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2022 Blog, Blog, Featured, Feature Blog

With the growing demand for moving to the cloud, organizations also face various challenges, such as the ability to track costs, health, security, and assets at application levels. Having this ability can help organizations get a clear picture of their business metrics (revenue, transaction costs, customer-specific costs, etc.). Some of the other challenges that they face are as follows:

  • No clear definition of what is a service or application. The concept keeps changing from customer to customer based on the business’s criticality and need.
  • Separation of business applications from Internal applications or software services.
  • Deployment of applications across accounts and regions makes consolidation harder.
  • Dependent services and microservice concepts complicate the discovery process.
  • Complex setup involving clustered and containerized deployments promoting service-oriented architecture.
  • What is the target business/efficiency goal? Is it tracking cost, better diagnostics, or CMDB? What is linking to business Unit or Application level spend tracking?

Modeling a Common Customer Use Case

A typical large enterprise goes through a maturity journey from a scattered Infrastructure Asset Management to a more matured Application Asset Management.

Need for Automated Application Service Mapping
Applications are common focal points related to business units and business services that are highlighted by the customers.

  • It is important to track the cost and expenses at the application level for chargebacks. This requires an asset and cost-driven architecture. There is no common way to automate the discovery of such applications unless defined by Customers and linked to their infrastructure.
  • Business endpoint applications are served as a combination of assets and services
  • Knowing such dynamic topology can help with better monitoring, diagnostics, and capacity planning
  • There is a way to discover the infrastructure linked to templates and a service registry, but no easy way to roll that to an application linking

RLCatalyst AppInsights Solution
RLCatalyst AppInsights helps enterprises understand their current state of maturity by defining the global application master and linkage to business units. This is done using the discovery process to link applications, assets, and costs as a one-time activity. In this process, assets are categorized into two categories – allocated or mapped assets (i.e., assets linked to templates) and unallocated assets (i.e., assets that are not linked to any templates).

As shown in the above picture of the discovery process, all assets across your AWS accounts are brought into ServiceNow asset tables using Service Management Connector. Once done using RLCatalyst AppInsights, all assets are demarcated with assets linked to templates and the ones that do not have templates (unallocated assets). At this stage, we have cost allocations across assets linked to templates and unallocated assets. The next step is linking the templates to applications creating a mapping between applications and business units.

Similarly, for all the unallocated assets, we can look at either linking them to newly created templates or linking them to a project and terminating/cleaning up the same. Once you have all this in place, all the data would automatically build your dashboard in terms of cost by applications, Projects, BU, and unallocated costs.

For any new application deployment and infrastructure setup, it would follow the standard process to ensure assets are provisioned through templates, and appropriate taggings are enabled. This is enforced using guardrails for ongoing operations.

As shown above, the plan is to have an updated version of AppInsights V2.0 on ServiceNow store by the end of 2022, which will include the following additional features.

  • Automated Application Service Discovery (AASD)
  • Cross account Applications Cost tracking
  • Support for Non-CFT based applications like Terraform
  • Security and Compliance scores at an account level
  • Support for AppRegistry 2.0

AWS Standard Products and Offerings in This Segment
AWS provides some key products and building blocks that are leveraged in the AppInsights solution.

Managing your cloud with an Application-Centric Lens can provide effective data analysis, insights, and controls that better align with how large enterprises track their business and Key Performance Indicators (KPIs). Traditionally, the cloud has provided a very Infrastructure-centric and fragmented view that does not allow for actionable insights. This problem is now solved by Relevance Lab AppInsights 2.0.

To learn more about building cloud maturity through an Application-centric view or want to get started with RLCatalyst AppInsights, feel free to contact

Governance 360 – Are you using your AWS Cloud “The Right Way”
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Configuration Management in Cloud Environments


2022 Blog, Blog, Featured, Feature Blog

Research Gateway SaaS solution from Relevance Lab provides a next-generation cloud-based platform for collaborative scientific research on AWS with access to research tools, data sets, processing pipelines, and analytics workbenches in a frictionless manner. It takes less than 30 minutes to launch a “MyResearchCloud” working environment for Principal Investigators and Researchers with security, scalability, and cost governance. Using the Software as a Service (SaaS) model is a preferable option for consuming functionality but in the area of scientific research, it is equally critical to have tight control on data security, privacy, and regulatory compliances.

One of the growing needs from customers is to use the solution for their online training needs and specialized use cases on Bioinformatics courses. With the pandemic, there is tremendous new interest in students to pursue life sciences courses and specialize in Bioinformatics streams. At the same time, education institutions are struggling to move their internal Training Labs infrastructure from data centers to the cloud. As an AWS specialized partner for Higher Education, we are working with a number of universities to understand their needs better and provide solutions to address the same in an easy + cost-effective manner.

