Hareesh Iyer

Autonomous software is moving from experiment to production — and faster than many teams expected. Coding LLMs, orchestration platforms, and event-driven architectures are changing how work gets done. Over 60% of companies are adopting autonomous software to boost efficiency, and that shift forces a rethink of architecture, ops and risk management. Gartner and McKinsey have flagged this as a structural change, not just a tooling upgrade. - Architecture: Treat autonomy as a platform service, not a point tool. Design for observable control loops, clear APIs, and pluggable decision models so you can swap or tune components without a forklift upgrade. - Scale and cost: Autonomous agents amplify small inefficiencies quickly. Plan for dynamic resource consumption and chargeback models that make behavior visible — otherwise your cloud bill becomes the loudest signal in the room. - Security and compliance: Decisions automated at scale require policy-as-code and runtime guardrails. Combine static policy checks with continuous monitoring; one without the other creates blind spots. - Governance and accountability: Who owns a machine-made decision? Define ownership boundaries early — product, platform, or legal — and instrument audit trails that are human-readable. - Operations and resilience: Expect more novel failure modes. Build recovery patterns and chaos tests for autonomous behaviours the same way you test for hardware faults. Most teams focus on accuracy metrics and forget that autonomy trades predictability for speed. The paradox: faster decision loops improve throughput but raise coupling, making rollout strategy a core architectural concern. How are you balancing control, speed, and cost in your autonomous stacks? Share a constraint you're wrestling with or a pattern that worked. Follow for more such content.

“Elastic has become PepsiCo’s gold standard for telemetry ingestion, correlation, and resolution velocity. It now sets performance baselines across our observability ecosystem.” — Vinod Chilakalapudi, Director - Observability at One PepsiCo Operations Center See how PepsiCo standardized with Elastic to achieve Full Stack Observability, cutting incident resolution times by 30% and hardware costs by up to 25% annually: https://gag.gl/uQmBXk

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Amazon Web Services (AWS) hiking prices on EC2 Capacity Blocks is less about GPUs and more about certainty. A sharp and telling story by Nidhi Singal Jain in Network World. Thanks for the opportunity to contribute insights. The link to the story is attached, and for deeper analysis, you can head over to greyhoundresearch.com. Here’s how we at Greyhound Research see it. What used to be a niche option has quietly become essential. EC2 Capacity Blocks are not where enterprises spend most of their GPU budget, but they are where they go when failure is not an option. Most training still runs on long-term commitments or on-demand capacity. But when a model retrain is tied to a product launch, a regulatory cycle, or a revenue forecast, certainty matters more than saving a few percentage points. That is why these blocks are increasingly treated like insurance. You may not need them every day, but when everything has to run in a specific window, you need to know the GPUs will actually be there. AI work is no longer experimental. It is tied to business calendars. Miss the window, and you miss the outcome. The price hike itself is logical. AWS is not charging for raw compute. It is charging for predictability. Capacity Blocks sit inside tightly engineered UltraClusters, and holding that space open has real opportunity cost in a constrained market. Guaranteed access is now a premium feature. Other clouds are doing the same thing in different ways. Google uses scheduled reservations. Azure relies on regional capacity holds and long-term commitments. Pricing pressure does not always show up as a visible hike. Sometimes it shows up as quotas, approvals, or long waits. The common shift is this: availability is no longer assumed. For enterprises, this changes behaviour. CIOs are becoming far more deliberate about which workloads deserve guaranteed capacity and which can wait. Critical retraining gets booked. Experiments get pushed elsewhere. Idle time suddenly hurts when capacity is reserved and expensive. No one is abandoning AWS over this. But many are hedging. Core workloads stay put, while smaller jobs get tested across clouds. Not an exodus. A pressure release valve. The bigger change is mental. CIOs are no longer starting with “what does a GPU cost per hour”. They are starting with “Can I get it when I need it?” For 2026 and beyond, certainty has become the real currency of AI infrastructure. https://lnkd.in/gCxZDZbr #GreyhoundStandpoint #AWS #AIInfrastructure #GPUs #EnterpriseAI #CloudStrategy #CIO

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At AI World Vegas, Oracle’s Sharat Chander told The Times of India that young engineers can stay relevant by strengthening their fundamentals — from concurrency and performance tuning to API design — and using AI tools to accelerate, not replace, learning. https://lnkd.in/eAzFdRc5

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“Elastic has become PepsiCo’s gold standard for telemetry ingestion, correlation, and resolution velocity. It now sets performance baselines across our observability ecosystem.” — Vinod Chilakalapudi, Director - Observability at One PepsiCo Operations Center See how PepsiCo standardized with Elastic to achieve Full Stack Observability, cutting incident resolution times by 30% and hardware costs by up to 25% annually: https://gag.gl/uQmBXk

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Amazon Web Services (AWS) Secrets Manager now makes it even easier to consume secrets on EKS clusters! Today, Secrets Manager announces EKS Add on for AWS Secrets Store CSI Driver provider -a simplified experience making the installation a single step process, eliminating the development overhead. This new integration allows customers to retrieve secrets from AWS Secrets Manager and parameters from AWS Systems Manager Parameter Store and mount them as files on their Kubernetes clusters running on Amazon Elastic Kubernetes Service (Amazon EKS). Check out What’s New Post: https://lnkd.in/gceqajq7 Get started with the feature:  https://lnkd.in/gAmSnnja Hit me up if you are interested to learn more, become a partner or connect with me at Re:Invent 2025 #AWS #security #reInvent2025 #AWSSecretsManager

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