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If you’re running data-intensive workloads on AWS today, you’ve likely run into the same wall: performance comes at a price — and often an unpredictable one.

Cloud data is more important than ever. Organizations are relying on it to power AI, analytics, and mission-critical workloads — and storage strategies are evolving to keep pace. To help IT and data leaders understand the trends, challenges, and opportunities shaping cloud data growth, we’re launching the 2026 State of Cloud Data & Storage Benchmark Survey. 

As businesses continue their digital transformations, cloud migration remains a critical priority. Whether you’re an emerging cloud-native startup or a well-established company transitioning legacy systems, optimizing cloud performance is crucial. Key cloud providers like AWS, Microsoft Azure, and Google Cloud have enabled companies to scale faster than ever. However, with increased scalability comes the challenge of ensuring high-performance operations. In this landscape, two fundamental metrics—Throughput and IOPS—are essential to understand for ensuring top-tier cloud performance.

The landscape of digital transformation is witnessing a significant surge in organizations migrating to the cloud, a trend that underscores the strategic shift towards more agile, scalable, and cost-efficient IT solutions. Recent industry reports and surveys consistently highlight that a substantial majority of organizations are either in the process of migrating to the cloud or planning to do so. The drive of application migration to the cloud is not restricted to specific sectors but spans a diverse range of industries, from healthcare and finance to education and retail, reflecting the pervasive recognition of the cloud’s transformative potential. 

The cloud is now a proven, viable solution for EHR and large healthcare systems and critical to infrastructure modernization and delivering a better experience for patients and providers.

The holidays are over! You can now take a breath before assessing how the season was for both your business and your IT team. During the holiday season, online retailers can see a 10x spike in traffic. Black Friday and Cyber Week represents 20% or more of a retailer’s holiday revenue. However, website and database performance issues can cut into revenue dramatically. This can lead to abandoned carts, lost sales, and a drop in customer confidence and loyalty.

You’ve designed your system, and you’ve deployed your SaaS application. Now what? This is where your focus shifts to optimization and tuning. Even a fully optimized SaaS application needs adjustment and continuous tuning as workload patterns change.

Congratulations! You’ve successfully deployed turned your software into a SaaS offering. You might be ready to log off and head on some much needed PTO but there’s a few things you should do to ensure that the offering is a success. We’ve collected a number of the most impactful practices that successful SaaS platform operators have shared. These also extend into many other application environments, so even if you aren’t a SaaS administrator, these practices can still be put into place.

Looking to make the change from an on-prem solution to a Software as a Service (SaaS) offering? Your SaaS applications will be a set of services and features that are available in a hosted environment for your customers and clients. As you beginning designing your application requirement, there are a few decisions that will need to be determined in order to both provide a great experience for your clients as well as meet your business requirements. In this post, we will cover some of the decisions you will be make as you begin to design your SaaS architecture.

Machine learning stands out as a thrilling breakthrough for companies aiming to extract greater knowledge and insight from their data reservoirs. The primary hurdles when integrating machine learning into data applications encompass the proficiency gap required for implementation and the consequential influence on applications and databases.