The Top-5 use cases shared by customers to set up their Virtual Cloud Labs for courses like Bioinformatics are the following:

  • Enterprise Needs: Ability to move from Data Center based physical labs to cloud-based Virtual Labs using their Corporate Cloud accounts easily without compromising on security, tight cost controls, and a self-service portal for Instructors and Students. Enterprise-grade controls on Budget, Students/Instructors Access, Data Security, and Approved Products Catalog.
  • Business Needs: The setup of a New Virtual Training Lab should support the key learning and research needs of the students.
    • Programs available to provide labs access to students based on calendar programs for the duration of the full semester.
    • Longer-term projects and programs accessible for labs based on research grants and associated budgets/time constraints.
  • IT Department Needs: From University Corporate IT to be able to allow specific departments (like Bioinformatics) to have their own Programs and Projects with self-service without compromising on Enterprise Security and Compliance Needs.
  • Curriculum Department Needs: From different Department Heads (like Bioinformatics) and Instructors be able to define learning curriculum and associated training programs with access to Classroom and Research Labs. Departments also need tight control on budgets and student access management.
  • Student Needs: The ability for students to access cloud-based Training Labs is a very easy and simple manner without requiring deep access to cloud knowledge. Also having pre-build solutions for basic needs covering Analytics Tools like RStudio/Jupyter, access to secure data repositories, open-source tools/containers access, and collaboration portal.

The following picture describes the basic organization and roles setup in a university.

To balance the needs of speed with compliance, we have designed a unique model to allow Universities to “Bring your own License” while leveraging the benefits of SaaS in a unique hybrid approach. Our solution provides a “Gateway Model” of Hub-n-Spoke design where we provide and operate the “Hub” while enabling universities and their departments to connect their own AWS Research accounts as a “Spoke” and get started within 30 min with full access to a complete Classroom Toolkit. A sample of out-of-the-box Bioinformatics Lab tools available as a standard catalog is shown below.

Professors can add more tools to the standard catalog by importing their own AMIs using AWS Service Catalog. It is also very simple to create new course material and support additional tools using the base building blocks provided out-of-the-box.

Currently, it is not easy for universities, their IT staff, professors, students, and research groups to leverage the cloud easily for their scientific research. There are constraints with on-premise data centers and these institutions have access to Cloud accounts. However converting a basic account to a secure network, secure access, ability to create & publish product/tools catalog, ingress & egress of data, sharing of analysis, enforce tight budget control are non-trivial tasks that divert attention away from education to infrastructure.

Based on our discussions with stakeholders it was clear that the users want something that is as easy to consume as other consumer-oriented activities like e-shopping, consumer banking, etc. This led to the simplified process of creating a “My -Bioinformatics-Cloud-Lab” with the following basic needs:

1. A university can decide to sign up with Research Gateway (SaaS) to enable their different departments for using this software to enable online training and research needs. Such a university-level adoption is recommended to be an enterprise version of the software (hosted by us or by the university themselves) and used for different departments (called Organization or Business Units).
2. Another simpler way is to use our hosted version of Research Gateway by a particular department to create a tenant in Research Gateway with no overheads to maintain a university-specific deployment.
3. A Head of Department (HOD) can sign-up to create a new Tenant on Research Gateway and configure their own AWS Billing account to create Projects. Each Project can then invite other professors to be part of the online Training Labs. Projects can be aligned with semester-based classroom lab needs or can be part of ongoing research projects. Each project has a budget assigned along with associated professors and students, who have access to the project. The figure below shows typical department projects inside the portal.

4. Once the professor selects the project they can see standard “available products” in the Project. This project is used as a basic setup for a Training Lab. The figure below shows the sample screen for the available set of tools Professors can access by default. They can also add new products to the Lab Catalog.

For every Project (Lab) by default shared infrastructure is made available in the form of Project Storage, where curriculum-related data and information can be stored and made available to all students. Also, necessary security aspects for SSL connection, VPC, IAM roles, etc. are setup by default to make sure the Cloud Training Lab has a well-architected design.

5. A professor can control basic parameters for the Lab in terms of adding/deleting users, managing budgets, and also be able to take actions like “Pausing” a Project (no new products can be created while existing ones can be used) or “Stopping” the project (where all existing running machines are force stopped and no new ones can be created, however, data on the storage is accessible by students). The figure below shows how to manage project-level users and budget controls.

6. A professor can track the consumption of the lab resources by all users including professors and students as shown in the figure below.

