Constantin Michael Weisser, Developer in São Paulo, Brazil
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Constantin Michael Weisser

Verified Expert  in Engineering

DevOps Engineer and Developer

São Paulo, Brazil
Toptal Member Since
November 15, 2022

Michael is a DevOps engineer and consultant who has worked as a developer, architect, team lead, and consultant for the last seven years. Specializing in automation engineering, continuous delivery, QA automation, and infrastructure engineering, he is passionate about building great products with great teams using modern technology. Michael is a methodic problem solver, experienced in managing trade-offs and building efficient and future-proof solutions.


Clojure, Contract Testing, Test Automation, Continuous Deployment...
Novatec Consulting
Azure, Java, Kotlin, Bash, SQL, Apache Kafka, Jira, Confluence, JDBC, Hibernate...
Novatec Consulting
Amazon Web Services (AWS), Azure, Azure Kubernetes Service (AKS), Jenkins...




Preferred Environment

Terraform, Amazon Web Services (AWS), Azure, Linux, Java, GitHub, Azure DevOps, Splunk, Kubernetes, Docker

The most amazing...

...thing I've worked on is a large-scale deployment safety platform securing thousands of weekly production rollouts, cherishing product engineers' peace of mind.

Work Experience

Senior Software Engineer

2021 - PRESENT
  • Extended a global contract testing platform by targeted multi-country support, as regional differences are a significant concern in our business. The platform secures thousands of code changes in over 1,200 microservices every week.
  • Engineered the performance of an automated test in every pipeline execution. Reduced the overall execution time and cost by 35%, enabling cheaper operations and reducing wait time for all engineers.
  • Planned and oversaw the migration of contract test execution and contract testing data of over 1,200 microservices to provide new features and a better development experience.
Technologies: Clojure, Contract Testing, Test Automation, Continuous Deployment, Performance Engineering, Microservices, Apache Kafka, GitHub, Google BigQuery, Data-driven Decision-making, Whiteboarding, Decision Modeling, Request for Comment (RFC), CI/CD Pipelines, Test-driven Development (TDD), Functional Programming, REST APIs, Amazon Web Services (AWS), Architecture, Programming Languages, Infrastructure as Code (IaC), DevOps, Networking, Git, Metrics, Continuous Integration (CI), Continuous Development (CD), Continuous Delivery (CD)

Senior Consultant

2018 - 2021
Novatec Consulting
  • Led a DevOps transformation project, advising the managers of a mid-sized tech company with less than 1,000 employees to pick key technologies, reorganize team structures, and adopt new problem-solving methods. Reduced lead time for changes by 90%.
  • Developed and maintained a continuous delivery platform on Azure for six product teams with scarce operations engineers, enabling easy operation for twenty microservices. Trained engineers from all teams in crucial technologies and best practices.
  • Built an infrastructure testing strategy for the automated rollout of a cloud-native application platform. Implemented the first release for the automated test suite, then integrated it into all infrastructure automation pipelines.
  • Devised a disaster recovery plan for a cloud-native application landscape, covering unforeseen data loss, regional outages, and emergency failover options.
  • Simplified the development experience by automatically configuring the working environment for all engineers on the team using configuration management and carefully automated scripts.
Technologies: Azure, Java, Kotlin, Bash, SQL, Apache Kafka, Jira, Confluence, JDBC, Hibernate, Kubernetes, Docker, OpenID Connect (OIDC), REST, WebSockets, Terraform, Pulumi, Git, GitHub, Bitbucket, Ansible, Puppet, Jenkins, Azure Pipelines, GitHub Actions, Miro, Slack, Grafana, Prometheus, Fluentd, Splunk, Agile, Continuous Deployment, Infrastructure as Code (IaC), Infrastructure Testing, Spring Boot, Micronaut, Azure DevOps, Linux, Arch Linux, Ubuntu, DevOps, Continuous Learning, Data-driven Decision-making, Key Performance Indicators (KPIs), REST APIs, Amazon Web Services (AWS), Architecture, Programming Languages, Clojure, Networking, Test Automation, CI/CD Pipelines, Helm, Metrics, Infrastructure, Continuous Integration (CI), Continuous Development (CD), Continuous Delivery (CD), Helmfile

Software Engineer

2016 - 2018
Novatec Consulting
  • Built an Azure-based environment to deploy microservices on AKS with Azure SQL continuously. The environment was completely provisioned with Terraform and tested automatically on infrastructure changes.
  • Developed an event-sourcing application based on Apache Kafka, which maintained a transaction-safe audit log of all user events on the platform to autogenerate business-level reports.
  • Migrated the set of microservices from a proprietary Cloud Foundry to a public Azure AKS-based environment. Devised a migration strategy for Jenkins pipelines to Azure DevOps pipelines, following a strict pipelines-as-code approach.
Technologies: Amazon Web Services (AWS), Azure, Azure Kubernetes Service (AKS), Jenkins, Terraform, Spring Boot, Apache Kafka, Microservices, Pipelines, Architecture, Linux, Java, Infrastructure as Code (IaC), Infrastructure, Continuous Integration (CI), Back-end, Log Collector

DevOps Transformation: From Traditional Deployments to High Velocity

The client was a B2B logistics enterprise with a stable customer base, but competition was catching up. The leaders wanted to explore ways to secure the market position and identified high lead time and failure rate as the primary issues. They faced technical difficulties such as an aging on-premises stack, complex monoliths, and scattered configuration. They were confronted with cultural hurdles, such as unclear responsibilities for incident response.

