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2023 Blog, Blog, BOTs Blog, Feature Blog, Featured, RLCatalyst Blog

Automation Service Bus (ASB) – A New Approach for Intelligent and Touchless Automation

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May, 2023

- 2023 Blog, Blog, BOTs Blog, Feature Blog, Featured, RLCatalyst Blog

With growing interest & investments in new concepts like Automation and Artificial Intelligence, the common dilemma for enterprises is how to scale these for significant impacts to their relevant context. It is easy to do a small proof of concept but much harder to make broader impacts across the landscape of Hybrid Infrastructure, Applications and Service Delivery models. Even more complex is Organizational Change Management for underlying processes, culture and “Way of Working”. There is no “Silver bullet” or “cookie-cutter” approach that can give radical changes, but it requires an investment in a roadmap of changes across People, Process and Technology. RLCatalyst solution from Relevance Lab provides an Open Architecture approach to interconnect various systems, applications, and processes like the “Enterprise Service Bus” model.

What is Intelligent Automation?
The key building blocks of automation depend on the concept of BOTs. So, what are BOTs?


  • BOTs are automation codes managed by ASB orchestration
    • Infrastructure creation, updation, deletion
    • Application deployment lifecycle
    • Operational services, tasks, and workflows – Check, Act, Sensors
    • Interacting with Cloud and On-prem systems with integration adapters in a secure and auditable manner
    • Targeting any repetitive Operations tasks managed by humans that are frequent, complex (time-consuming), security/compliance related

  • What are types of BOTs?
    • Templates – CloudFormation, Terraform, Azure Resource Models, Service Catalog
    • Lambda functions, Scripts (PowerShell/python/shell scripts)
    • Chef/Puppet/Ansible configuration tools – Playbooks, Cookbooks, etc.
    • API Functions (local and remote invocation capability)
    • Workflows and state management
    • UIBOTs (with UiPath, etc.) and un-assisted non-UI BOTs
    • Custom orchestration layer with integration to Self-Service Portals and API Invocation
    • Governance BOTs with guardrails – preventive and corrective

  • What do BOTs have?
    • Infra as a code stored in source code configuration (GitHub, etc.)
    • Separation of Logic and Data
    • Managed Lifecycle (BOTs Manager and BOTs Executors) for lifecycle support and error handling
    • Intelligent Orchestration – Task, workflow, decisioning, AI/ML


To deploy BOTs across the enterprise and benefit from more sophisticated automation leveraging AI (Artificial Intelligence), RLCatalyst provides a prescriptive path to maturity as explained in the figure below.


ASB Approach
An Open- Architecture approach to interconnect various systems, applications, and processes similar to the “Enterprise Service Bus” model. This innovative approach of “software-defined” models, extendable meta-data for configurations, and a hybrid architecture takes into consideration modern distributed security needs. This ASB model helps to drive “Touchless Automation” with pre-built components and rapid adoption by existing enterprises.

To support a flexible deployment model that integrates with current SAAS (Software as a Service) based ITSM Platforms allows Automation to be managed securely inside Cloud or On-Premise data centers. The architecture supports a hybrid approach with multi-tenant components along with secure per instance-based BOT servers managing local security credentials. This comprehensive approach helps to scale Automation from silos to enterprise-wide benefits of human effort savings, faster velocity, better compliance and learning models for BOT efficiency improvements.


RLCatalyst provides solutions for enterprises to create their version of an Open Architecture based AIOps Platform that can integrate with their existing landscape and provide a roadmap for maturity.


  • RLCatalyst Command Centre “Integrates” with different monitoring solutions to create an Observe capability
  • RLCatalyst ServiceOne “Integrates” with ITSM solutions (ServiceNow and Freshdesk) for the Engage functionality
  • RLCatalyst BOTs Engine “Provides” a mature solution to “Design, Run, Orchestrate & Insights” for Act functionality

Relevance Lab is working closely with leading enterprises from different verticals of Digital Learning, Health Sciences & Financial Asset Management in creating a common “Open Platform” that helps bring Automation-First approach and a maturity model to incrementally make Automation more “Intelligent”.

