SEGA HARDlight Migrates to MongoDB Atlas to Simplify Ops and Improve Experience for Millions of Mobile Gamers

Joe Drumgoole
March 15, 2018 | Updated: July 27, 2022
#Customer Stories#Cloud#Atlas

It was way back in the summer of 1991 that Sonic the Hedgehog first chased rings across our 2D screens. Gaming has come a long way since then. From a static TV and console setup to online PC gaming in the noughties and now to mobile and virtual reality. Surprisingly, for most of those 25 years, the underlying infrastructure that powered these games hasn’t really changed much at all. It was all relational databases. But with ever increasing need for scale, flexibility, and creativity in games, that’s changing fast. SEGA HARDlight is leading this shift by adopting a DevOps culture and using MongoDB Atlas, the cloud-hosted MongoDB developer data platform, to deliver the best possible gaming experience.

Bringing Icons to Mobile Games

SEGA HARDlight is a mobile development studio for SEGA, a gaming company you might have heard of. Based in the UK’s Royal Leamington Spa, SEGA HARDlight is well known for bringing the much loved blue mascot, Sonic the Hedgehog, to the small screen. Along with a range of Sonic games, HARDlight is also responsible for building and running a number of other iconic titles such as Crazy Taxi: City Rush and Kingdom Conquest: Dark Empire.

Sonic Dash

Earlier versions of the mobile games such as Sonic Jump and Sonic Dash didn’t require a connection to the internet and had no server functionality. As they were relatively static games, developers initially supported the releases with an in-house tech stack based around Java and MySQL and hosted in SEGA HARDlight’s own data centre.

The standard practice for launching these games involved load testing the servers to the point of breaking, then provisioning the resources to handle an acceptable failure point. This limited application functionality resulted in service outages when reaching the provisioned resources’ breaking point. As the games started to add more online functionality and increased in popularity, that traditional stack started to creak.

Mobile games have an interesting load pattern. People flock in extreme numbers very soon after the release. For the most popular games, this can mean many millions of people in just a few days or even hours. The peak is usually short and then quickly drops to a long tail of dedicated players. Provisioning for this kind of traffic with a dynamic game is a major headache. The graph from the Crazy Taxi: City Rush launch in 2014 demonstrates just how spikey the traffic can be.

We spoke with Yordan Gyurchev, Technical Director at SEGA HARDlight, who explained: “With these massive volumes even minor changes in the database have a big impact. To provide a perfect gaming experience developers need to be intimately familiar with the performance trade offs of the database they’re using.”

Supersonic Scaling

SEGA HARDlight knew that the games were only going to get more online functionality and generate even more massive bursts of user activity. Much of the gaming data was also account-based so it didn’t fit naturally in the rows and columns of relational databases. In order to address these limitations, the team searched for alternatives. After reviewing Riak, Cassandra, and Couchbase, but feeling they were either too complex to manage or didn’t have the mature support needed to satisfy the company’s SLAs, the HARDlight engineers looked to MongoDB Atlas, the MongoDB developer data platform.

Then came extensive evaluations and testing across multiple dimensions such as cost, maintenance, monitoring, and backups. It was well known that MongoDB natively had the scalability and flexibility to handle large volumes and always-on deployments but HARDlight’s team had to have support on the operations side too.

Advanced operational tooling in MongoDB Atlas gave a small DevOps team of just two staffers the ability to handle and run games even as millions of people join the fray. They no longer had to worry about reliability, maintenance, upgrades, or backups. In fact, one of the clinchers was the point-in-time backup and restore feature, which meant that they can roll back to a checkpoint with the click of a button. With MongoDB Atlas and running on AWS, SEGA HARDlight was ready to take on even Boss Level scaling.

“At HARDlight we’re passionate about finding the right tool for the job. For us we could see that using a horizontally scalable document database was a perfect fit for player-account-based games,” said Gyurchev.

“The ability to create a high traffic volume, highly scalable solution is about knowing the tiny details. To do that, normally engineers need to focus on many different parts of the stack but MongoDB Atlas and MongoDB’s support gives us a considerable shortcut. If this was handled in-house we would only be as good as our database expert. Now we can rely on a wealth of knowledge, expertise, and best-in-class technology.”

