Summary
Since beginning his work in DevOps and cloud-based technologies, Jonathan has built a set of varied skills centered around automation and “everything-as-code”. He has most often helped lead efforts to design, implement, and support both cloud-native infrastructures and automated delivery pipelines for enterprise-level software. Jonathan’s strengths lie in his experience with various cloud platforms, development lifecycles, and deployment strategies for containerized microservices. He is most in his element when closely collaborating with a small, dedicated team of developers and engineers with a focus on best practices for infrastructure-as-code, configuration management, and code management.
Certifications
Skills & Proficiencies
Amazon Web Services
Microsoft Azure
Google Cloud Platform
JenkinsCI
Harness
GitLab
GitHub Actions
Docker
Kubernetes
Helm
Datadog
Dynatrace
Terraform
Groovy
Bash
Python
Ruby
Golang
Git
Chef
SaltStack
Ansible
Experience
- Contributor on the Mavericks team for Ford ProIntelligence
- Managing the DevOps requirements and requests of multiple development teams
- Developed additional features for Jenkins pipelines
- Used Terraform to manage and deploy resources in Google Cloud Platform
- Took part in a Cost Optimization initiative, resulting in a reduction of approximately $3 million dollars in monthly spend
- Automated deployment and provisioning of EC2-backed SQL instances
- Automated the auditing process for thousands of EC2 instances across multiple AWS accounts
- Automated the deployment of security and monitoring agents to EC2 instances in production environments
- Created a custom Terraform provider to create and maintain third-party resources used by mission-critical applications
- Helped migrate monitoring and alerting from AWS CloudWatch to Datadog
- Worked on implementing CI/CD pipelines via GitHub Actions
- Created Terraform modules to be used by teams across the organization
- Supported development teams with data migrations in MongoDB Atlas and new service deployments
- Managed code delivery and permissions for containerized AI training built on AWS SageMaker and Lambda
- Helped improve functionality of delivery pipelines for AWS Lambda-based microservices
- Created documentation and standards for managing multiple Jenkins instances
- Participated in technical deep-dives with customers to help validate and scope potential engagements
- Dissected and documented existing applications deployed to both physical data centers and AWS
- Created and executed a plan for migrating an existing containerized application to dedicated AWS infrastructure via Terraform and Drone
- Improved automation for the deployment of new infrastructure and web applications via Terraform and Jenkins
- Upgraded and reimplemented configuration management in Ansible for servers hosting mission critical applications and services
- Implemented infrastructure for multiple environments in AWS ECS+Fargate and EKS using Terraform
- Designed and managed user and inter-service access to Kubernetes-backed microservices via NGINX Ingress Controller
- Created charts using Helm 3 to deploy microservices to Kubernetes
- Managed GitLab repositories and corresponding CI/CD pipelines for each service
- Worked with development teams to standardize versioning strategy and define testing strategies
- Eliminated messy and error-prone Bash scripting via Terraform and Ansible to deploy dynamic lab environments for five to fifteen participants, including a bastion host with individual users authenticated to dedicated Kubernetes clusters in GCP
- Instructed week-long labs focused on utilizing the Dynatrace product and the data it collected to enhance and automate development lifecycles and enable auto-remediation and advanced deployments in production-like environments
- Went on-site with clients as a Dynatrace and DevOps SME to discover issues and bottlenecks within their development process, help optimize monitoring using the Dynatrace product, and scope work for ongoing engagements
- Worked with clients to create well-defined quality gates and integrate the Dynatrace product into their larger testing and automation strategies using platforms such as JenkinsCI, Azure DevOps, and Octopus Deploy.
- Helped develop the Autonomous Cloud Enablement practice as part of Dynatrace professional services
- Engaged potential clients during the sales process to judge eligibility and help scope possible work and requirements
- Conducted AWS Well-Architected Reviews
- Validated statements of work and began sprint planning once signed
- Designed and documented proposed architectures for AWS or Azure
- Defined state for instances and VMs using configuration manage tools such as SaltStack and Chef
- Created and managed cloud infrastructures using AWS CloudFormation or Terraform
- Automated code integration, testing, and deployment using Jenkins Pipelines and custom library
- Enabled client development teams to easily deploy on-demand environments using tools and services such as Vagrant, Packer, and AWS ElasticBeanstalk
- Successfully migrated client applications to AWS while meeting compliance requirements such as PCI, HIPAA, and SOC2
- Ensured timely support for various client infrastructures and applications by working with SREs on the Managed Support team to quickly troubleshoot and correct issues as they occurred
- Managed variable case load, including escalations and long-running data migrations
- Remotely administered multiple Linux boxes in the field via SSH
- Solved issues ranging from hardware failures (RAID arrays, motherboards, etc) to networking issues and misconfiguration
- Corresponded with customers via email and phone to successfully close tickets
- Worked with development and engineering teams to identify bugs in firmware versions