As we learn of more and more cloud services and modern cloud hosting platforms put forth by providers, enterprises are seeing the possibilities of a multitude of cloud environments. Artemis Consulting assists our clients with running secure and reliable cloud infrastructure and provides them with the ideal approach for fully managing their cloud services across providers (e.g., AWS, Azure, Google Cloud, IBM Cloud). We provide assistance with all three models of cloud service—IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service).
From assessing legacy applications for migration to the cloud by using a lift-and-shift approach in providing the best target cloud architecture to designing, implementing, managing, and monitoring the deployed cloud applications, we provide our clients with the full life cycle of cloud transformation services or the various parts that are best suited for their needs.
Cloud Migration & Development
We have the expertise to help organizations move to the cloud with confidence. We help with migrating legacy applications and designing cloud-native applications from the ground up using the principles of virtualization, microservices, serverless, API-based architecture, horizontal scalability, and auto-scaling based on load. Our focus on security ensures continuity of operations in the face of cyberattacks or catastrophic data center failures.
Cloud Architecture & Engineering
We have the knowledge to reengineer and build mission-critical applications and infrastructure to be cloud-native. Our architects have the track record to help evaluate cloud providers (e.g., AWS, Azure, Google Cloud, IBM Cloud) that are the best fit for our clients’ architecture needs and utilize cloud-native technologies, such as containers, microservices, and serverless implementations, to revamp our clients’ infrastructure for the cloud in a scalable, secure, and cost-effective manner. Our experts make our cloud applications more easily accessible and faster for use by clients.
Artemis Consulting recognizes that each organization has its own unique set of challenges, requiring customized solutions based on needs. Our cloud architects will assist clients with a customized approach to managing their cloud provider (e.g., AWS, Azure, Google Cloud, IBM Cloud), including managing large computing services for ML and AI workloads.
As part of an ongoing modernization effort, a large federal agency requested assistance to move from a legacy system to a more robust and cost-effective cloud system. Our team at Artemis Consulting conducted an application assessment plan for the agency to migrate from the old application to a new system built to scale in the cloud. Our strategy involved moving the old data center content to a new cloud-based system utilizing, in this case, an Amazon Web Services RDS for the database backend. This plan allowed the customer to move to the new system with zero downtime and a more secure and fault-tolerant system.
Artemis Consulting implemented a cloud-native solution using AWS as the cloud provider for the enterprise system. When designing a system, many requirements need to be factored into the system architecture. These include customer goals, infrastructure needs, application availability, and a whole host of other considerations. Our approach factors in server allocation costs, so that the application is not using valuable resources when it is not being utilized. This project, in particular, required multiple layers of infrastructure development and provisioning. Our solution utilized a set of cloud-based services and solutions to create a CI/CD pipeline that deploys containerized components. The containers are orchestrated in AWS’s ECS as Fargate tasks. This system is built and maintained using Terraform scripts that allow an Infrastructure-As-Code approach to provisioning and maintaining cloud resources.
To complete the data center migration, the AWS ECS clusters were built using common reusable Terraform templates, enabling baked-in security features and auto-scaling policies to ensure consistency across environments. These environments use the following AWS services:
- AWS ECS for Container Orchestration
- AWS Postgres RDS
- AWS OpenSearch
- AWS Simple Notification Service (SNS)
- Queuing Service
- CodeArtifacts and ECS for Artifacts and Container Registry
- AWS Lambda for Short-Lived Serverless Tasks
This migration, development, and management of a major enterprise-wide Cloud-based solution required a comprehensive plan and detailed execution. Beginning with a thorough assessment of applications to be hosted, we designed the target AWS environment with sufficient capacity. We then designed the migration plan using automated CI/CD deployments, taking time to build flexible scripts rather than hastily utilize a manual build process. We instituted repeatable processes for maintaining and updating the environment with a focus on security and sustainability. The ultimate benefit to the institution was a high-performance, low-risk, reliable solution that took advantage of the offerings of a cloud-based solution.
A long-time legislative client required assistance with migrating one of their enterprise applications to production. Having maintained servers and databases of their own, they were increasingly constrained by aging infrastructure. Requesting on-premises virtual servers took weeks and code releases were still being done manually. Their legacy infrastructure was difficult to scale, time-consuming, and costly to maintain. They were looking for organizational agility in their IT—the ability to improve deployment speed, flexibility, reliability, redundancy, and security.
Artemis Consulting began by helping automate their software delivery process using docker images. We closely collaborated with the client to devise the best possible solution to align with their timelines. Keeping with the Azure DevOps platform they were using, we automated the continuous integration and continuous delivery (CI/CD) process and ensured the right permissions were established to provide the pipeline access to the right resources. The docker images were built using Azure’s prebuilt tasks for docker. The final containerized application was then deployed to a Kubernetes cluster that is hosted on Azure Cloud.