7. Once a student logs into the project and accesses the lab resources, they can create their own workspaces like Rstudio and interact with the same from within the Portal. Once they are done with their work, they can stop the machine and log out to ensure no costs are being spent while the systems are not being used. When a researcher or student logs in, they can interact with active products and project storage as shown in the figure below.

8. The students can interact with their tools like RStudio from within the portal and connect to the same in a secure manner with a single click as shown in the figure below.

9. On Clicking the “Open Link” action, it allows access to an RStudio familiar environment for students to log in and learn as per their curriculum needs. The figure below shows the standard RStudio environment.

The new solution from Relevance Lab makes Scientific Research and Training in Cloud very easy for use cases like Bioinformatics. It provides flexibility, cost management, and secure collaborations to truly unlock the potential of the Cloud. For Higher Education Universities, this provides a fully functional Training Lab accessible by professors and students in less than 30 minutes.

If this seems exciting and you would like to know more or try this out do write to us at

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2022 Blog, Blog, Featured, Feature Blog

Relevance Lab (RL) is a specialist company in helping customers adopt cloud “The Right Way” by focusing on an “Automation-First” and DevOps strategy. It covers the full lifecycle of migration, governance, security, monitoring, ITSM integration, app modernization, and DevOps maturity. Leveraging a combination of services and products for cloud adoption, we help customers on a “Plan-Build-Run” transformation that drives greater velocity of product innovation, global deployment scale, and cost optimization for new generation technology (SaaS) and enterprise companies.

In this blog, we will cover some common themes that we have been using to help our customers for cloud adoption as part of their maturity journey.

  • SaaS with multi-tenant architecture
  • Multi-Account Cloud Management for AWS
  • Microservices architecture with Docker and Kubernetes (AWS EKS)
  • Jenkins for CI/CD pipelines and focus on cloud agnostic tools
  • AWS Control Tower for Cloud Management & Governance solution (policy, security & governance)
  • DevOps maturity models
  • Cost optimization, agility, and automation needs
  • Standardization for M&A (Merger & Acquisitions) integrations and scale with multiple cloud provider management
  • Spectrum of AWS governance for optimum utilization, robust security, and reduction of budget
  • Automation/BOT landscape, how different strategies are appropriate at different levels, and the industry best practice adoption for the same
  • Reference enterprise strategy for structuring DevOps for engineering environment which has cloud native development and the products which are SaaS-based.

Relevance Lab Cloud and DevOps Credentials at a Glance

  • RL has been a cloud, DevOps, and automation specialist since inception in 2011 (10+ years)
  • Implemented 50+ successful customer cloud projects covering Plan-Build-Run lifecycle
  • Globally has 250+ cloud specialists with 100+ certifications
  • Cloud competencies cover infra, apps, data, and consulting
  • Provide deep consulting and technology in cloud and DevOps
  • RL products available on AWS and ServiceNow marketplace recognized globally as a specialist in “Infrastructure Automation”
  • Deep Architecture know-how on DevOps with microservices, containers, Well-Architected principals
  • Large enterprise customers with 10+M$ multi-year engagements successfully managed
  • Actively managing 7000+ cloud instances, 300+ Applications, annual 5.0+M$ cloud consumption, 20K+ annual tickets, 100+ automation BOTs, etc.

Need for a Comprehensive Approach to Cloud Adoption
Most enterprises today have their applications in the cloud or are aggressively migrating new ones for achieving the digital transformation of their business. However, the approach requires customers to think about the “Day-After” Cloud in order to avoid surprises on costs, security, and additional operations complexities. Having the right Cloud Management not only helps eliminate unwanted costs and compliance, but it also helps in optimal use of resources, ensuring “The Right Way” to use the cloud. Our “Automation- First Approach” helps minimize the manual intervention thereby, reducing manual prone errors and costs.

RL’s matured DevOps framework helps in ensuring the application development is done with accuracy, agility, and scale. Finally, to ensure this whole framework of Cloud Management, Automation and DevOps are continued in a seamless manner, you would need the right AIOps-driven Service Delivery Model. Hence, for any matured organizations, the below 4 themes become the foundation for using Cloud Management, Automation, DevOps, and AIOps.

Cloud Management
RL offers a unique methodology covering Plan-Build-Run lifecycle for Cloud Management, as explained in the diagram below.

