Cloud Infrastructure Management Services

Cloud infrastructure management is the foundation on which successful cloud adoption journeys are built. Different types of applications – web apps, data analytics , AI/ML implementations, games – different types of domains – healthcare, fintech, edtech, retail – different types of workloads – VMs, containers, databases, data warehouses – all are dependent on underlying infrastructure. As part of cloud infrastructure management services, we ensure that the foundation of your cloud based workloads are built strong and resilient.

We can assist you at various stages – right from strategy formulation to implementation and then on to monitoring and management.

Cloud Strategy

We start with helping you build your cloud strategy. Should you opt for IaaS or PaaS? Should you choose cloud, multi-cloud, hybrid-cloud? Should you go in for modernization? After a detailed understanding of your application, architecture, business and technical requirements, we will come up with the right approach for your cloud strategy. Along with the strategy we also build a road map to achieve the strategy based on immediate and long term goals to be achieved.

Infrastructure Management Process

The methodology can be summarized as follows:

Assessment.

The first step in any cloud management/implementation strategy is assessment. Whether it is assessment of existing infrastructure, need for expansion for newer and different workloads or fresh implementation, we start with understanding the needs of the customer.

Architect /Refactor

 

The assessment phase leads into the architect/refactor phase, where we come up with appropriate design for the current and projected requirements. The foundation of any cloud workload is the infrastructure. Infrastructure design involves choosing:

  1. Compute – choose the correct options in terms of machine types, disk types, amount of resources such as CPUs and memory. This is applicable for compute only workloads as well as for containerized workloads. 
  2. Network – design firewalls, load balancers, subnets, WAF etc
  3.  Security – roles and permissions, users and groups , etc

We work closely with our customers and finalise on the infrastructure giving due consideration to :

  1. Present and projected  usage
  2. Current and Target Cost
  3. Current and Target Performance.
  4. Other objectives such as modernization needs and use of managed services.

In addition, requirements for HA and DR are considered. Based on business needs and SLAs, appropriate HA and DR strategies are developed. These could be active-active or active-passive. For HA and reliability, choice of using multi-region, multi-zonal resources are made based on business and technical requirements

Deployment Phase

   Once the assessment and initial design is done, we get into deployment phase which involves:

  • Implementation
  • Testing
  • Monitoring
  • Optimization
 

 Implementation

 
The inputs to this phase can come from either the assessment and architect phase  or the optimization phase.
 The Assessment and Architect activities are  undertaken when a new project, customer engagement is initiated. Optimization leading to implementation of changes recommended is part of a continuous process of management.

 Implementation of the desired changes is done following best practices using as much automation and scripting as possible. 

Testing

 
Implementation phase is followed by the testing phase, which includes infrastructure testing as well as relevant application testing. 

Monitoring


An active monitoring system is developed in parallel with the implementation phase.

An effective monitoring system can be built as follows:

  • Identity metrics to be measured and thresholds to be monitored for all relevant parts of the system.
  • Define application endpoints for application health check
  • Create dashboard for effective communication of overall system state
  • Build alerts and notification system for prompt and timely action in case of events
  • Define activities and actions to be taken in case of events.
  • Setting up log retention policies
  • Set up audit policies.

Optimization

Monitoring insights and analysis are then used for coming up with optimizations. The optimizations could be for cost or performance.Once these are finalized and agreed upon with all stakeholders, the insights are then circled back into the deployment phase.

The deployment phase is a repetitive construct used in various types of projects.

“MORE is a premier partner with Google Cloud Platform and has vast experience with managing infrastructure on Google Cloud. We are experts applying GCP best practices right from the design to implementation to management of workloads on Google Cloud. Our experience gives the ability to choose the right tools for infrastructure management from the various options available from Google Cloud Platform.”

Infrastructure Services in Google Cloud.

Google Cloud Platform provides various services for infrastructure and infrastructure management.

Services such as Google Cloud Compute Engine and Google Cloud SQL provide most commonly used infrastructure services such as VMs, disks and databases. Built on top of these underlying services, container orchestration services such as Google Kubernetes Engine are available.

Supporting these compute services, Google Cloud networking products such as Cloud DNS, Cloud Load Balancing, Cloud VPN and Cloud CDN. 

To monitor these services, Google Cloud provides Google Cloud Operations Suite that helps you gain visibility into the performance, availability, and health of your applications and infrastructure.

To ensure security, in addition to basic Identity and Access Management, Google Cloud provides several advanced options such as Cloud Armor and Google Cloud Security Command Center. The Security Command Center helps discover misconfigurations and vulnerabilities and detect threats.

Together these form a formidable set of tools for us for effective infrastructure management.

Customer Stories

Thetaray

Thetaray were using auto managed instance groups for scaling their applications. This was not very cost effective. We helped them containerize their application, use GKE with preemptible VMS and this helped them save costs. We also helped automate their deployment process where we ran jenkins in GKE and automated infrastructure creation and tear down as well.
Read more about this at
:   https://cloudwithmore.com/thetaray-case-study/

Investing

The customer infrastructure for Investing was spread across 3 local data centers, MORE helped move part of it to Google Cloud which helped in scalability. For regulatory reasons databases had to be run locally, however using Cloud Interconnect read replicas, latency issues were prevented. Read more about how we helped successfully create a hybrid cloud environment here : https://cloudwithmore.com/investing-case-study/

Enterprise Data Company

 Our client has designed a solution that makes it possible for every company to do advanced analysis without the overhead that comes with traditional data infrastructure.Their solution is an end-to-end enterprise data platform for analysts. We, as partners, helped modernize their data management solution. They wanted to migrate from AWS Redshift to BigQuery for better scale and we helped them with design for the solution. Read more about this at : https://cloudwithmore.com/enterprise-data-company/