CASTOR K8S Platform

Ship product updates with push of a button

Managed application platform for quick, reliable, and secure software releases.

Castor Introduction

CASTOR is an end-to-end automated application platform, built on top of Kubernetes.

Offered as a fully managed service.

One-click software releases

Castor comes pre-integrated with 30+ services, with best practices, and sensible defaults.

Once set-up, simply push your updated code to the remote repository. Castor will automatically create secured containers and run them on Kubernetes clusters.

Quick Deployments

Git push to live deployment in 5 mins.

Fully automated process. No more latency in operation cycles.

Auto-scaling Infrastructure

Castor automatically scales CPU, memory, and storage as a response to changing demand.

Orchestrating a perfect balance between availability, performance, and resource utilisation.

Reliable releases

Make product releases with high levels of certainty and predictability.

No more pre-deployment jitters and post-deployment fire-fighting.

Robust Set-up

Robust Set-up

Leverage best-practices in configuration and environment set-up. Have a strong foundation.

High availability

High Availability

Serve your customers with zero downtime during product deployments and scaling.

Automated Workflows

Never miss planned deployments, scaling up/down opportunities, and testing cycles.

Mapping image vulnerability to running containers, allow only approved registries and images, automate base image upgrades, auto image-scanning.

Secure default configurations for service mesh, ingress, egress, namespaces etc

RBAC authorisation, continuous monitoring, secure access to Kubernetes API, and pod security standards adherence.

Highly Secured

Move from DevOps to DevSecOps thinking. 

Castor practices high standards for data and code integrity, access control vulnerability, privacy, and end-point security.

Cost-Optimised Operations

Get all the benefits of having a mature engineering team and an automated stack at a fraction of your current cost.

Optimised infrastructure costs

Avail best-in-class built-in optimisations. Pro-rata costs for servers, databases, file system storage. Smart defaults with Fargate Profiles, Spot instances etc. Custom configurations and consulting to lower cloud service costs

Reduced manpower costs

Zero manual errors. Lean engineering team. Productive development team.

CASTOR helped InveniAI scale up their machine learning application while reducing overall costs

Constantly evolving stack

Our team of engineers constantly upgrade and optimise every component to ensure highest levels of stability and security

24 APR 2022

Autoscaling database update

The latest Aurora serverless v2 database is now available to be used with Castor.

17 APR 2022

Kubernetes update

Castor is now compatible with Kubernetes v1.22. Clusters are available now for both the new k8s version along with support for those on the older version.

11 APR 2022

Load-balancer update

We have added a new component, Network load balancer with proxy protocol V2 is now available on Castor.

28 MAR 2022

Storage update

Castor’s storage options now include both AWS EFS and EBS storage classes.

12 MAR 2022

Ingress update

Our Ingress component now supports both TCP and UDP services.

Easy Kubernetes adoption for everyone

Our fully managed services help engineering teams at all stages adopt Kubernetes with full functionality and minimum disruption

Early-Stage​

Reliable product releases and infrastructure from Day 1. Outsource engineering and DevOps automation to Castor. Grow at your own pace.

In Transition

Stay ahead of market demand. We help you migrate your mature product to microservices, and automate your CI/CD pipeline with Castor.

Mature Teams

Improve specific metrics of infrastructure cost, reliability, or downtime. Castor consulting provides domain-specific solutions. End-to-end automation.

Ship new features. Delight your customers​

Get an infrastructure that supports your growth plans.

Where to, next?

Case Study

InveniAI and Castor

How Castor helped InveniAI scale up their machine learning application while reducing costs

Problem

Our client’s core focus is a machine learning application. It was resource-intensive work, which was turning out very expensive to operate on the cloud. Limiting infrastructure expenses would in turn impact the productivity of the model - each iteration would cost them weeks to a few months. All the while, the data scientist experts are waiting on the model output. They were facing a dilemma - improve speed but lose on infrastructure costs or save costs but lose time and improvements to the ML model.

Solution

Castor implemented a solution that helped them make progress on both cost and velocity, at the same time. Castor implementation was configured to take advantage of spot instances, creating a system that decreased infrastructure costs. The manual processes were fully automated in DevOps, making auto-scaling available 24*7. Castor took care of the Kubernetes expertise required to support ML applications on the cloud.

Impact

The costs decreased to 33% since Castor, while the model processing time reduced 50%. Data experts were freed up from infrastructure tasks, and they had a lesser wait time between model iterations.

Talk to us about ML and big data specific optimization