I was part of the DevOps transformation leadership team. I guided the CICD team in building CD as an in-house product. I designed the company's tech stack with the infrastructure team and advised the management team in picking key technologies. I also supported the management team in choosing KPIs that determined the transformation's success.

During my engagement, the first microservices were deployed to the infrastructure on Azure. Terraform automatically provisioned the cloud environment, which could significantly improve the infrastructure's reliability. Instead of scheduling massive releases and high risk, engineers deployed changes within hours or days of picking up a task. The management team now had access to metrics such as Lead Time for Changes and Deployment Frequency.

Continuous Delivery Platform for Microservices on Azure

I've contributed to this project as a DevOps engineer. I initially developed an automated cloud architecture to run around twenty microservices on Azure. Software from six product teams was automatically built and deployed via Azure DevOps pipelines. The deployment target was AKS on the Azure cloud. The whole infrastructure was described and automated via Terraform modules. One of the biggest challenges was the unavailability of operations engineers that could help to operate the infrastructure. Consequently, I standardized systematic manual development processes and provided reusable solutions to engineers to speed up rollouts and diminish cognitive load.

Automatic Scaling to Dozens of Similar Environments

This client hosted dozens of similar environments, one per customer. Initially, all environments were traditional on-premises deployments that engineers built and maintained manually. The customer wanted to reduce the set up time from weeks to hours. They were looking for a scalable solution to add a new customer on demand.

I advised my client to select ideal technologies for cloud-based deployment on Azure. The client had only a few people for operations, so I chose scalable low-maintenance solutions such as Azure Appservice. I built Terraform modules as the blueprint for a single environment. Automation and configuration management complemented the code to quickly scale up to dozens or even hundreds of instances. I devised an update strategy and best practices for monitoring and log management at scale. Since the application had only been used on-premises before, I supported the engineers in turning it into cloud-native services and debugging tricky platform dependencies.

With my solution, my client could build a new environment in minutes. All deployments were independently configurable in size and feature flags. That way, they could adjust the deployment to the exact needs while keeping management overhead to a minimum.

Extending a Fully Automated Contract Testing Platform for Safe Continuous Deployments

The project aimed at extending a contract testing platform that ensures safe synchronous and asynchronous communication between more than a thousand microservices.

I've contributed as a software engineer, leading this project that supports multi-country deployments, which caused regional differences in the microservices' communication patterns. I devised a migration strategy and ensured a smooth rollout of the new features without interrupting the hundreds of daily test runs on which engineers rely. I also automated metrics collection to follow up on feature adoption.

SaaS Application for Lean Construction Management

A Spring Boot and Kubernetes-based cloud-native SaaS application that provides well-structured and auditable communication between construction site managers, lead workers, and subcontractors on large-scale construction sites.

I contributed to this project as a back-end software engineer. I worked closely with the product owners and other stakeholders to deliver new features, which are digitized versions of the usual civil construction modus operandi. I provided vital pieces to cross-cutting solutions, such as solving the exactly-once semantics for sending Apache Kafka messages and committing to a database.

I was also responsible for CI/CD infrastructure built on Jenkins with automatically provisioned worker nodes on AWS.

Central Customer Identification System

A client from the financial sector accumulated several unconnected databases with customer records over the years. Back-office clerks had to consult all those systems manually when trying to identify a customer and the products they already had.

As a back-end software engineer, I designed and implemented a central customer identification system. Data was regularly pulled from the existing customer databases and potentially merged with records from other data sources. The merge criteria were built as an extensible rule set. I created a straightforward user interface that enabled the search and visualization of customer records. This central entry point reduced clerks' effort from more than half an hour to less than a minute for each customer request.
2014 - 2016

Master's Degree in Computer Science

University of Stuttgart - Stuttgart, Germany

2011 - 2014

Bachelor's Degree in Computer Science

University of Stuttgart - Stuttgart, Germany


REST APIs, JDBC, OpenAPI, Terragrunt


Terraform, GitHub, Git, Jenkins, Helm, Splunk, Jira, Confluence, Bitbucket, Ansible, Puppet, Miro, Slack, Grafana, Fluentd, Gradle, Azure Kubernetes Service (AKS), Helmfile, Log Collector


Java, Bash, Clojure, Perl, Kotlin, SQL, Go


Continuous Deployment, DevOps, Test Automation, Functional Programming, Continuous Integration (CI), Continuous Development (CD), Continuous Delivery (CD), Azure DevOps, Software-defined Networking (SDN), REST, Agile, Microservices, Test-driven Development (TDD)


Linux, Docker, Azure IaaS, Azure, Kubernetes, Amazon Web Services (AWS), Apache Kafka, Arch Linux, Ubuntu, Oracle, LAMP


Hibernate, Spring Boot, Micronaut, Thymeleaf


Databases, PostgreSQL, MySQL


Programming Languages, Software Engineering, Infrastructure as Code (IaC), Infrastructure Testing, Whiteboarding, Pipelines, Infrastructure, GitHub Actions, Data-driven Decision-making, Decision Modeling, Architecture, Computer Science, Operating Systems, Complexity Theory, Algorithms, Mathematics, Networking, Distributed Systems, Graph Theory, OpenID Connect (OIDC), WebSockets, Pulumi, Azure Pipelines, Prometheus, Continuous Learning, Key Performance Indicators (KPIs), Contract Testing, Performance Engineering, Google BigQuery, Request for Comment (RFC), CI/CD Pipelines, Psychology, Metrics, Datomic, HTTP, Back-end, DevOps Engineer

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