Kuberiter Inc was founded as a SaaS #AIDevOps company in 2017, a B2B product. Since then I lead the product design, development, hiring resources, technology tool selection and bootstrapping it.
Being a technical founder has its pros and cons.
The advantages are industry experience, technology network, knowledge about software products, ability to hire resources that fit requirements (piece of cake), fire fight system issues when necessary, and there is no need to hire an expensive CTO as a co-founder. The pitfalls are spending too much time on technology, project management with rational approach and Sales. However, on the Sales front my previous experience with new product launches gives me an advantage to explain how Kuberiter as a solution aligns with the company requirements making the pitch relevant to C Executives.
As many articles suggests, DevOps (Dev- Development, Ops- Operations) is not only a technology change but a massive cultural change in software development and infrastructure provisioning to speed to market. Few years back, I saw reluctance from a Banking Customer to move to the Cloud. I explained how imperative the move to Cloud was, as Cloud is here to stay. While they did not agree with me then, that Customer eventually adopted Cloud, they migrated their low risk applications to Amazon Cloud recently. In the same way, DevOps tools like Jenkins, Docker, Kubernetes etc. will take over the software delivery market for many years to come. There are some challenges in provisioning, utilizing and maintaining the listed product tools to adopt DevOps. The complexity of the tools may create siloed teams again and may fail the concept of DevOps.
Kuberiter fills this gap. Our SaaS DevOps tool helps the customers to provision their DevOps hosting environment by a few clicks. Our Docker DevOps tool takes only 65 seconds to download a Docker Tomcat Container, add a .war file from Nexus/GitHub/Local Disk, Insert Dockerfile commands with an UI, Build and Push them to the chosen Docker Registry.
Kuberiter also commenced work on the Jenkins module. The objective is to build the application within the Docker Container so the application is aware of Infrastructure features from the beginning.
In my 10 years of experience as a build and deployment engineer working on hundreds of RCA’s (Root Cause Analysis) documents, I found that the most neglected layer in Application Release Management pipeline are Development and Build Servers. The lack of management in this area cause sever sprawling, repeat mistakes in build and troubleshoot issues because the Infrastructure Engineers refuses to step in to solve developer issues immediately. It is always a P4 ticket for them.
During a project with a US government agency as their Release Management Architect, my role was to integrate the various vendors that managed each module for major applications for the agency and to make sure the build release life cycle works as per the project plan. The build started failing intermittently when a specific vendor added their code to the build. It was hard to prove which vendors code caused the failure because each vendor had their own ticketing system and there was so much back and forth emails from vendors to justify the integrity of their code.
The Manager and I were determined to get to the root of the issue. After extensive weeks of work, we proved that the code from a specific vendor broke the complete build process. They fixed the issue and after few months, the build broke for the same reasons. It was frustrating to troubleshoot by scanning through 400 GB size of log files, 15 integrated servers, tickets, and multiple emails on the same. However, we proved that the specific vendor code was the culprit, then they fixed the code and we could all get back to work. The manager and I left the project after a year and I heard that the specific vendor still has challenges managing this environment with the new team.
The troubleshooting in a neglected infrastructure environment is a nightmare for every development manager and sponsor. Accountability is the major issue.
Kuberiter solves the above problem.
The objective is to provide an end to end DevOps product that’s built on Jenkins, Docker, Kubernetes with TensorFlow based predictive analytics. Our massive MongoDB clusters refine, sort and store the build and operational logs with specific, notable error messages. The TensorFlow predictive algorithm scans the build process against specific error pattern stored in the data lake and proactively warns the build engineers to not repeat certain mistakes. It also enables the release managers to view the similar error messages from the past and compare with new builds from our Intelligent Dashboard.
DevOps is an ongoing journey and you will never be satisfied. But you should take that first step to take your software delivery model to the #4IR revolution to be ready for the future.
I’m going to hire a Sales Manager this week to start marketing our product and services. The future is very bright.
#DevOps #AIDevOps #Jenkins #Docker #Kubernetes #TensorFlow #MongoDB #Linux