For more information feel free to contact marketing@relevancelab.com

References
Get Started with Building Your Automation Factory for Cloud
Intelligent Automation For User And Workspace Onboarding
Intelligent Automation with AS/400 based Legacy Systems support using UiPath
RLCatalyst BOTs Service Management connector for ServiceNow


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2023 Blog, AWS Service, Blog, Feature Blog, Featured

Health Informatics and Genomics on AWS with  Research Gateway

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May, 2023

- 2023 Blog, AWS Service, Blog, Feature Blog, Featured

Major advances are happening with the leverage of Cloud Technologies and large Open Data sets in the areas of Healthcare informatics that include sub-disciplines like Bioinformatics and Clinical Informatics. This is being rapidly adopted by Life Sciences and Healthcare institutions in commercial and public sector space. This domain has deep investments in scientific research and data analytics focussing on information, computation needs, and data acquisition techniques to optimize the acquisition, storage, retrieval, obfuscation, and secure use of information in health and biomedicine for evidence-based medicine and disease management.

In recent years, genomics and genetic data have emerged as an innovative areas of research that could potentially transform healthcare. The emerging trends are for personalized medicine, or precision medicine leveraging genomics. Early diagnosis of a disease can significantly increase the chances of successful treatment, and genomics can detect a disease long before symptoms present themselves. Many diseases, including cancers, are caused by alterations in our genes. Genomics can identify these alterations and search for them using an ever-growing number of genetic tests.

With AWS, genomics customers can dedicate more time and resources to science, speeding time to insights, achieving breakthrough research faster, and bringing life-saving products to market. AWS enables customers to innovate by making genomics data more accessible and useful. AWS delivers the breadth and depth of services to reduce the time between sequencing and interpretation, with secure and frictionless collaboration capabilities across multi-modal datasets. Also, you can choose the right tool for the job to get the best cost and performance at a global scale— accelerating the modern study of genomics.

Relevance Lab Research@Scale Architecture Blueprint
Working closely with AWS Healthcare and Clinical Informatics teams, Relevance Lab is bringing a scalable, secure, and compliant solution for enterprises to pursue Research@Scale on Cloud for intramural and extramural needs. The diagram below shows the architecture blueprint for Research@Scale. The solution offered on the AWS platform covers technology, solutions, and integrated services to help large enterprises manage research across global locations.


Leveraging AWS Biotech Blueprint with our Research Gateway
Use case with AWS Biotech Blueprint that provides a Core template for deploying a preclinical, cloud-based research infrastructure and optional informatics software on AWS.

This Quick Start sets up the following:

  • A highly available architecture that spans two availability zones
  • A preclinical virtual private cloud (VPC) configured with public and private subnets according to AWS best practices to provide you with your own virtual network on AWS. This is where informatics and research applications will run
  • A management VPC configured with public and private subnets to support the future addition of IT-centric workloads such as active directory, security appliances, and virtual desktop interfaces
  • Redundant, managed NAT gateways to allow outbound internet access for resources in the private subnets
  • Certificate-based virtual private network (VPN) services through the use of AWS Client VPN endpoints
  • Private, split-horizon Domain Name System (DNS) with Amazon Route 53
  • Best-practice AWS Identity and Access Management (IAM) groups and policies based on the separation of duties, designed to follow the U.S. National Institute of Standards and Technology (NIST) guidelines
  • A set of automated checks and alerts to notify you when AWS Config detects insecure configurations
  • Account-level logging, audit, and storage mechanisms are designed to follow NIST guidelines
  • A secure way to remotely join the preclinical VPC network is by using the AWS Client VPN endpoint
  • A prepopulated set of AWS Systems Manager Parameter Store key/value pairs for common resource IDs
  • (Optional) An AWS Service Catalog portfolio of common informatics software that can be easily deployed into your preclinical VPC

Using the Quickstart templates, the products were added to AWS Service Catalog and imported into RLCatalyst Research Gateway.



