Cloud storage trends in five APAC countries

Australia
  • 89% of respondents cited expecting to increase the amount of data their organization stores in the public cloud in 2024, compared to 93% average of other respondents in the region.
  • 83% of respondents expected their organization’s public cloud storage budget to increase this year.
  • 50% of Australian respondents’ cloud storage budget was allocated to fees and not storage costs.
  • 50% of Australian respondents cited exceeding their organization’s budgeted spend on cloud storage for the previous year
  • 100% of respondents cited adopting or planning to adopt some form of AI/ML application or service within the next 12 months. Specifically, these respondents indicated a high rate of concern with addressing new data backup, protection and recovery requirements associated with AI/ML adoption
Japan
  • 94% of respondents cited plans to increase the amount of data they stored in the public cloud in 2024, compared to the global average of all respondents
  • 50% of these respondents’ cloud storage bill was going not into storage capacity but towards storage fees such as those for data operations, retrieval, transfer, and egress. These respondents ranked such unpredictable storage cost patterns (e.g., egress fees, data access fees) as a leading concern.
  • 55% of respondents cited exceeding their budgeted spend on cloud storage.
  • Generative AI ranked top among the Japan respondents as the leading workload currently deployed or planned for deployment
  • Top 2024 priorities for AI adoption among Japan respondents were cited as: accelerating innovation; development cycles for existing products/services; improving customer facing product/services
Singapore
  • 44% of billing was allocated to fees, on average, in the Singapore respondents.
  • 66% of respondents cited exceeding budgeted spend on cloud storage in 2023 — the highest rate among other regional respondents.
  • When it came to choosing a cloud storage provider/service, respondents here ranked sustainability (in terms of infrastructure architecture, service provider initiatives/commitments, or built-in tools for things like carbon footprint calculation) as the top most important consideration.
  • Respondents here ranked operational improvements as the top driver for AI/ML implementation, and chose AI/ML solutions for security and compliance (e.g., advanced anomaly detection) as the top workload implemented or planned for implementation.
India and South Korea
  • 96% of respondents across both countries here indicated their organization will increase the amount of data stored in the public cloud in 2024.
  • 96% of South Korea respondents indicated their organization will increase public cloud storage budgets in 2024, while 90% in India cited the same.
  • India and South Korea both ranked “accelerating innovation and development cycles for existing products/services” as the leading driver of AI/ML solution adoption. In terms of planned and implemented AI/ML workloads, India ranked computer vision (inclusive of a range of image and video processing or recognition) as a leading use case, and South Korea identified gaming applications (including 3D rendering) as one of its top three workloads driving AI/ML adoption, higher than any other country surveyed.