Sonic Forces

HARDlight’s first MongoDB-powered game was Kingdom Conquest: Dark Empire, which was a frictionless launch from the start and gave the engineers their first experiences of MongoDB. Then in a weekend in late 2017 Sonic Forces: Speed Battle was launched on mobile. It’s a demanding, always-on application that enables constant connection to the internet and shared leaderboards. In the background a three-shard cluster running on MongoDB Atlas easily scaled to handle the complex loads as millions of gamers joined the race. The database was stable with low latency and not a single service interruption. All of this resulted in a low-stress launch, a happy DevOps team, and a very enthusiastic set of gamers.

Gyurchev concluded, “With MySQL, it had taken multiple game launches to get the database backend right. With MongoDB Atlas, big launches were a success right from the start. That’s no mean feat.”

Just as the gaming platforms have evolved and transformed through the years, so too has the database layer had to grow and adapt. SEGA HARDlight is now expanding its use of MongoDB Atlas to support all new games as they come online. By taking care of the operations, management, and scaling, MongoDB Atlas lets HARDlight focus on building and running some of the most iconic games in the world. And doing it with confidence.

Gone is the 90s infrastructure, replaced by a stack that is every bit as modern, powerful, and fast as the famous blue hedgehog.

SEGA Hardlight is looking for talented engineers to join the team. If you are interested, check out the careers page or email: hardlightcareers@sega.co.uk.

Start your Atlas journey today for free

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On 20 March, the MongoDB team will be in Sydney for this year’s largest MongoDB event in the Southern hemisphere. Join local members of the tech community for a day that’s jam-packed with technical content, swag, food, and a drinks reception! Technical Content At MongoDB.local Sydney, you’ll get to participate in 15+ sessions focusing on topics including: The cherry on top? A keynote from MongoDB CTO and Co-founder Eliot Horowitz, who will give you all the details on what’s new in MongoDB 3.6. Jumpstart Sessions Ask the Experts If you have a MongoDB question you’ve been meaning to ask, or an idea you’d like an expert on the database to give input on, schedule an appointment at the Ask the Experts table. You’ll get a 30-minute, complimentary consulting slot with a MongoDB engineer. They will be equipped with whiteboards, so you can get creative! Swag If you’ve attended a MongoDB event before, you already know that you will walk away with brand new swag items. This time will be no different. Can you guess what you’ll receive at MongoDB.local Sydney? Let us know . Fuel With so much relevant information to absorb in a day (and probably a few emails to respond to in between sessions), the conference struggle can be real. But no worries, we’ll keep you focused by providing breakfast, lunch, and plenty of coffee and tea throughout the day. Drinks Reception Ahhh, perhaps the most fun part of the day. After spending time investing in your technical education, you can grab a drink (non-alcoholic options available) and a bite to eat before heading home. This is your opportunity to digest what you’ve learned, connect with the local community, and strike up a conversation with your favorite speakers of the day. Ready to participate? Sign up for your conference pass today. You won’t regret it! Register Now Event Details: Date: 20 March, 2018 Time: 8:00am - 5:30pm Location: Doltone House - Darling Island Wharf, 48 Pirrama Road Pyrmont, NSW 2009

March 15, 2018
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The Converged AI and Application Datastore for Insurance

