Meet Dave

The client operated a high-traffic multimedia streaming platform, managing a logging service that ingested over 300 TB of data daily across multiple multi-region OpenSearch clusters. They sought a DevOps engineer to optimize their architecture, enhance performance, and reduce operational costs while ensuring scalability and stability.

As a DevOps engineer, I designed and improved the architecture for a hot-warm logging solution, implementing autoscaling to minimize manual interventions and enhance cost-effectiveness. My efforts led to a 50% boost in cluster performance and a significant reduction in search latencies and costs through advanced indexing strategies and mapping optimizations.

I developed a hybrid solution for Kinesis streams, merging provisioned and custom autoscaling modes, cutting Kinesis costs by 40%. Additionally, I established a blue/green deployment strategy to safeguard critical configurations during updates and created Helm charts to automate cluster management via FluxCD.

Through troubleshooting, cloud cost optimization, and maintaining IaC with CI/CD pipelines, I ensured the system's reliability and improved service level agreements (SLAs), allowing the client to focus on their core objectives.

The client had an Elastic cluster on AWS, serving between 400 and 500GB of data per day. They wanted an engineer to support and manage their infrastructure and the stack as well as optimize and scale the cluster to provide monitoring solutions to other teams. With the increasing growth, the development of automation was also needed.

As a DevOps engineer, I oversaw managing customers' Elastic Stack and entire infrastructure. I helped the client with capacity planning, optimization, architecture improvements, and upgrades through different major versions of the Stack without downtime required. I also helped the client with stability improvements, which resulted in improving their SLA. I migrated Splunk applications onto Elastic Stack, which reduced the Splunk licensing cost. The daily ingestion in the cluster was increased from between 400 to 500GB to 1.5TB. To reduce the operational tasks, I helped the client build automation to focus on their milestones more. Apart from managing the Elastic Stack, CI/CD development, Chef cookbook development for configuration management on hosts, development, and enhancements of CloudFormation templates to manage infrastructure were also part of my roles and responsibilities.

The client wanted to migrate their Elastic cluster, which was running on AWS, to the Elastic Cloud to reduce the operational costs. They also wanted to migrate their ingestion layer from one AWS account to another.

As a DevOps engineer, I helped the client migrate the Elastic cluster from AWS to Elastic Cloud without downtime. The cluster contained over 100TB of data, and it received 1.5TB of data per day. I also helped the client migrate the stack's ingestion layer from one AWS account to another. I helped with the planning, architecture design, Chef cookbook development, infrastructure as code (IaC), scripts to automate the migration, CI/CD for the new stack, and the migration.

The organization wanted to build software as a service product on AWS to automate the deployment and management of the databases for their customers.

As a DevOps engineer, I helped a client develop Terraform modules to manage the entire infrastructure for a SaaS product. I helped the client design scalable architecture with self-healing and high availability (HA) capabilities. Also, I developed CI/CD pipelines to build, test, and deploy applications in AWS ECS and integration test pipelines for end-to-end testing.

As a member of the Puppet module development team, I contributed to the successful management of thousands of servers for a prominent SaaS product. My primary responsibility was to assist clients in enhancing their existing Puppet modules to efficiently manage configurations, ensuring optimal performance and reliability. In addition, I leveraged my expertise to design and implement advanced functionalities that enabled the SRE team to apply configurations on hosts effortlessly.

As a DevSecOps engineer, I worked with clients to build automation around Azure policies to improvise the compliance and monitoring of Azure resources. I also developed CI/CD pipelines using Azure Pipelines to build, test, and deploy applications in Azure. They were created around Azure policy deployment, assignment, remediation, exemption, and data collection. Also, I enforced policies to achieve compliance and designed and managed infrastructure using ARM templates.

As a DevOps engineer, I collaborated with a development team to aid in the implementation and improvement of their continuous integration/continuous deployment (CI/CD) workflows for a Kubernetes application. Specifically, the client required a product that would enable the efficient backup and restoration of the application state and data. I contributed to creating, repairing, and advancing internal tools that allow teams to construct and configure infrastructure and Kubernetes environments on various platforms such as GKE, EKS, AKS, RKE, OCP, KOPS, Kind, and others. Moreover, I devoted efforts to optimizing the Helm chart and streamlining the deployment and management process for end-users.

The client had a requirement to host their application and API on a blockchain network and sought to implement monitoring solutions for the entire system. Additionally, they needed an infrastructure that could join the existing blockchain network. I designed a scalable architecture for the client in Azure and AWS to meet these needs.

The architecture I developed allowed the client's infrastructure to be easily deployed across multiple regions, with an active-active DR (disaster recovery) strategy in place for added resilience. To enable this scalability and resilience, I implemented complex infrastructure-as-code (IaC) modules using Terraform and Terragrunt. These modules automated the infrastructure deployment across all environments, streamlining the process and minimizing the risk of errors.

In addition, I also implemented continuous integration/continuous deployment (CI/CD) pipelines for the client's infrastructure, ensuring that any changes or updates were deployed seamlessly and with minimal disruption. Overall, my design and implementation of this infrastructure provided the client with a highly scalable, resilient, and automated solution to meet their blockchain hosting requirements.

The client operated a cybersecurity application that monitored network activity and detected threats across millions of devices. They needed an AWS DevOps engineer to enhance their infrastructure management, optimize costs, and improve deployment processes.

As an AWS DevOps engineer, I managed the AWS infrastructure using Terraform, implementing best practices for scalability and reliability. My optimization strategies and architectural improvements led to a 30-40% reduction in cloud costs, significantly enhancing the project's efficiency.

I streamlined CI/CD pipelines, achieving a 40% reduction in execution time through caching, restructuring, and parallel job implementations, which accelerated deployment cycles. Embracing a GitOps approach, I improved infrastructure management and collaboration among development teams.

To further ensure resilience, I designed and implemented an active-passive multi-region disaster recovery strategy, enhancing the system's reliability and minimizing downtime in case of failures. This comprehensive approach not only improved performance and cost-effectiveness but also bolstered the client's ability to respond to security threats effectively.