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Google Cloud Platform > Case Studies > Bareksa: Leveraging Google Kubernetes Engine for Rapid Growth and Enhanced Customer Satisfaction
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Bareksa: Leveraging Google Kubernetes Engine for Rapid Growth and Enhanced Customer Satisfaction

Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Machine Learning
Applicable Industries
  • Buildings
  • Construction & Infrastructure
Applicable Functions
  • Product Research & Development
Use Cases
  • Leasing Finance Automation
  • Time Sensitive Networking
Services
  • Cloud Planning, Design & Implementation Services
  • System Integration
The Challenge

Bareksa, an Indonesian fintech startup, was founded in 2013 with the mission to provide investment opportunities to the rapidly growing middle class in Indonesia. However, as the popularity of the platform grew, Bareksa found itself struggling to scale services during spikes in customer demand. This was a significant issue for a startup that relied on speed and 100% reliability to succeed. Additionally, its engineering team was spending a significant amount of time on DevOps tasks, such as provisioning servers and managing databases, leaving little time for creating innovative fintech solutions to grow the business. Bareksa was operating in a monolithic on-premise environment, with physical servers and a self-managed database, which was proving to be inefficient and time-consuming.

About The Customer

Bareksa is an Indonesian fintech startup that offers an online mutual fund marketplace and robo advisory service. The company aims to provide investment opportunities to millions of Indonesians who are joining the middle classes. Bareksa's digital platform opens access to a wealth of investment opportunities, allowing Indonesians to grow their wealth and plan for a secure future. In 2021, Bareksa won Series C investment from ride-hailing giant and super-app Grab. The company operates with a lean team of only three DevOps engineers tasked with keeping the platform running 24/7, regardless of market swings or fluctuations in customer demand.

The Solution

To overcome these challenges, Bareksa decided to migrate to Google Cloud, adopting Google Kubernetes Engine (GKE) as its scalable infrastructure, and Cloud SQL as its relational database. This move allowed Bareksa to seamlessly autoscale compute power for its hundreds of services with just six nodes, significantly improving operational efficiency and platform performance. The migration also freed up the engineering team to focus on product innovation, such as real-time market analysis and product customization. Additionally, the deployment of Cloud SQL as Bareksa's scalable relational database reduced the time spent on configuring and managing databases by 60%. Bareksa also switched to Google Workspace as its productivity solution, which improved workflows and collaboration, and ensured the safe and secure handling of sensitive financial data.

Operational Impact

  • The migration to Google Cloud and the adoption of Google Kubernetes Engine (GKE) and Cloud SQL significantly improved Bareksa's operational efficiency and platform performance. The engineering team was able to focus more on product innovation, leading to the development of new product features and an improved customer satisfaction rating. The switch to Google Workspace enhanced the team's ability to optimize workflows and collaborate effectively, while also ensuring the secure handling of sensitive financial data. Furthermore, the company is now able to plan for the next stage of its mission, which involves creating a more curated financial product range for its customers through big data analytics using BigQuery.

Quantitative Benefit

  • Assets under management (AUM) grew by 500% in just one year after migrating to Google Cloud.

  • Time spent on database management tasks was reduced by 60% with the deployment of Cloud SQL.

  • Customer satisfaction rating improved from 3.8 to 4.7 due to a more resilient platform and a steady stream of new product features.

Related Case Studies.

Case Study
IoT System for Tunnel Construction
The Zenitaka Corporation ('Zenitaka') has two major business areas: its architectural business focuses on structures such as government buildings, office buildings, and commercial facilities, while its civil engineering business is targeted at structures such as tunnels, bridges and dams. Within these areas, there presented two issues that have always persisted in regard to the construction of mountain tunnels. These issues are 'improving safety" and "reducing energy consumption". Mountain tunnels construction requires a massive amount of electricity. This is because there are many kinds of electrical equipment being used day and night, including construction machinery, construction lighting, and ventilating fan. Despite this, the amount of power consumption is generally not tightly managed. In many cases, the exact amount of power consumption is only ascertained when the bill from the power company becomes available. Sometimes, corporations install demand-monitoring equipment to help curb the maximum power demanded. However, even in these cases, the devices only allow the total volume of power consumption to be ascertained, or they may issue warnings to prevent the contracted volume of power from being exceeded. In order to tackle the issue of reducing power consumption, it was first necessary to obtain an accurate breakdown of how much power was being used in each particular area. In other words, we needed to be able to visualize the amount of power being consumed. Safety, was also not being managed very rigorously. Even now, tunnel construction sites often use a 'name label' system for managing entry into the work site. Specifically, red labels with white reverse sides that bear the workers' names on both sides are displayed at the tunnel work site entrance. The workers themselves then flip the name label to the appropriate side when entering or exiting from the work site to indicate whether or not they are working inside the tunnel at any given time. If a worker forgets to flip his or her name label when entering or exiting from the tunnel, management cannot be performed effectively. In order to tackle the challenges mentioned above, Zenitaka decided to build a system that could improve the safety of tunnel construction as well as reduce the amount of power consumed. In other words, this new system would facilitate a clear picture of which workers were working in each location at the mountain tunnel construction site, as well as which processes were being carried out at those respective locations at any given time. The system would maintain the safety of all workers while also carefully controlling the electrical equipment to reduce unnecessary power consumption. Having decided on the concept, our next concern was whether there existed any kind of robust hardware that would not break down at the construction work site, that could move freely in response to changes in the working environment, and that could accurately detect workers and vehicles using radio frequency identification (RFID). Given that this system would involve many components that were new to Zenitaka, we decided to enlist the cooperation of E.I.Sol Co., Ltd. ('E.I.Sol') as our joint development partner, as they had provided us with a highly practical proposal.
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