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AirAsia flies Superapp into the cloud

AirAsia is a Malaysian low-cost airline that operates domestic and international flights to more than 165 destinations in 25 countries. It is the largest airline in Malaysia by fleet size and destinations served. AirAsia Launched Superapp in October 2020. The mobile app for Android and Apple originally focused on flights and related services, but as the Covid-19 pandemic severely restricted international travel, it was clear that AirAsia needed to broaden its scope. Adding services such as food delivery, taxis, and hotels to Superapp proved to be highly successful. To date, the app has been downloaded 40 million times, with 13 million monthly active users, and 15 product and service offerings. “Most of our services are on Google Kubernetes Engine (GKE), so everything we run is in containers,” says Danial Hui, Head of Software Engineering at AirAsia at MongoDB.local Kuala Lumpur. “For Superapp and the AirAsia.com website, all our applications are connected to APIs and microservices.” With Superapp’s rapid rise in popularity, the previous database’s scalability and quota limits were causing problems. “Superapp is really a collection of apps that work quite differently and have different database needs. We switched to MongoDB because it has integration and geospatial functions that work very well for us,” adds Hui. “Most of our microservices are now on MongoDB. It’s flexible, it’s agile, and it complements our microservice architecture.” “ We realized that as a growing company, we might not be able to invest so much energy, skill sets or resources into managing MongoDB,” Hui explains. “That was one of the main drivers of why we went for MongoDB Atlas.” Time to market was also an important factor. With AirAsia looking to scale to five countries in 15 months, representing a 1,000% growth rate, being able to automatically set up multiple clusters in different countries was a substantial benefit. Another key feature that attracted Hui was the multi-cloud capabilities of MongoDB Atlas. AirAsia’s cloud provider of choice is Google Cloud Platform, but in territories where demand for resources can be unusually high, such as Singapore, the ability to switch to AWS has been highly advantageous. “The multi-cloud aspect of MongoDB Atlas is excellent; it works seamlessly,” concludes Hui. “We only use it when we absolutely have to, but it ensures that we never have any issues.”

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Globe Group turbocharges digital overhaul with multi-cloud approach

Globe Group is one of the largest telecommunications companies in the Philippines, with almost 87 million customers. A cloud-native since its 2014 launch, 70-80% of its workload is on AWS. Globe’s focus has always been rapid digital delivery. With 800 applications across 7,000 servers and 5.8 petabytes of storage on public and private clouds, a recent incident galvanized Globe to re-energize its cloud usage and innovate faster. Presenting at MongoDB.local Singapore, Ricky Mohan, Globe Telecom’s Head of Cloud Enablement and Service Operations, told the story. On December 25th, 2022, Ricky got notification of what appeared to be a distributed denial-of-service (DDoS) attack. Customers in huge numbers were attempting to visit Globe’s website and apply to register their SIM cards, as they were required by a new government mandate to do. If they failed within a given time, they’d lose their phone number. But Globe hadn’t designed the system to have millions of customers accessing its call systems downstream. Each time they solved one point of failure, another would fail behind it. The incident lasted over two days. Emerging from the crisis, Ricky and the team realized that most of Globe’s legacy systems had backend synchronous dependency, so that only once one operational task was completed could the next be tackled. They began to rethink how to ‘do digital at Globe.' The team started small, with an auto-capturing site for SIM-card-only registration. They wanted the customer journey to take a zero-negative path, meaning that if a particular system failed, instead of customers receiving a ‘try again later’ message, Globe could capture the order and process it themselves. The aims were to: never go offline Zero-touch provisioning reduce human involvement To meet the challenge, Globe formed a cross-functional engineering group with MongoDB –MongoDB Atlas was already supporting several of Globes products and services – as a key partner. Already running on AWS, the team chose Google Cloud Platform (GCP) for the project from a multi-cloud perspective. “It benefits us to have healthy competition between multiple partners,” explains Ricky, “and MongoDB Atlas being multi-cloud by default allows us to use data across multiple cloud vendors.” The infrastructure was configured with a multi-cloud platform engineering mindset, creating patterns that could be re-used by developer teams so they could be quicker to realize business value. Typically, at a large-scale enterprise, a project of such complexity, involving SAP, provisioning systems, and Operational Support Systems (OSS) and Business Support Systems (BSS) layers, would take at least nine months to deliver. The Globe team nicknamed their effort, ‘Project Impossible.’ Here’s why: 4 months to delivery Nearly 90% reduction in opertational running costs 70% reduction in human involvement to process orders “We were able to deliver so quickly because of the technology choices we made to reduce the work of developers, and MongoDB played a major part in that,” says Ricky.

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