Technology News: Latest Updates from 2026-04-26
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This report summarizes the technology news from 2026-04-26 and is based exclusively on the original texts of the sources.
🔑 At a Glance
- Amazon Quick integrates Visier’s AI assistant Vee
- Google Cloud Next ’26: AI agents in the spotlight
- Product sprints for developer portals and content
- DVD Store 3.5: New workload profiles for database testing
- GPT-5.5 and Codex now available on Databricks
Amazon Quick Integrates Visier’s AI Assistant Vee
According to aws.amazon.com, Amazon Quick now integrates Visier’s AI assistant Vee via the Model Context Protocol (MCP). The announcement published on April 24, 2026 targets HR leaders, finance managers, and operations executives who can now access Visier’s workforce intelligence data directly within their Amazon Quick workspace without having to switch between different tools.
After setting up the connection via Visier’s remote MCP server, users can ask questions in natural language about headcount, turnover, tenure, and open positions. The answers are based on Visier’s controlled workforce data model. Vee can also be invoked from automated Quick Flows, for example to create recurring workforce reports or draft documents.
Amazon Quick intelligently routes relevant queries to Vee and delivers contextualized answers together with internal company knowledge — such as budgets, policies, and plans stored in Quick Spaces. This way, every answer is intended to reflect the complete organizational picture.
The Visier integration with Amazon Quick is available in all AWS Regions where Amazon Quick is offered. Further information can be found in the integration guide and on the Amazon Quick integration page.
Google Cloud Next ’26: AI Agents in the Spotlight
At Google Cloud Next ’26 in Las Vegas, Google declared the beginning of a new era: Artificial intelligence is set to not only support work but autonomously complete tasks as an independent agent. At the heart of the announcements is the Gemini Enterprise Agent Platform — an end-to-end development environment that enables enterprises to create, manage, and scale AI agents. Available models include Gemini 3.1 Pro for complex workflows, Gemini 3.1 Flash Image (also known as Nano Banana 2) for visual content, Lyria 3 for professional audio, and Claude from Anthropic Opus 4.7. With Agent Studio as a low-code interface and the no-code tool Agent Designer, even users without programming skills can build their own agents.
New hardware generations provide the required computing power. The TPU 8t was designed for training AI models, while the TPU 8i is optimized for inference and is said to deliver 80% better performance per dollar. Additionally, Google will be among the first providers of the new NVIDIA Vera Rubin NVL72 systems. The custom-developed Virgo Network connects supercomputers to each other, and Managed Lustre achieves transfer rates of 10 terabytes per second.
| Component | Details |
|---|---|
| Gemini 3.1 Pro | Most powerful model for complex workflows |
| Gemini 3.1 Flash Image | Image generation (also called Nano Banana 2) |
| Lyria 3 | Professional audio generation |
| TPU 8t | Optimized for model training |
| TPU 8i | Optimized for inference, 80% better performance per dollar |
| NVIDIA Vera Rubin NVL72 | New GPU systems available |
| Managed Lustre | Up to 10 TB/s data throughput |
To enable AI agents to access relevant enterprise data, Google introduced the Agentic Data Cloud. Its Knowledge Catalog automatically organizes and links data assets using Gemini. The Cross-Cloud Lakehouse is based on Apache Iceberg and enables queries across cloud boundaries — even for data in AWS — without having to move it.
In the area of security, Google combines its threat intelligence with the platform from Wiz, which is now part of Google Cloud. Specialized agents such as the Threat Hunting Agent, the Detection Engineering Agent, and the Third-Party Context Agent are designed to proactively detect threats and autonomously create security rules. Wiz now also supports Databricks as well as additional AI studios and multicloud platforms.
Product Sprints for Developer Portals and Content
According to blogs.cisco.com, when developing developer portals, speed in decision-making is often more important than perfectionism. Instead of spending months working on a feature, one should start with a concrete and measurable hypothesis — for example, that half of users drop off in the conversion funnel after the first API call, or that the average session duration in the Cloud IDE is under 10 seconds.
After each release, the article recommends measuring success using product-market fit indicators. These include, for example, growth in usage and registration with a focus on Activation Rate and Return Usage, the correlation between documentation visits and API requests, and the so-called Time to First Hello World (TTFHW). According to the source, decisions should be validated through three pillars: product analytics, user feedback, and business impact.
| Indicator | Benchmark according to source |
|---|---|
| Time-to-completion deviation | A lab designed for 30 minutes that takes an average of one hour indicates too much friction |
| TTFHW (first app, integration, or API call) | Under 10 minutes |
| Cloud IDE session duration (problem indicator) | Under 10 seconds |
| Time-to-completion increase (tutorials) | 20 minutes |
| Critical pages (low session duration) | Under 15 seconds |
| Threshold for short-duration pages | Under 2 minutes |
As a practical example, the article describes the introduction of a README-first Cloud IDE at DevNet. User feedback and analytics showed that the default VS Code start screen was distracting, especially in specialized environments like Cisco NSO containers. The solution was to open the repository’s README guide by default. In addition, analytics events such as copy_for_ai or download_openapi_doc are recommended to understand how content is consumed by users and AI-powered development tools.
