to contend with the sheer scale of managing more than 120,000 active events on the site at any given time, and between 800 and 1,200 new ones being published every day. StubHub’s catalog included more than 54,000 entities with multiple images that needed to be selected, edited and updated continually.

The Hub, an online marketplace that connects brands with creators, was facing a challenge with the storage and resizing of large image and video files uploaded by creators to their personal portfolios on the platform. The Hub needed as many as 10 unique size and aspect combinations for each uploaded primary image, which was a time-consuming process that burdened its team of front-end developers. The two options they had were either to restrict the creative community to abide by a maximum pixel size and file size or to allow creatives to upload large files and then manually downsize them to the largest resolution needed. Both options were not ideal as they either limited the creative community or burdened the Hub's team.

VELTRA, a leading online travel experience marketplace in Japan, was faced with the challenge of optimizing cost expenditure when web traffic dropped due to the COVID-19 pandemic. The company's website relies heavily on attractive images of travel destinations, which directly influences users' likelihood of signing up for its services. The pages also need to be highly responsive to prevent users from leaving the site. Previously, VELTRA used an in-house image optimization tool and then switched to a tool offered by their Content Delivery Network (CDN) service company. However, the fixed monthly fees of this service increased as the number of visitors and processes to the web service grew, leading to high costs during off-peak seasons.

Stencil, a web-based graphic design platform, was in need of an image management solution that could handle the rendering, manipulation, and resizing of images within each design. The founders, Oliver Nassar and Adam Rotman, were aware of the complexities and potential issues associated with building their own image management and transformation platform, such as storage and memory issues, managing server farms, and the time it takes to build such a complex system. They were looking for a solution that would save them the hassle and provide users with an easy-to-use means for handling image transformations and delivering final designs that are sized perfectly for their needs.

In 2016, Fairfax Media began a wide-ranging digital transformation of its news organization, which included streamlining image management and delivery workflow. An efficient publishing workflow is key for journalists at Fairfax Media, who are responsible for posting articles, including supporting assets, such as imagery. Historically, a lot of production time was spent manipulating images to ensure they were optimized for different target devices and formats for the audience. This process was frustrating because it took valuable time from their core reporting, writing and editing duties. The team initially considered developing its own in-house image management solution, but decided to outsource these tasks to a commercial partner to save time and resources.

PetRescue, a nonprofit organization based in Australia, was facing challenges with its image management system. The organization, which helps match vulnerable animals with new homes, relies heavily on its ability to allow users to upload pictures of potential pets. However, the existing system was complex and time-consuming. When a user created a listing, their animal photos had to be uploaded to a front-end server then to an Amazon AWS S3 bucket, queued, manipulated then sent back to S3 and the image updated. This process often resulted in delays and break points, and the organization was unable to offer users any cropping or resizing functionality. Furthermore, the organization was struggling to optimize its website for mobile users, an increasingly important demographic for the site.

Moviepilot Inc., a media company that hosts a website and social publishing platform for movie and TV fans, was facing challenges with its infrastructure. The company was initially running its platform on hardware in Berlin, but with a site tailored to a U.S.-based audience, it needed to rely on content delivery networks (CDNs) to reduce latency and deliver an optimal user experience. The company was spending significant resources on ensuring that images worked properly on the Moviepilot platform, which was taking focus away from its core business.

Reformation, a Los Angeles-based fashion brand, primarily focuses on eCommerce, with more than half of their customers visiting its website using mobile devices. The company was using an out-of-the-box, built-in functionality included with Workarea, its eCommerce platform. It leveraged Dragonfly, a customizable RubyGem, to generate thumbnails in Ruby on Rails. However, this solution was causing issues as it required every website visitor to download the same image at the same resolution. This either caused issues with the quality of brand and product images on high-resolution screens or required unnecessary bandwidth use by the customer, depending on the platform or device they were using to access the site. Additionally, the company was experimenting with video on the site, integrating clips via Vimeo. However, the performance was choppy and not the quality experience it hoped to deliver to visitors.

Deporvillage, Spain’s top online sports retailer, was facing challenges in managing its website which features multiple images of the more than 8,000 seasonal products it offered. The company’s engineering team bore the cost of using Amazon S3 to store and serve a growing number of product images. They needed to ensure all images were responsive and optimized for size and speed, since mobile devices accounted for about 70% of its web traffic, and about 55% of all conversion was mobile. The company managed its website in six different languages and were needed to constantly add or remove images for high-turnover to items, or to address seasonal promotions.

