Our Expertise

HashedIn helps you run your containers and maintains a high level of security, reliability, and scalability. We provide both serverless and managed server commute for your containers. Our containerization experts help you modernize your technology setup and ecosystem, standardize the deployment of code, and make it easier to build workflows for applications that operate between on-premises and on various cloud environments. Our expertise in containerization helps build a structured platform which makes it easier to manage infrastructure and standardize on how applications are deployed and managed.

50+

Dockers and K8s Engineers

60+

DevOps Engineers

125+

AWS certified Engineers

Our exquisite containerization packaged services are

Containerization Packaged Services

  • Fully decoupled containerized microservices
  • Dockerfile/Docker-compose written with best practices
  • Automated Security, DR, and Backups with the help of preferred open source tools
  • Production-grade documentation/checklist to maintain the setup

Kubernetes Packaged Services

  • On-premise or managed Kubernetes setup and security testing of setup using the preferred open-source tool
  • No cloud vendor lock-in also available
  • Setup using existing Ansible scripts
  • No single point of failures with full HA setup
  • Documentation on operations at the time of hand-over

Well-Architectured Framework Packaged Services

  • Container and Kubernetes Packaged services inclusions
  • CI/CD setup using tools of your choice
  • DR, Backup and BCP risks mitigation
  • Applicable for both on-premise or managed Kubernetes setup
  • Handling compliances like FedRamp or GDPR or HIPAA

HashedIn’s containerization packaged services offer a variety of price models based on the requirements. Typically, it is a factor of a number of services, nodes, and governance(logging, monitoring, auditing, security, and other compliances) requirements. HashedIn’s containerization journey enables an organization to decouple their complex monolithic or microservice architecture into service-based containers and then deploy them into platform/servers of their requirements. As part of our packaged services, we give free 8 hour proof of concept Dockerization of your non-production services and provide operational support for 3 months after KPIs are met.

Our Solutions

Vm2docker

Vm2docker takes care of converting a standalone application, e.g. WordPress into a docker image and pushes to ECR. Vm2docker facilitates and help reduce containerization time to minutes, containerizes at scale, supports Amazon Linux and a majority of other Linux Distros, and provides out of the box support for AWS ECR, ECS, and EKS.

KubeIn

KubeIn helps build a Docker image, push the image to the Docker repository, and finally deploy it into a self-managed Kubernetes cluster, all without the intervention of the operations team. This process also facilitates and helps deploy MVP or a Proof of Concept or bootstrapping an application over EKS. KubeIn takes a git repo with Dockerfile as input and generates an application URL as an output.

Kube-it-out

Kube-it-out avoids manual interventions in AWS EKS deployments through automation. It does through a set of scripts that allow for the templatization of manifest files. The code needs to be uploaded with prerequisites and dockerfile, the solution we deploy the code in an EKS within a newly created VPC. Kube-it-out helps templatize EKS deployments fully, no requirements to acquire or learn new tools, controls costs and possesses AWS Native Security.

Insights

Container Services Engagement Guide

Snow

Step 1

Assessment and Workshop

  • Problem Statement Definition
  • Existing Setup Walkthrough
  • Requirement Definition and Documentation
  • SLA Requirements
  • Stakeholder identification
  • Number of services/nodes requirements
  • Geographic Support Requirement Overview
  • Domain Specific Support Requirement Overview
  • Budgetary Objective, Resource, and Constraint Overview
  • Kick Off Meeting

Snow

Step 2

Implementation

  • Problem Statement Definition
  • Week based project plan and milestones
  • Step by step containerisation of agreed services
  • Checklist preparation of services mandate
  • Weekly reviews and demos
  • Progress tracking towards project plan

Snow

Step 3

Support

  • Identification of handover stakeholders
  • Identification of definition of done
  • SLAs Support/Operations triages

Snow

Step 4

Handover

  • Acceptance on KPIs and definition of done
  • Sharing documentation

Case Studies

FAQs

Containers are lightweight, self-sufficient, unit of software which contains code and its dependencies. That unit can run the code in any environment, without needing any external dependencies to be installed.
There are several practical benefits of containers but the two main ones are- a. Better resource utilisation and thus hardware cost savings. b. Portability with consistency ensures that even if one takes that single unit and runs it on any development or production environment, it would behave the same.
Fundamentally both are the same concepts, and allow independent runtimes for your applications. But the difference lies in their implementation. Virtual Machines(VMs) are basically isolation of runtimes at hardware level. Containers do this isolation at application level. Each VM installs its own copy of the whole OS on a host machine, but containers isolate runtimes using cgroups (isolates CPU, RAM, etc.) and namespaces (allows access to network, storage, host, etc.).
Docker is the leading container runtime with ~80% market share. Others are Mesos, containerd, CoreOS rkt etc. Each OS distribution comes with their own implementation of containerization.
Docker command utility creates a separate cgroup and namespace inside the kernel whenever it runs. That means a particular process can have its own pseudo-filesystem, process hierarchy and logically separate access to system resources like RAM, CPU, system files, etc. Docker runtime adds all requirements into the new cgroup and namespace from Dockerfile. This way it behaves in an independent unit of software.
Kubernetes is an orchestrator for containers. It supports various container technologies like docker and containerd. These work for complex container based apps, where services stack like port management, IP exposure, load balancing, networking, healthchecks, etc. are provided by Kubernetes for supported container runtimes like Dockers.
For complex docker based applications, you need an orchestrator like Kubernetes to manage various deployments, auto-healing, container scaling, replication, load balancing amongst replicas, networking amongst multiple containerized services and health checks of all. All these are done by Kubernetes, as an orchestrator.
Horizontal Pod Auto-scaling(HPA) is a feature in K8s that increases the number of pods based on certain metrics (CPU, memory, custom metrics, etc.) every 30 seconds, or based on API triggers. Vertical Pod Scaling(VPA) is also supported in some implementations of K8s but cannot be used with HPA.
Apart from pods auto-scaling, Kubernetes also allows ClusterScaling service which adds another node to your cluster. This is not the same as cloud-based auto-scaling and both work at different layers of scaling. Cluster autoscaling gets triggered only when K8s scheduler is not able honour HPA or VPA requests, and those requests are in pending state. CA is not triggered by any metric but only when the scheduler has any HPA/VPA request in pending for more than 10 mins.
Yes. Various managed K8s servers provide simple methods of updating. Tools like Kubeadm also provide commands to update. An important point to note is not to upgrade more than one minor version, and go step by step.

Container Services Consulting

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