Using the standard products, the Nextflow Workflow Orchestration engine was launched for Genomics pipeline analysis. Nextflow helps to create and orchestrate analysis workflows and AWS Batch to run the workflow processes.

Nextflow is an open-source workflow framework and domain-specific language (DSL) for Linux, developed by the Comparative Bioinformatics group at the Barcelona Centre for Genomic Regulation (CRG). The tool enables you to create complex, data-intensive workflow pipeline scripts, and simplifies the implementation and deployment of genomics analysis workflows in the cloud.

This Quick Start sets up the following environment in a preclinical VPC:

  • In the public subnet, an optional Jupyter notebook in Amazon SageMaker is integrated with an AWS Batch environment.
  • In the private application subnets, an AWS Batch compute environment for managing Nextflow job definitions and queues and for running Nextflow jobs. AWS Batch containers have Nextflow installed and configured in an Auto Scaling group.
  • Because there are no databases required for Nextflow, this Quick Start does not deploy anything into the private database (DB) subnets created by the Biotech Blueprint core Quick Start.
  • An Amazon Simple Storage Service (Amazon S3) bucket to store your Nextflow workflow scripts, input and output files, and working directory.

RStudio for Scientific Research
RStudio is a popular IDE, licensed either commercially or under AGPLv3, for working with R. RStudio is available in a desktop version or a server version that allows you to access R via a web browser.

After you’ve analyzed the results, you may want to visualize them. Shiny is a great R package, licensed either commercially or under AGPLv3, that you can use to create interactive dashboards. Shiny provides a web application framework for R. It turns your analyses into interactive web applications; no HTML, CSS, or JavaScript knowledge is required. Shiny Server can deliver your R visualization to your customers via a web browser and execute R functions, including database queries, in the background.

RStudio is provided as a standard catalog item in Research Gateway for 1-Click deployment and use. AWS provides a number of tools like AWS Athena, AWG Glue, and others to connect to datasets for research analysis.

Benefits of using AWS for Clinical Informatics

  • Data transfer and storage
    • The volume of genomics data poses challenges for transferring it from sequencers in a quick and controlled fashion, then finding storage resources that can accommodate the scale and performance at a price that is not cost-prohibitive. AWS enables researchers to manage large-scale data that has outpaced the capacity of on-premises infrastructure. By transferring data to the AWS Cloud, organizations can take advantage of high-throughput data ingestion, cost-effective storage options, secure access, and efficient searching to propel genomics research forward.

  • Workflow automation for secondary analysis
    • Genomics organizations can struggle with tracking the origins of data when performing secondary analyses and running reproducible and scalable workflows while minimizing IT overhead. AWS offers services for scalable, cost-effective data analysis and simplified orchestration for running and automating parallelizable workflows. Options for automating workflows enable reproducible research or clinical applications, while AWS native, partner (NVIDIA and DRAGEN), and open source solutions (Cromwell and Nextflow) provide flexible options for workflow orchestrators to help scale data analysis.

  • Data aggregation and governance
    • Successful genomics research and interpretation often depend on multiple, diverse, multi-modal datasets from large populations. AWS enables organizations to harmonize multi-omic datasets and govern robust data access controls and permissions across a global infrastructure to maintain data integrity as research involves more collaborators and stakeholders. AWS simplifies the ability to store, query, and analyze genomics data, and link with clinical information.

  • Interpretation and deep learning for tertiary analysis
    • Analysis requires integrated multi-modal datasets and knowledge bases, intensive computational power, big data analytics, and machine learning at scale, which, historically can take weeks or months, delaying time to insights. AWS accelerates the analysis of big genomics data by leveraging machine learning and high-performance computing. With AWS, researchers have access to greater computing efficiencies at scale, reproducible data processing, data integration capabilities to pull in multi-modal datasets, and public data for clinical annotation—all within a compliance-ready environment.