Under Armour, a global leader in performance footwear, apparel, and equipment, was looking to extend its brand through the Under Armour Connected Fitness™ platform. This platform powers the world’s largest digital health and fitness community through a suite of applications: UA Record, MapMyFitness, Endomondo, and MyFitnessPal. As Under Armour was creating UA Record, developers began looking for a solution that would enable it to host a large quantity of images and video, and simplify image sizing and transformation. The company’s various fitness apps – which encourage professional athletes and weekend warriors to share images and other details of their workouts – have more than 150 million registered users. Developers researched various solutions that could meet their needs.

Bleacher Report was seeking a way to further enhance its content offerings by delivering short video highlights while games were still in progress. But with nearly 85 percent of users accessing Bleacher Report content on mobile devices, the company needed to ensure that short video highlights could be created quickly and streamed flawlessly, regardless of the viewing device or bandwidth. Delivering video content to users across different devices is not a trivial task. To do so, Bleacher Report would have to manipulate and optimize each video to suit every viewing device, viewport and bandwidth.

Apartment List, a fast-growing online rental marketplace, faced a significant challenge when creating its first website in 2011. The company needed to upload millions of images of apartment interiors, property exteriors, and other images from clients and deliver them to potential renters using the site. The initial system was labor-intensive, requiring two full-time engineers to maintain the natively built system. Despite the dedicated manpower, the engineering team was unable to support the design team with all the image resolutions and aspect ratios they required. Storage was another concern as Apartment List received thousands, sometimes millions, of images at a time, so it needed a reliable storage platform that could handle the library of images and properties listed on the site as it grew.

lastminute.com, a leading European online travel and leisure retailer, faced the challenge of managing over 120,000 images across multiple teams and repositories. The company had been using Cloudinary for specific use cases, such as hotel images, managed by tech teams. In parallel, a team dedicated to manual asset management, using a different DAM provider for editorial purposes. Another challenge was the time-consuming task of modifying images for new campaigns. This process could take weeks, limiting lastminute.com’s ability to quickly launch new campaigns that would let vacationers capitalize on limited-time deals.

Hipcamp, a website that allows campers to discover great destinations, faced challenges in managing thousands of images of varying quality, size, and format, uploaded by campers and property owners. Developers had to individually reformat, crop and resize each photo to meet Hipcamp’s quality standards. To ensure these images appeared correctly, regardless of how the visitors were viewing them, developers had to make multiple versions of images, designed specifically for desktops, tablets, or phone viewing. But with a team of only 11 engineers, who work on the full stack, managing images could be a full time job, leaving them less time to focus on continually innovating the company’s offerings to its users.

Babolat, a leader in B2B racquet sports equipment sales, was planning to redesign its brand website to roll out its B2C e-commerce business. The company needed a digital asset management (DAM) solution to be at the center of these changes and digital transformation. Babolat was planning to launch a new brand website in eight Asian and European countries in 2020 and the United States in 2021. The company focused on designing an e-commerce ecosystem that featured inspiring videos of top players using its gear, as well as an image-rich website that showcased its products and brand. Babolat’s team started researching various DAM solutions to enable efficient management with a centralized library of assets and the ability to easily share with external teams.

Complex Networks, a global lifestyle brand and media company, was using a variety of content management systems (CMS) for different sites, each one with its own image management process. This created unnecessary complexity for teams that worked on multiple sites. The process was burdensome for both editors and developers, who had to become well versed in multiple CMS, and know the formats, sizes and restrictions unique to each website. Editors would typically have to create and upload as many as six different versions of an image per site, and oftentimes had to work with the development team to ensure the images were appropriate for the individual site. This resulted in a very time-consuming process and slower time to market. Even with these processes in place, Complex Networks found that many of its pages weren’t optimized because some editors did not follow the standards, uploading images that were too large, which caused page load time to slow and impacted visitors’ experiences.

Stylight, a fashion and design retail search engine, was facing challenges with managing and manipulating thousands of new images being added to its site each week. With a small development team, the company needed an efficient way to ensure that these images could be viewed quickly and optimally on any device used by consumers in 16 countries. The team considered on-premises options, which would require the company to host and store its own images, but decided to look for cloud solutions instead.

