Senior DevOps - AWS / Kubernetes / Jupyterhub / EFS / EBS Task - Hiring Immediately
Budget: $5,000 – $10,000 USD
We are looking for a Senior DevOps Engineer / Cloud Engineer to work on our existing infrastructure to build and optimize the following services for our software project:
1) Optimize our Jupyterhub installation inside EKS - we are experiencing connectivity issues, delays in processing, etc. So, we're looking for someone to dig into this configuration and optimize it.
2) EFS setup - we have a membership website and we give each member an S3 bucket with their membership, but the upload/download/zipping/unzipping of files is slow in S3. So, we would like to explore using EFS.
3) Remote Spawn / Destroy of EC2 instances - Improve speed of this functionality
4) Terraform - Write terraform structure so we can spawn/destroy and manage our infrastructure with Terraform - currently we are using CLI.
5) Use terraform to setup/configure Spawn/Destroy of instances on other service providers (Google Cloud, Azure, lambda labs, and one other data center)
You'll be working with full stack software engineers, and two part-time devops team members to assist with any questions you might have.
Time to complete: 4 weeks
1) Optimize our Jupyterhub installation inside EKS - we are experiencing connectivity issues, delays in processing, etc. So, we're looking for someone to dig into this configuration and optimize it.
2) EFS setup - we have a membership website and we give each member an S3 bucket with their membership, but the upload/download/zipping/unzipping of files is slow in S3. So, we would like to explore using EFS.
3) Remote Spawn / Destroy of EC2 instances - Improve speed of this functionality
4) Terraform - Write terraform structure so we can spawn/destroy and manage our infrastructure with Terraform - currently we are using CLI.
5) Use terraform to setup/configure Spawn/Destroy of instances on other service providers (Google Cloud, Azure, lambda labs, and one other data center)
You'll be working with full stack software engineers, and two part-time devops team members to assist with any questions you might have.
Time to complete: 4 weeks
Related categories:
Cloud Computing
Software Architecture
Machine Learning (ML)
Amazon Web Services
DevOps