  • Clinical applications
    • There are several hindrances that impede the scale and adoption of genomics for clinical applications including speed of analysis, managing protected health information (PHI), and providing reproducible and interpretable results. By leveraging the capabilities of the AWS Cloud, organizations can establish a differentiated capability in genomics to advance their applications in precision medicine and patient practice. AWS services enable the use of genomics in the clinic by providing the data capture, compute, and storage capabilities needed to empower the modernized clinical lab to decrease the time to results, all while adhering to the most stringent patient privacy regulations.

  • Open datasets
    • As more life science researchers move to the cloud and develop cloud-native workflows, they bring reference datasets with them, often in their own personal buckets, leading to duplication, silos, and poor version documentation of commonly used datasets. The AWS Open Data Program (ODP) helps democratize data access by making it readily available in Amazon S3, providing the research community with a single documented source of truth. This increases study reproducibility, stimulates community collaboration, and reduces data duplication. The ODP also covers the cost of Amazon S3 storage, egress, and cross-region transfer for accepted datasets.

  • Cost optimization
    • Researchers utilize massive genomics datasets, which require large-scale storage options and powerful computational processing and can be cost-prohibitive. AWS presents cost-saving opportunities for genomics researchers across the data lifecycle—from storage to interpretation. AWS infrastructure and data services enable organizations to save time, money, and devote more resources to science.

Summary
Relevance Lab is a specialist AWS partner working closely in Health Informatics and Genomics solutions leveraging AWS existing solutions and complementing them with its Self-Service Cloud Portal solutions, automation, and governance best practices.

To know more about how we can help standardize, scale, and speed up Scientific Research in Cloud, feel free to contact us at marketing@relevancelab.com.

References
AWS Whitepaper on Genomics Data Transfer, Analytics and Machine Learning
Genomics Workflows on AWS
HPC on AWS Video – Running Genomics Workflows with Nextflow
Workflow Orchestration with Nextflow on AWS Cloud
Biotech Blueprint on AWS Cloud
Running R on AWS
Advanced Bioinformatics Workshop



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2023 Blog, Blog, Digital Blog, Feature Blog, Featured

Relevance Lab Playbooks for Frictionless IT and Business Operations

By on

March, 2023

- 2023 Blog, Blog, Digital Blog, Feature Blog, Featured

Relevance Lab’s (RL) focus on addressing the digital transformation jigsaw puzzle has a strategic investment in leveraging Products & Platforms to create a unique differentiation and competitive advantage. We are a specialist Cloud, DevOps, Automation, and Analytics Services company with an IP (Intellectual Property) led technology strategy. This helps our customers achieve frictionless business outcomes by leveraging cloud across their infrastructure, applications, and data.

We optimize IT spending with smart cloud workload migration, reducing ongoing operations costs by leveraging automation & governance, speeding up innovation in the delivery of new software products with Agile & DevOps, and getting key real-time business insights with Actionable Analytics.

The key platforms and playbooks that we have are the following:


RLCatalyst provides an “Automation-First” approach for Enterprise Cloud Orchestration across “Plan, Build & Run” lifecycle, leveraging our unique IP. A pre-built library of quick-starts, BOTs and open-source solutions helps customers use Cloud “The Right Way” focused on best practices like “Infrastructure as Code” and “Compliance as Code”. We also have unique specialization on AWS and ServiceNow platforms leveraged to provide Intelligent Cloud Operations & managed services with our ServiceOne platform covering workload migration, security, governance, CMDB, ITSM, and DevOps.

SPECTRA provides a Digital and Agile Analytics platform that helps build enterprise data lakes and Supply Chain analytics with multiple ERP systems connectors (SAP, Oracle, Dynamics, JDE, etc.). It also provides a smart-document search engine for Google-like features on enterprise digital documents (images, PDF, engg drawings, etc.). We leverage the Digital platforms for Frictionless Application modernization and Cloud Product Engineering services extending across platforms covering content, commerce, CRM, and supply chain (Adobe, Shopify, SFDC, Oracle Fusion, Azure PowerApps, Services & ADF) integrated with actionable insights from SPECTRA.