Atom Tickets, a social movie ticketing app and platform, was initially a mobile-only platform for iOS and Android users. They used Amazon Web Services (AWS) for storing images and movie trailers on Amazon Simple Storage Service (S3) and Amazon Cloudfront, then Fastly, as its content delivery network. However, as the company grew and launched a website version of its platform in 2016, they realized the need for a robust media management platform, with integrated storage and CDN, to support a larger scale of customers across all touchpoints. They also launched a third-party website on behalf of Regal Theaters, which required its own content managers to manage their assets in a self-service fashion. Atom Tickets needed a powerful solution that could support the large scale of images, trailer videos, and other rich media assets, such as animated still pictures, that require significant bandwidth.

Vorwerk, a German company known for its high-tech household appliances, faced a significant challenge in delivering high-quality images and videos to its Cookidoo® recipe platform. The platform hosts over 66,000 digital recipes and is available through the web, mobile applications, and the new generation of Thermomix® smart kitchen appliances. Delivering visual content fast, globally, to all appliances and websites, proved a considerable challenge. Vorwerk needed a content delivery network (CDN) to efficiently deliver images and videos across all the regions it serves. This was particularly challenging in China, where content must be delivered through a local CDN. Additionally, IoT devices like its flagship Thermomix® appliance have special video codec requirements. Different use cases need different video variants, which takes time, resources, and technical skills to do it right, making for a very complex situation that Vorwerk had to solve.

Bloomsbury Publishing's Academic division embarked on an ambitious project to digitize encyclopedias, studies, and images from museum and private collections, as well as archive ancient manuscripts and very old printed books. The finished digital products would then be offered for sale to universities and other academic organizations, who would make the content available to all students and staff for research and educational purposes. The images of these books, manuscripts, and museum collections would be used as thumbnails for search results, merged into books view so users could digitally turn the pages, and zoom in and out. Also all products needed to be responsive, since visitors would access the content from both mobile devices and laptops. Another critical requirement was strong, yet flexible, security. Some images would be freely available to the public as part of its marketing efforts, while those that were part of published content — inside books, encyclopedias, and collections of museum objects — needed to be restricted so that only purchasers and authorized users could access the content.

The New Democratic Party of Canada was facing a dilemma. The amount of available data was growing and their homemade data integration solution wasn’t able to handle this data anymore. They needed to find a way to process this data, or lose the chance to effectively work with their constituents. The NDP quest for quality data started with over one hundred datasets from organizations like Elections Canada, Canada411, NDP regional counterparts and more. They needed a solution that could match those records, cleanse, duplicate and delete faulty records, validate them with external and internal validators and migrate them into the NDP system.

The online retailer had achieved rapid growth in just a few years since being founded. Having built the business as very much a technology-first enterprise, they were looking for a data solution to better help all areas of the organization, and one that could scale with and support the company’s expansion. The decision to build a data warehouse was made to provide rapid access to the value held within their operational data. By deploying a flexible data lake they had direct access to source systems via a replicated database. One of the key requirements from the IT team was to handle changes in the business more easily, and to be able to get quick answers to business questions from the data. While a traditional data warehouse is built to answer specific questions, the ability to access source data meant that the company could be much more flexible and responsive in its approach, and get the valuable insights they needed, fast.

ProcessGold AG is a company that specializes in process mining, a Business Intelligence (BI) discipline that allows consultants to recreate, visualize, and analyze processes within a customer’s organization based on digital footprints. These footprints can be anything from records in SAP to financial transaction logs or any other participating source of information. The success of process mining heavily relies on the completeness, accuracy, and quality of the data that is fed to the analysis. Before the implementation of CloverETL, ProcessGold would consume up to 80% of their project time extracting the required data and preparing it for analysis. This was a significant challenge as it reduced the time available for core analytical business and ensuring heightened transparency for their customers.

The logistics company was facing a challenge with the expansion to new territories which meant more address data that was notoriously difficult to validate and interpret. Particularly in Emerging Markets, the company was facing vast regional differences in both address structure and rules, and had to contend with the availability of tools and databases, or lack thereof, to process them. The company had assembled a data quality team tasked with manually verifying and cleaning the data, working shifts to meet overnight delivery deadlines. However, the ever-growing need for manpower to process more data with a quick turnaround became a bottleneck that blocked the company’s ability to expand further.