DVD Store 3.5: New Workload Profiles for Database Testing
The open-source database testing tool DVD Store, which has been widely used since its initial release in 2005, now supports documented workload profiles for different load scenarios. The software simulates an online store where users log in, browse, rate, and purchase DVDs. It runs on SQL Server, Oracle, PostgreSQL, and MySQL and uses common database features such as stored procedures, indexes, foreign keys, full-text search, complex multi-table queries, and transactions.
Originally, DVD Store was designed as a CPU-intensive workload, but parameters could always be adjusted to also create network-intensive, disk-intensive, or memory-intensive profiles. Examples of these profiles are now provided and documented in the official GitHub repository at https://github.com/dvdstore/ds35/tree/main/workload_profiles.
The validation tests were performed on a single virtual machine running on a VMware Cloud Foundation (VCF) ESX 9.0 server. The guest operating system was Windows Server 2022 with SQL Server 2022. All performance metrics were captured from the ESX host perspective using esxtop.
| Workload Profile | Change compared to CPU profile |
|---|---|
| Disk-intensive | 13x more IOPS |
| High IOPS | 95x more IOPS, 7x more than disk-intensive |
| Network-intensive | 15x more Mb sent per second |
| Memory-intensive | 2.9x more active memory |
All configuration details for the individual workload profiles, including specific DVD Store parameters and database settings, can be found in the ds35_workload_profiles.txt file in the GitHub project.
GPT-5.5 and Codex Now Available on Databricks
According to databricks.com, Databricks now natively supports GPT-5.5. The model is described as OpenAI’s most powerful frontier model for agent-based enterprise applications, complex document analysis, and long-horizon coding agents. All GPT-5.5 usage on Databricks is managed through Unity AI Gateway, which is designed to provide centralized security, cost control, and monitoring — for both GPT-5.5 model inference and OpenAI’s Codex coding workflows.
| Feature | Description |
|---|---|
| Genie | Natural language analytics interface that enables business users to query enterprise data in natural language |
| Agent Bricks Custom Agents | Build custom agents for complex multi-step workflows — such as document analysis or business process automation — with deployment as Databricks Apps |
| Lakeflow Spark Declarative Pipelines for GenAI ETL | Automated document processing with AI transformations such as summarization, extraction, or classification |
According to the source, GPT-5.5 is said to deliver more reliable results particularly when processing complex, real-world documents such as scanned PDFs, tables, and multi-format data. Developers can build GPT-5.5-powered agents using their preferred tools and frameworks and deploy them as fully managed, serverless Databricks Apps.
According to Databricks, GPT-5.5 is available immediately on AWS, Azure, and GCP. Unity AI Gateway serves as the central control plane for security and governance across all agents, queries, and coding workflows.
Conclusion
Today’s technology news reveals a clear trend toward AI-powered agents and platform integrations: Amazon Quick incorporates Visier’s AI assistant Vee, Google introduces its Gemini Enterprise Agent Platform at Cloud Next ’26, and Databricks makes GPT-5.5 along with Codex natively available. In addition, articles on product sprints for developer portals and the updated DVD Store 3.5 provide practical insights for software development and database testing.
Frequently Asked Questions
How can users access Visier’s workforce data in Amazon Quick?
After setting up the connection via Visier’s remote MCP server, users can ask questions in natural language about headcount, turnover, tenure, and open positions without having to switch between different tools.
What new AI models did Google introduce at Cloud Next ’26?
Google presented Gemini 3.1 Pro for complex workflows, Gemini 3.1 Flash Image (Nano Banana 2) for visual content, Lyria 3 for professional audio, and the new TPU 8t for the required computing power, among others.
What workload profiles does DVD Store 3.5 offer for database testing?
DVD Store 3.5 now provides documented workload profiles covering CPU-intensive, network-intensive, disk-intensive, and memory-intensive scenarios. The profiles are available in the official GitHub repository under ds35/workload_profiles and were validated on a VM running VMware Cloud Foundation ESX 9.0.
📚 Sources
- 🔗 aws.amazon.com: Amazon Quick now integrates with Visier’s Vee agent for workforce inte…
- 🔗 blog.google: 7 highlights from Google Cloud Next ’26…
- 🔗 blogs.cisco.com: Product sprints for developer-oriented portals and content…
- 🔗 blogs.vmware.com: CPU, Disk, Network, and Memory Workload Profiles for DVD Store Databas…
- 🔗 databricks.com: OpenAI GPT-5.5 + Codex, now available and fully-governed in Databricks…
