When One Month Becomes Two Days
Infrastructure migrations have long been synonymous with weeks of manual effort — extracting data, categorising information, reformatting for new systems, and checking every input for accuracy. Our recent migration from PRTG to Zabbix proved there’s a better way.
Through intelligent use of enterprise AI assistance, our Cloud and Infrastructure teams compressed a month’s worth of traditional work into just two days — achieving faster turnaround, higher accuracy, and predictable outcomes.
The Traditional Challenge
Past monitoring platform migrations taught us the painful reality of manual processes. When we previously moved from OpManager to PRTG, it consumed nearly a month of engineering time.
The workflow involved exporting data, manually documenting each component, and carefully re-entering information into the new platform. With hundreds of monitoring points, human error was inevitable, typos in service tags, mismatched vendor details, or contact information swapped between similar links.
Manual approaches simply don’t scale efficiently.
How we Applied AI
This time, our Cloud Services team designed Python scripts to pull data directly from PRTG via API. AI assistance helped structure the scripting logic and extract the metadata required for Zabbix import.
Our Infrastructure team then worked within a ChatGPT-enabled development environment that integrated directly into Visual Studio Code. Instead of switching between browser-based prompts and local coding tools, engineers could collaborate seamlessly with an AI coding assistant that categorised and reformatted data automatically.
The result: all required data successfully extracted, structured, and validated — without the tedious manual input that previously consumed weeks of work.
Accuracy at Scale
The true breakthrough wasn’t speed alone — it was precision.
When handling hundreds of monitoring points across multiple vendors, small manual errors compound quickly. Links with similar names can be mislabelled. Contact details can be misplaced. Service tags can easily drift out of sync.
AI assistance removed those risks by standardising the format, validating consistency, and ensuring every field aligned correctly before import. Once one device line imported successfully, the AI could replicate the formatting across all others — guaranteeing accuracy across the entire dataset.
Predictable Timelines Through Strategic AI Implementation
With the foundation automated, our teams could focus on validation rather than data wrangling.
Traditional migrations often discover formatting errors mid-import, forcing rework and delay. Our AI-assisted approach caught inconsistencies before any import attempts, enabling clean first-run success.
Two days of focused engineering time replaced nearly a month of manual effort. More importantly, the process delivered confidence — knowing the import would succeed the first time.
What we Learned
AI Enhances, Doesn’t Replace: Technical expertise remains essential. Our engineers designed the scripts, defined the data structure and validated every result. AI accelerated the work, but human oversight and expertise ensured success.
Team Collaboration Multiplies Impact: By combining cloud scripting, AI-driven code integration and infrastructure insight, our teams achieved what neither could have accomplished alone with the same efficiency.
Confidence Comes from Accuracy: Traditional migrations carry uncertainty until the final import. AI-assisted workflows validate accuracy earlier in the process, giving teams confidence and clients predictability.
Scalability Without Proportional Effort: Manual processes scale linearly with workload. AI-assisted transformations scale exponentially — handling larger volumes without increasing human effort.
Looking Ahead
We’re not replacing engineering expertise with AI, we’re amplifying it!
This migration demonstrates how intelligent automation can eliminate repetitive work, reduce human error, and free skilled engineers to focus on strategic architecture rather than manual transformation.
As we plan future migrations, one question will guide us:
Which parts of this process can AI assist with to improve accuracy and reduce effort?
Increasingly, that answer will determine whether a migration takes months — or just days.
Team Acknowledgement
This success reflects the collaboration between our Cloud Services and Infrastructure teams. By combining engineering expertise with practical AI implementation, they transformed a traditionally time-intensive task into a model of precision, speed and confidence.