In the inherently information-driven insurance industry, companies ingest, analyze, and process massive amounts of data, requiring extensive decision-making. To manage this, they rely on a myriad of technologies and IT support staff to keep operations running smoothly but often lack effectiveness due to their outdated nature. Artificial intelligence (AI) holds great promise for insurers by streamlining processes, enhancing decision-making, and improving customer experiences with significantly less time, resources, and staff compared with traditional IT systems. The convergence of AI and innovative application datastores is transforming how insurers work with data. In this post, we’ll look at how these elements are reshaping the insurance industry and offering greater potential for AI-powered applications, with MongoDB at the heart of the converged AI and application datastore. Scenario planning and flexible data layers One of the primary concerns for IT leaders and decision-makers in the insurance industry is making smart technology investments. The goal is to consolidate existing technology portfolios, which often include a variety of systems like SQL Server, Oracle, and IBM IMS. Consolidation helps reduce inventory and prepare for the future. But what does future-proofing really look like? Scenario planning is an effective strategy for future-proofing. This involves imagining different plausible futures and investing in the common elements that remain beneficial across all scenarios. For insurance companies, a crucial common thread is the data layer. By making data easier to work with, companies can ensure that their technology investments remain valuable regardless of how future scenarios unfold. MongoDB’s flexible developer data platform offers a distinct architectural advantage by making data easier to work with, regardless of the cloud vendor or AI application in use. This flexibility is vital for preparing for disruptive future scenarios, whether they involve regulatory changes, market shifts, or technological advancements. Watch now: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance The role of AI and data in insurance Generative AI is revolutionizing the insurance sector, offering new ways to manage and utilize data. According to Celent's 2023 Technology Insight and Strategy Survey, 33% of companies across different industries have AI projects in planning, 29% in development, and 19% in production (shown in Figure 1 below). This indicates a significant shift towards AI-driven solutions by insurers actively experimenting with gen AI. Figure 1: Celent Technology Insight and Strategy Survey 2023 However, there's tension between maintaining existing enterprise systems and innovating with AI. Insurance companies must balance keeping the lights on with investing in AI to meet the expectations of boards and stakeholders. The solution lies in integrating AI in a way that enhances operational efficiency without overwhelming existing systems. However, data challenges need to be addressed to achieve this, specifically around access to data. According to a Workday Global Survey , only 4% of respondents said their data is fully accessible, and 59% say their enterprise data is somewhat or completely siloed. Without a solid data foundation, insurers will struggle to achieve the benefits they are looking for from AI. Data architectures and unstructured data When adopting advanced technologies like AI and ML, which require data as the foundation, organizations often grapple with the challenge of integrating these innovations into legacy systems due to their inflexibility and resistance to modification. A robust data architecture is essential for future-proofing and consolidating technology investments. Insurance companies often deal with a vast amount of unstructured data, such as claim images and videos, which can be challenging to manage. By leveraging AI, specifically through vector search and large language models, companies can efficiently process and analyze this data. MongoDB is ideal for managing unstructured data due to its flexible, JSON-like document model, which accommodates a wide variety of data types and structures without requiring a predefined schema. Additionally, MongoDB’s flexibility enables insurers to integrate seamlessly with various technologies, making it a versatile and powerful solution for unstructured data management. For example, consider an insurance adjuster assessing damage from claim photos. Traditionally, this would require manually reviewing each image. With AI, the photos can be converted into vector embeddings and matched against a database of similar claims, drastically speeding up the process. This not only improves efficiency but also enhances the accuracy of assessments. The converged AI and application datastore with MongoDB Building a single view of data across various systems is a game-changer for the insurance industry. Data warehouses and data lakes have long provided single views of customer and claim data, but they often rely on historical data, which may be outdated. The next step is integrating real-time data with these views to make them more dynamic and actionable. 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By making smart technology investments, leveraging AI to manage unstructured data, and building robust data architectures, insurance companies can future-proof their operations and embrace innovation. A versatile and flexible data platform provides the foundation for these advancements, enabling companies to make their data more accessible, actionable, and valuable. The MongoDB Atlas developer data platform puts powerful AI and analytics capabilities directly in the hands of developers and offers the capabilities to enrich applications by consolidating, ingesting, and acting on any data type instantly. Because MongoDB serves as the operational data store (ODS)—with its flexible document model—insurers can efficiently handle large volumes of data in real-time. By integrating MongoDB with AI/ML platforms, insurers can develop models trained on the most accurate and up-to-date data, thereby addressing the critical need for adaptability and agility in the face of evolving technologies. With built-in security controls across all data, whether managed in a customer environment or through MongoDB Atlas, a fully managed cloud service, MongoDB ensures robust security with features such as authentication (single sign-on and multi-factor authentication), role-based access controls, and comprehensive data encryption. These security measures act as a safeguard for sensitive data, mitigating the risk of unauthorized access from external parties and providing organizations with the confidence to embrace AI and ML technologies. If you would like to learn more about the convergence of AI and application datastores, visit the following resources: Video: The Converged AI and Application Datastore: How API's, AI & Data are Reshaping Insurance Paper: Innovation in Insurance with Artificial Intelligence The MongoDB Solutions Library is curated with tailored solutions to help developers kick-start their projects

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