Commvault focuses on data protection and recovery in the event of cyberattacks, ransomware, and system failures for both enterprise environments and cloud providers. Its clients include 3M, Sony, and Hilton.
"In agentic environments, agents mutate state across data, systems, and configurations in ways that compound fast and are hard to trace," says Pranay Ahlawat, Chief Technology and AI Officer at Commvault.
If GenAI enhances or speeds things up, they should get more value faster and shouldn't pay the same rates. Our customers' buying patterns shifted to favor agile, outcome-based, AI-powered engagements with faster time to value and clear ROI, creating a significant revenue and workload concentration risk in our top revenue cohort.
As businesses contend with ever-increasing data volumes and performance-intensive applications such as AI model training, AI inferencing and high-performance computing, they need infrastructure that delivers speed, scalability and efficiency without added complexity.
Uber has built HiveSync, a sharded batch replication system that keeps Hive and HDFS data synchronized across multiple regions, handling millions of Hive events daily. HiveSync ensures cross-region data consistency, enables Uber's disaster recovery strategy, and eliminates inefficiency caused by the secondary region sitting idle, which previously incurred hardware costs equal to the primary, while still maintaining high availability. Built initially on the open-source Airbnb ReAir project, HiveSync has been extended with sharding, DAG-based orchestration, and a separation of control and data planes.
A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?
A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."
Specifically, analysts pulled some numbers out of their... hat, and decided that Amazon would end up spending $150 billion on CapEx for 2026. Amazon then proclaimed that it was going to be a lot closer to $200 billion ("no worries, you only missed by the GDP of Croatia"), and the industry spent the next two business weeks just beating the absolute stuffing out of their stock for it. How badly? Shares fell 11% after hours, then kept falling for nine straight sessions - the longest losing streak since 2006 - erasing more than $450 billion in market value. That's more than the entire market cap of most companies that analysts are supposedly experts at evaluating.
The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.