Over the years we’ve delivered tens of projects. These are the highlights
As an interim CTO, Milan led the team of software developers and data scientists and delivered the highly available healthcare research platform from greenfield to production.
Java, MongoDB, IBM Cloud, IBM Watson, Ansible, GoCD
Navigating complex healthcare privacy and security regulations as well as the external audit from one of the biggest pharmacology companies in the world. All with very tight deadlines and limited resources.
In order to deliver an enterprise-ready platform we had to, among all the engineering effort, fully automate and document infrastructure set up, document all the relevant procedures (business continuity plan, privacy and security design and considerations, backup and restore procedures and so on).
Even though we were building an MVP, we quickly realized how often the requirements change and due to complexity of the data flow we decided to heavily cover the platform with the integration test suite from early on. This decision was crucial to the product's success later on - it allowed us to be confident when making changes requested by the external auditors just before putting the platform in production.
By being very careful and proactive about the scope and feature set, we managed to put the platform in production on time and budget and onboard the first patients on time and budget.
Vladimir worked as a software architect with multiple development teams to create event-driven, highly scalable platform based on microservices from greenfield to production.
Java, Spring Boot, Apache Kafka, Schema Registry, Apache Cassandra, Redis, Elasticsearch, PostgreSQL, Jenkins, Ansible
Making a highly configurable system as multi-tenant is, with a large amount of regulatory requirements for each country. Keeping low latency within the critical features while developing a highly scalable and distributed system.
Aim of the project was a system rewrite of a monolithic platform which was in development for more than 12 years. Vladimir started the project with the requirements gathering sessions upon which the architecture proposal was written. Requirements gathering pinpointed two major challenges that new architecture will face, leading to a Proof of Concept (PoC).
After successful PoC, the development started and the team was growing to meet the needs of the project. The challenge was to keep architecture and code as uniform as possible to allow for easy onboarding and flexibility when team members switch between services. This also provided the simplicity in build and deployment pipelines.
The platform was put in production without major problems or reworks.
As an interim CTO, Milan led the product development team working on the enterprise level platform with strict privacy and security requirements. Under his leadership, delivery was streamlined and made predictable, productivity was increased and the developers’ onboarding process shortened.
Python, AWS Cloud (S3, CloudFormation, Quicksight, Athena)
Complex system that was hard to maintain and extend. AWS S3 was used as a database. Technical leadership left the company and the development team had a lot of trouble delivering features in the predictable manner, and ownership and team motivation was very low.
Milan joined the team as a backend engineer. He introduced and followed Scrum methodology and improved the transparency of the product development process. Once the entire product team adopted the process and saw that the transparency was a good thing, the ownership and motivation increased drastically. This led to Milan being assigned an interim CTO role. On the technical side, we identified both the strong sides of the current platform (reliability, privacy by design), and the weak points (hard to extend, complex, undocumented). When we improved the documentation (a lot!) and started building new components on the edge of the system (which use the API to communicate with the core), developer’s productivity increased a lot and the onboarding process was shortened.
Being obsessed with automated software testing and quality assurance, Milan created a declarative test data generator for Java. It allows easy specifying test data format and quickly generating - the goal was to create the opposite of the SQL for test data. Instead of querying the data, it generates the data - instead of “give me all the users born in 1981, having a driving licence and owning a car ” the data generator allows for this kind of “create me 10 000 random users out of which 150 will be born in 1981 and have a driving licence and owning a car”. The library heavily relies on generics and is used for generating test data for an automated test suite for several projects in production.
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