AVM.io

Name: AVM.io
Address: 1818 Library Street suite 500, Reston, VA, 20190, US
Telephone: +12134586011

Contact information, map and directions, contact form, opening hours, services, ratings, photos, videos and announcements from AVM.io, Software Company, 1818 Library Street suite 500, Reston, VA.

AVM is an AWS Advanced Partner and global consultancy based in Virginia, specializing in Data, Security, and Observability — all accelerated through AI-driven approaches to architecture, automation, and ex*****on.

05/28/2026

The Future of Cloud Migration Is Becoming Agentic...

AWS Transform’s latest capabilities highlight an important shift in how organizations approach cloud modernization: the future of cloud migration is becoming agentic. Migration is evolving beyond static assessments and manual planning into a more intelligent, context-aware process that helps teams make smarter decisions faster.

With new features such as what-if scenario modeling, customizable assumptions, flexible data inputs, and enhanced TCO analysis, AWS Transform enables organizations to simulate different migration paths and compare outcomes before making critical decisions. Teams can evaluate factors such as regions, resource utilization, service mapping, and infrastructure costs across services like EC2, FSx, S3, SQL Server, and virtual desktops.

What makes this especially interesting is that the focus is no longer only on moving workloads. The platform also considers broader business outcomes such as productivity, resilience, agility, and sustainability. This represents a move toward agentic systems that assist in planning, analyzing, and optimizing decisions rather than simply executing tasks.

Cloud migration is increasingly becoming less about “lift and shift” and more about intelligent decision-making.

How do you see AI and agentic systems changing cloud migration strategies in your organization?

05/26/2026

The Next Security Battle Isn’t in Code - It’s in the Supply Chain...

GitHub has introduced new npm security controls to strengthen software supply chain protection and reduce the risk of compromised packages reaching developers. One major feature, called staged publishing, now requires package maintainers to manually approve releases using two-factor authentication (2FA) before packages become publicly available. Instead of immediately publishing a package, it first enters a staging area where a maintainer must verify and approve it. This adds a “proof of presence” layer and helps protect even automated CI/CD workflows.

GitHub also introduced new package installation controls that allow developers to explicitly manage where packages can be installed from, such as local files, remote URLs, and directories. These controls create stronger safeguards against unauthorized or risky package sources.

These updates come at a time when software supply chain attacks are increasing rapidly, making security controls more critical than ever. Protecting code today is no longer just about applications—it’s also about securing dependencies and development pipelines.

How is your team strengthening software supply chain security? Share your thoughts and practices below.

05/25/2026

The Real AI Race Is No Longer About Adoption...

Microsoft cancelled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months.

Source: https://x.com/hedgiemarkets/status/2057531661785628841?s=46

At AVM, we’re watching a clear shift: companies like Starbucks, Uber, and Microsoft are starting to rethink how they deploy AI. AI isn’t going away but the way it’s implemented is maturing quickly. The winners won’t be the ones who adopted first. They’ll be the ones who learned fastest and optimized best.

At AVM, we believe the next wave of AI will be defined by precision, not proliferation.

05/22/2026

Starbucks just shut down an AI program designed to automate inventory counts after just nine months, after the system repeatedly miscounted and mislabeled items.

That’s a textbook example of AI built for speed, not accuracy—and it’s a warning every operations‑ and AI‑led leader should heed.

At AVM Consulting, we often see businesses focus on deploying AI tools rather than designing systems that can scale reliably. The result? Costly tools that erode trust instead of scaling efficiency. AI should strengthen operations, not create friction.

If you’re exploring AI‑driven operations from inventory, to supply chain, to field‑service workflows let’s talk about how to avoid the ‘Starbucks moment’ and build systems that last.

Have you seen examples where AI improved processes—or created unexpected challenges? Share your thoughts and experiences below.

https://x.com/techmeme/status/2057545916417208735?s=46

05/21/2026

Cloud Boundaries Are Disappearing Faster Than We Expected...

AWS has announced the public preview of AWS Interconnect for multicloud connectivity with Oracle Cloud Infrastructure (OCI). As more organizations adopt multicloud strategies, many are looking for greater flexibility, easier interoperability, and the freedom to use the technologies that best fit their business needs. However, connecting workloads across different cloud providers has often required complex, do-it-yourself networking approaches that can be difficult to build and manage at scale.

AWS Interconnect aims to simplify this process by providing a purpose-built solution for creating secure, resilient, and scalable private connections between cloud environments. Instead of managing complex networking layers, organizations can quickly establish connectivity and streamline communication between cloud platforms. OCI is the latest cloud provider to support the open specification behind AWS Interconnect, joining Google Cloud and with Microsoft Azure support expected later in 2026.