Following are the basic steps for Cloud Management:

Step-1: Leverage
Built on best practices offered from native cloud providers and popular solution frameworks, RL methodology leverages the following for Cloud Management:

  • AWS Well-Architected Framework
  • AWS Management & Governance Lens
  • AWS Control Tower for large scale multi-account management
  • AWS Service Catalog for template-driven organization standard product deployments
  • Terraform for Infra as Code automation
  • AWS CloudFormation Templates
  • AWS Security Hub

Step-2: Augment
The basic Cloud Management best practices are augmented with unique products & frameworks built by RL based on our 50+ successful customer implementations covering the following:

  • Quickstart automation templates
  • AppInsights and ServiceOne – built on ITSM
  • RLCatalyst cloud portals – built on Service Catalog
  • Governance360 – built on Control Tower
  • RLCatalyst BOTS Automation Server

Step-3: Instill
Instill ongoing maturity and optimization using the following themes:

  • Four level compliance maturity model
  • Key Organization metrics across assets, cost, health, governance, and compliance
  • Industry-proven methodologies like HIPAA, SOC2, GDPR, NIST, etc.

For Cloud Management and Governance, RL has Solutions like Governance360, AWS Management and Governance lens, Cloud Migration using CloudEndure. Similarly, we have methodologies like “The Right Way” to use the cloud, and finally Product & Platform offerings like RLCatalyst AppInsights.

RL promotes an “Automation-First” approach for cloud adoption, covering all stages of the Plan-Build-Run lifecycle. We offer a mature automation framework called RLCatalyst BOTs and self-service cloud portals that allow full lifecycle automation.

In terms of deciding how to get started with automation, we help with an initial assessment model on “What Can Be Automated” (WCBA) that analyses the existing setup of cloud assets, applications portfolio, IT service management tickets (previous 12 months), and Governance/Security/Compliance models.

For the Automation theme, RL has Solutions like Automation Factory, University in a Box, Scientific Research on Cloud, 100+ BOTs library, custom solutions on Service WorkBench for AWS. Similarly, we have methodologies like Automation-First Approach, and finally Product & Platform offerings like RL BOTs automation Engine, Research Gateway, ServiceNow BOTs Connector, UiPath BOTs connector for RPA.

The following blogs explain in more detail our offerings on automation.

DevOps and Microservices
DevOps and microservices with containers are a key part of all modern architecture for scalability, re-use, and cost-effectiveness. RL, as a DevOps specialist, has been working on re-architecting applications and cloud migration across different segments covering education, pharma & life sciences, insurance, and ISVs. The adoption of containers is a key building block for driving faster product deliveries leveraging Continuous Integration and Continuous Delivery (CI/CD) models. Some of the key considerations followed by our teams cover the following for CI/CD with Containers and Kubernetes:

  • Role-based deployments
  • Explicit declarations
  • Environment dependent attributes for better configuration management
  • Order of execution and well-defined structure
  • Application blueprints
  • Repeatable and re-usable resources and components
  • Self contained artifacts for easy portability

The following diagram shows a standard blueprint we follow for DevOps:

For the DevOps & Microservices theme, RL has Solutions like CI/CD Cockpit solution, Cloud orchestration Portal, ServiceNow/AWS/Azure DevOps, AWS/Azure EKS. Similarly, we have methodologies like WOW DevOps, DevOps-driven Engineering, DevOps-driven Operations, and finally Product & Platform offerings like RL BOTs Connector.

AIOps and Service Delivery
RL brings in unique strengths across AIOps with IT Service Delivery Management on platforms like ServiceNow, Jira ServiceDesk and FreshService. By leveraging a platform-based approach that combines intelligent monitoring, service delivery management, and automation, we offer a mature architecture for achieving AIOps in a prescriptive manner with a combination of technology, tools, and methodologies. Customers have been able to deploy our AIOps solutions in 3 months and benefit from achieving 70% automation of inbound requests, reduction of noise on proactive monitoring by 80%, 3x faster fulfillment of Tickets & SLAs with a shift to a proactive DevOps-led organization structure.

For the AIOps & Service Delivery theme, RL has Solutions like AIOps Blueprint, ServiceNow++, End to End Automated Patch Management, Asset Management NOC & ServiceDesk. Similarly, we have methodologies like ServiceOne and finally Product & Platform offerings like ServiceOne with ServiceNow, ServiceOne with FreshService, RLCommand Center.

RL offers a combination of Solutions, Methodologies, and Product & Platform offerings covering the 360 spectrum of an enterprise Cloud & DevOps adoption across 4 different tracks covering Cloud Management, Automation, DevOps, and AIOps. The benefits of a technology-driven approach that leverages an “Automation-First” model has helped our customer reduce their IT spends by 30% over a period of 3 years with 3x faster product deliveries and real-time security & compliance.

To know more about our Cloud Centre of Excellence and how we can help you adopt Cloud “The Right Way” with best practices leveraging Cloud Management, Automation, DevOps, and AIOps, feel free to write to

Reference Links
Considerations for AWS AMI Factory Design