Projects & Case Studies
Case Study: Optimizing a Stressed Redis Cluster for a SaaS Application
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The Challenge: Critical Application Instability
A fast-growing SaaS provider was experiencing severe performance issues with its Redis Enterprise cluster on Azure. The problems manifested as high latency, service timeouts, and general application instability, directly impacting user experience. The client’s in-house team had exhausted their diagnostic tools and was unable to pinpoint the root cause of the intermittent but catastrophic issues.
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Case Study: Unlocking Enterprise Sales with Secure On-Premise Deployments in Azure
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The Challenge: A Major Enterprise Sales Blocker
While working with a leading B2B SaaS provider, we faced a recurring and costly problem: large enterprise customers, particularly in finance and healthcare, loved our product but were unable to use our multi-tenant cloud offering due to their strict data residency and compliance policies. They required our entire SaaS application and their data to reside within their own corporate Azure environment.
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Project Deep Dive: Artefact Mirror
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The Problem: Dependency on Public Registries
Modern applications rely on dozens of public container images and Helm charts. This creates a significant business risk: what happens if Docker Hub, Quay.io, or a public Helm repository goes down? Deployments fail, and you are at the mercy of a third-party outage. Furthermore, enterprises often need to run in air-gapped environments or require security scans on all artifacts before they can be used.
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Case Study: From Cost Center to Innovation Hub with a Modern Data Warehouse
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Executive Summary
A leading technology company was facing spiraling monthly costs and significant performance limitations with their legacy, cloud-based database solution. Their existing setup was not only expensive but also lacked the flexibility to support future AI and real-time analytics initiatives. By leveraging a modern, open-source-first strategy on Kubernetes, I architected and deployed a new data warehouse platform that not only outperformed their previous solution but also reduced their projected monthly cloud database expenditure by an estimated 5-6 figures, paving the way for new revenue streams.
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