A senior IT Architect specialising in building long-lasting cloud-based platforms for lower TCO.

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Building and deploying highly available platforms isn't about increasing your cloud technology spend. It is more about how you use technologies and resources intelligently in order to achieve the goals of your business.

With a holistic and pragmatic approach to application design, infrastructure architecture and operations, organizations of any size can achieve successful, fault-tolerant, scalable and HA applications without breaking the bank.

Lower total cost of ownership ... and you can sleep through the night.

Find out how today.

I've spent the past 30 years designing, building and managing highly available, resilient, secure and scalable enterprise workloads running on on-premise, cloud and containerised platforms of all kinds.

I have a unique combination of experience, having held junior and senior positions in every area in IT and possessing a deep hands-on technical knowledge of numerous products. I have successfully delivered dozens of enterprise projects, from small in-house clusters to global containerised hybrid cloud platforms.

Examples of work I've done for past clients:

  • Design and delivery of a multi-region, multi-environment, HA platform based on Azure, Docker, Confluent Kafka and Mongo
  • Productionalising Kafka, Redis, Elasticsearch and Solr-based applications
  • Implementing multi-level Azure cloud redundancy for data-driven applications
  • Tracking down performance bottlenecks in Kafka, Elasticsearch, Redis, Storm and Spark
  • Stabilisation of complex Java-based containerised applications
  • Single-pane-of glass dashboards for global infrastructure monitoring
  • Azure cloud architecture for HA production workloads
  • Data architecture design for Solr, Mongo and Elasticsearch
  • Greenfield implementation of a custom, hybrid-cloud, Kubernetes-based PaaS

Here are a few of the technologies I work with on a regular basis:

  • Cloud providers: Azure, AWS
  • CI/CD: Terraform, Cloud Formation, Jenkins, GitLab, Helm, GoCD, ArgoCD
  • ITOA: Splunk, DataDog, Catchpoint, Fluentd, Kowl, Prometheus, Grafana, New Relic
  • Microservices: Docker, OpenShift, LXC, Kubernetes
  • Data processing: Kafka (open source and Confluent), Storm, Spark
  • Databases: PostgreSQL, MariaDB, MySQL, SQL Server
  • NoSQL: Mongo, Elasticsearch, Solr, Redis
  • Big Data: Hadoop, Hive, HBase, MapReduce
  • Coding: Java, Python, Bash, C

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