Insights on AI, Software & Cloud Engineering
Practical articles from the Vikgol engineering team — covering Generative AI, LLM development, AWS, web development, and software best practices.
Cloud Monitoring and Observability: Metrics, Logs, Traces and the Bill
Observability costs rose 212% in four years, and 84% of users tell Gartner they are struggling with them. The estate did not grow that fast — a forty-service system doesn't cost six times a monolith to run, but it emits six times the telemetry. Here is what actually drives the number, and what to do about it without going blind.
Kubernetes Cost Optimisation: Right-Sizing, Autoscaling and Spot in 2026
Average CPU utilisation across production Kubernetes clusters is 8% — down from 10% the year before. More tooling, more FinOps teams, more blog posts about this exact subject, and the number went backwards. That tells you the problem is not a tooling problem.
Multi-Cloud, Hybrid, or Single Cloud: An Honest Framework for 2026
87% of organisations run multi-cloud and 73% run hybrid estates. Very few of them decided to. Most arrived there through an acquisition, a team that preferred a different provider, or a vendor deal someone signed three years ago — and then called it a strategy retroactively. This is a framework for making the decision deliberately, including when the right answer is to consolidate.
Running AI Workloads in the Cloud: GPU Cost and Scaling in 2026
The same NVIDIA H100 rents for around $1.38 per GPU-hour on a marketplace and $12.29 on Azure. Identical silicon, identical memory, a twelvefold spread — the only variable is who is selling it. And that spread is still not the most expensive decision most teams get wrong.
Application Performance Optimisation: What Actually Moves Revenue in 2026
Portent's analysis put conversion at 3.05% for pages loading in one second and 0.41% at five seconds. Seven times the revenue from the same traffic and the same page. Yet most performance work targets a lab score that has almost no relationship to what Google actually measures — which is why teams optimise for weeks and watch Search Console refuse to move.
Spec-Driven Development: Why AI Coding Needs a Contract in 2026
Ninety per cent of developers now use AI at work. Only thirteen per cent use it across the full software lifecycle. That gap is the whole story — AI is stuck at autocomplete in most teams, and the reason is not model capability. It is that agents build faster than anyone can specify what they should be building.
AIOps and Self-Healing Infrastructure: What Actually Prevents Downtime in 2026
Forrester expects 60% of enterprises to fail at AIOps this year. Not because the technology doesn't work — Deloitte's own data shows 17% of organisations reaching genuine autonomous remediation. The failures cluster somewhere less interesting than the AI: most teams have nothing worth automating yet.
Self-Service Customer Portals: What Actually Reduces Support Costs in 2026
Vendor decks promise 50 to 60 percent ticket deflection. Independent benchmarks put the median between 22 and 41 percent. That gap is not a rounding error — it is the difference between a business case that holds up and one that quietly fails in year two. Here is what the data actually supports, and what to build instead.
AI Agents and the End of Per-Seat Software
Agents don't log in. So what are you paying per seat for? What seat compression means for enterprise buyers — and the hybrid pricing models replacing it in 2026.
Generative AI Consulting: The Enterprise Adoption Guide for 2026
88% of enterprises use AI. Only 6% see real profit impact. The adoption barriers, the ROI data, and a practical 6-phase framework for 2026.
API-First Development: Why Modern Enterprises Are Building Around APIs in 2026
Design the API contract before writing a single line of code — the 2026 enterprise standard for faster delivery, parallel development, and plug-and-play integrations.
Data Lake vs Data Warehouse vs Data Lakehouse: Which One Does Your Business Need in 2026?
Real 2026 costs, honest trade-offs, and a 5-question framework to choose the right data architecture — lake, warehouse, or lakehouse.
AI-Powered Data Analytics: Benefits for Modern Enterprises in 2026
From reactive dashboards to real-time predictive intelligence — how enterprises are using AI analytics to make decisions in seconds, not weeks.
Building Enterprise AI Agents: Architecture & Best Practices for 2026
The 6-layer architecture that separates production AI agents from demo failures — orchestration, memory, governance, and the mistakes that kill most enterprise agent projects.
LLM Cost Optimisation: How We Reduced GPT-4 Costs by 65%
Redis caching, model routing, prompt compression, and batch processing — how we cut a production AI platform's API bill from $41,800 to $14,620/month.
GCC in India 2026: Why Global Companies Are Building Their Next Engineering Team Here
India now hosts 2,100+ Global Capability Centers employing 2 million professionals. Here's what the GCC boom means for engineering teams and AI talent.
Agentic AI vs Traditional AI: What Every Founder Needs to Know
The AI landscape has shifted. Traditional AI is no longer enough. Here is a practical framework for founders and CTOs on when to use each approach.
RAG vs Fine-Tuning: Which AI Approach is Right for Your Business?
A practical decision framework — when to use RAG, when to fine-tune, and when to combine both for enterprise AI.
What Is Agentic AI — And Why Enterprise Adoption Is Harder Than It Looks
Agentic AI is the most significant architectural change in enterprise software since the move to cloud. Here is what it actually means and where it delivers results.
How Real-Time AI Analytics Is Transforming Customer Experience for Fintech
Fintech customers are unforgiving. Here is how real-time AI pipelines cut onboarding drop-offs by 60% and detect fraud in milliseconds.
Cost-Efficient Jenkins Setup with AWS Spot Instances
Cut your CI/CD infrastructure costs significantly by running Jenkins on AWS Spot Instances — with full failover and auto-recovery.
Achieving High Availability on AWS: Multi-AZ Setup with Terraform
A step-by-step guide to building a resilient, multi-AZ AWS architecture using Terraform — the way we do it in production.
How We Reduced AWS Costs by 60% for a UK Fintech Platform
The exact strategies we used to cut a UK fintech's AWS bill from £70K to £28K — step by step.
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Cloud Monitoring and Observability: Metrics, Logs, Traces and the Bill
Kubernetes Cost Optimisation: Right-Sizing, Autoscaling and Spot in 2026
Multi-Cloud, Hybrid, or Single Cloud: An Honest Framework for 2026
Running AI Workloads in the Cloud: GPU Cost and Scaling in 2026
Application Performance Optimisation: What Actually Moves Revenue in 2026
Spec-Driven Development: Why AI Coding Needs a Contract in 2026
AIOps and Self-Healing Infrastructure: What Actually Prevents Downtime in 2026
Self-Service Customer Portals: What Actually Reduces Support Costs in 2026
AI Agents and the End of Per-Seat Software
Generative AI Consulting: The Enterprise Adoption Guide for 2026
API-First Development: Why Modern Enterprises Are Building Around APIs in 2026
Data Lake vs Data Warehouse vs Data Lakehouse: Which One Does Your Business Need?
AI-Powered Data Analytics: Benefits for Modern Enterprises in 2026
Building Enterprise AI Agents: Architecture & Best Practices for 2026
LLM Cost Optimisation: How We Reduced GPT-4 Costs by 65%
GCC in India 2026: Why Global Companies Are Building Their Next Engineering Team Here
Agentic AI vs Traditional AI: What Every Founder Needs to Know
RAG vs Fine-Tuning: Which AI Approach is Right for Your Business?
What Is Agentic AI — And Why Enterprise Adoption Is Harder Than It Looks
How Real-Time AI Analytics Is Transforming Fintech
Creating a Cost-Efficient Jenkins Setup with AWS Spot Instances
Achieving High Availability on AWS with Terraform
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