This move highlights a broader shift in cloud strategy: enterprises increasingly need seamless connectivity, not isolated cloud environments.

What do you think—will simpler multicloud connectivity accelerate enterprise cloud adoption? Share your thoughts below.

05/19/2026

Security at the Edge Is Evolving: CloudFront Adds mTLS Passthrough...

Amazon CloudFront has introduced a new passthrough mode for mutual TLS (mTLS) viewer authentication, giving organizations more flexibility in how they manage secure connections. With this feature, CloudFront can now forward a client’s certificate chain directly to the origin server without validating it at the edge.

This is especially useful for organizations that already have mTLS validation processes running at their origin infrastructure. Instead of redesigning their security setup, they can now integrate CloudFront into existing environments while keeping authentication logic unchanged. At the same time, they still gain the benefits of CloudFront’s global edge network, including performance improvements and scalability.

CloudFront continues to support other mTLS options as well. Required mode validates all certificates at the edge, while Optional mode supports environments with both authenticated and unauthenticated users. The new passthrough mode is available at no additional cost, making it easier for teams to adopt secure architectures without extra overhead.

How do you see mTLS evolving for modern cloud and edge security strategies? Share your thoughts below.

05/18/2026

What happens when AI usage becomes a status symbol instead of a business tool?

A growing trend called “tokenmaxxing” is raising important questions across Big Tech.

https://www.tomshardware.com/tech-industry/big-tech/big-tech-has-a-tokenmaxxing-habit

Reports suggest employees at companies like Amazon, Meta, and Microsoft are increasing AI tool usage simply to boost internal metrics and leaderboard rankings—not always to improve productivity or business outcomes.
The concern is bigger than workplace culture. As organizations invest billions into AI infrastructure, GPU capacity, and inference scaling, inflated token consumption can blur the line between real adoption and performative usage. More AI activity does not automatically mean better business value. At the same time, this highlights a critical challenge for enterprises: measuring AI success correctly. The focus should not just be on token counts, prompts, or usage statistics, but on measurable outcomes such as faster.
At AVM, we believe AI should drive better decisions, stronger workflows, and measurable value—not just bigger token counts.

05/14/2026

Datadog has launched GPU Monitoring to help organizations better manage the growing cost and complexity of AI infrastructure. As AI adoption increases, GPU usage is becoming a major expense, yet many companies still lack clear visibility into how GPUs are being used, where costs are rising, or why workloads fail.

The new solution gives teams a unified view across the AI stack by connecting GPU health, performance, and cost data in one place. This helps organizations identify idle or overloaded GPUs, troubleshoot AI training and inference issues faster, and avoid unnecessary spending on additional hardware.

Datadog says the platform can help businesses scale AI projects more efficiently by improving resource planning, reducing downtime, and maximizing ROI on GPU investments. It also enables engineering and machine learning teams to collaborate more effectively with shared visibility into workloads and infrastructure performance.

As AI infrastructure costs continue to rise, observability and GPU efficiency are quickly becoming critical for enterprise AI success.

👉 How is your organization managing GPU costs and AI infrastructure visibility at scale?

05/12/2026

Datadog’s State of AI Engineering 2026 report shows that operational complexity is becoming one of the biggest challenges in scaling AI reliably. While AI adoption is growing rapidly, nearly 1 in 20 AI requests now fail in production, with most failures linked to capacity limits rather than the models themselves.

The report also highlights that companies are increasingly using multiple AI models and more advanced agent workflows, which adds complexity to production environments. At the same time, the amount of data processed by AI systems is growing significantly, putting additional pressure on infrastructure and workflows.

According to Datadog, success in AI will depend not only on choosing the right models but also on building strong operational control, visibility, and observability across the entire AI stack. Without proper monitoring and governance, scaling AI can lead to slowdowns, errors, and unreliable user experiences.

👉 Is your organization prepared to manage the operational complexity of AI at scale? Share your thoughts in the comments.

05/08/2026

We’re excited to share that AVM’s AI Training Program is now officially underway.

Led by our Head of Data and AI, Baseer Khan, this initiative is already bringing teams together through highly interactive, hands-on sessions focused on real-world AI applications.

Rather than being purely theoretical, the program is designed to be practical and engaging, and encouraging participants to actively explore how AI can be applied in day-to-day work. The sessions are sparking great discussions, experimentation, and a deeper understanding of how AI can drive smarter decision-making across the organization.

This marks an important step in AVM’s ongoing journey to strengthen AI capability internally and build a more data-driven culture.

Looking forward to the continued learning, collaboration, and innovation this program will unlock as it progresses.

Address

1818 Library Street Suite 500
Reston, VA
20190

Telephone

+12134586011

Website

https://www.avm.io/

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