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Mike Trienis

All about data product and services that scale; from design to implementation

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Professional for Hire

I love building data products that scale. That means implementing simple solutions with minimal maintenance through automation and eloquent designs.

Technical expertise

My software experience spans the full stack; from system level deployment to application implementation. In particular, I spent quite a bit of time working with the technologies

Professional projects

A few projects that I designed, implemented and delivered to a production environment.

Data pipeline and analytics framework

Implemented a high-throughput data pipeline that enabled massive amounts of data to be published to AWS Kinesis and consumed with Apache Spark. The infrastructure enabled in-flight computation as well as data integration with a variety of datastores.

  • Data pushed to S3, AWS Redshift and MongoDB within 1 minute.
  • Supports real-time machine learning and aggregation.

Real-time dashboards

Built a highly scalable analytics reporting system as part of the core product of our software as a service (SaaS) platform. The system was designed using a services oriented architecture (SOA) model to minimize coupling. It also supported horizontal scaling by distributing writes and reads across nodes. Over a million data points can be processed within minutes and rendered within seconds to the end user.

  • Dashboard metrics are updated within a minute.
  • Supports up to ~500 million events per day.

Cloud infrastructure and automation

Automated the deployment and buildup of an AWS cloud infrastructure that auto-scales with traffic demand. The infrastructure was automated using Ansible and enabled the deployment of multi-instance clusters with varying configuration and topology.

  • Multi-instance cluster collapsed into a single-instance.
  • Tear-down or build-up an environment within 5 minutes.
  • Decouple subsystems with independent deployment trains.

Decoupled platform architecture

Architected as well as implemented a new configuration management system for the core QP platform at QuickMobile. The design decoupled the system services from the application to enable greater flexibility and reduced down-down during deployments. The configuration mechanism was implemented using Ansible in idempotent style.