The figure above explains our company’s focus in driving frictionless IT and business operations leveraging these key platforms. The focus on a “coded business model” that the platforms deliver help us engage across the full lifecycle with customers covering the following stages:

  • Assess the key customer needs as each customer has a unique model we evaluate based on 3C’s (Culture, Content, & Constraints)
  • Standardize the internal systems, processes, engineering practices, and governance
  • Automate everything repetitive impacting speed, costs, quality, and compliance
  • Accelerate the achievement of business objectives with faster software delivery, better operational excellence, and real-time Agile Analytics

RLCatalyst Platform and ServiceOne Solution
RLCatalyst is an intelligent automation platform built with DevOps, Cloud, and Automation features covering infrastructure, applications, data, and workflows. RLCatalyst common services foundation is built using an open architecture in line with the industry standards and can be customized. On top of the foundation services, a set of specialized products, solutions, and services are created to cover the specialized needs of customers. Following are a few key foundation themes for RLCatalyst:

  • Built on Open-source products to provide flexibility and scalability for hybrid cloud deployments
  • Uses “Infrastructure as Code” best practices and DevOps standards covering CI/CD, end-to-end monitoring, and orchestration
  • The platform is built to have a UI Portal front-end, Node.JS API-based backend, integration layer for executing BOTs, and database layer based on NoSQL
  • The core concept uses a “self-aware” paradigm to embed dynamic configurations, end-to-end monitoring, and dynamic CMDB to enable smart operations using other ITSM and Cloud platforms
  • The Cloud Portal drives self-service models of DevOps and can be customized to add domain-specific business rules for customers or industry type
  • There is “Compliance as Code” embedded into the design to make sure customers can be aligned with well-architected principles
  • The platform is built on top of AWS and ServiceNow ecosystem but can also be deployed on-prem or other cloud platforms
  • The solutions are pre-integrated with other popular DevOps and Cloud tools like Docker, Chef, Anisible, Terraform, Jenkins, ELK, Sensu, Consul, etc
  • The platform comes with a pre-built library of BOTs and Quickstart templates

The combination of RLCatalyst and ServiceOne integrated solution provides an intelligent automation architecture, as explained in the figure below. The key building blocks are:

  • Discover the underlying assets, health, costs, vulnerability, security, and compliance.
  • Automate using a framework of BOTs built with self-aware intelligence covering tasks, workflows, decisioning, and AI/ML algorithms.
  • Resolve at speed all service management tickets and requests with complex workflows & integration across multiple systems

SPECTRA Platform and Business Process Automation
SPECTRA, the AI-driven Analytics platform from Relevance Lab, based on open-source technology, can fast track your journey from data to actionable insights. It can process data from structured data from different ERP Systems based on pre-existing adapters and unstructured data from PDFs, Emails, engineering drawings, and commercial labels. Every organization has invested in a combination of tools, technologies and solutions to create their Data platforms. However, most of these platforms are built with legacy technologies or fragmented components. When companies try to leverage the new technologies of Big Data, Cloud Architectures and Artificial Intelligence to achieve more meaningful Analytics a pre-built Platform like SPECTRA can save tremendous efforts, costs and time to provide a scalable and flexible alternative.

Similar to the RLCatalyst IT Optimization we leverage SPECTRA Platform for Business Optimization with Agile Analytics, as explained in figure below.


We have also leveraged SPECTRA Platform and UiPath Integration to Achieve business process hyper automation, as explained briefly below.


Customer Impact with RL Playbooks for IT and Business Transformation
Relevance Lab leverages our strengths in platforms for all our customer engagements to bring out special value on services delivery in areas of:

  • Cloud Infrastructure Automation
  • Data Analytics Platforms
  • Digital Applications and Product Engineering
  • Intelligent Operations and DevOps

The figure below highlights the value created for some of our key customers.


We have adopted the following maturity model as a specialist technology company with significant investments on competency and IP creation that guides the investments in RLCatalyst and SPECTRA platforms.


Level-1 Deep Technology Expertise Continuous learning and skills upgrade on latest/emerging Technologies focus across Cloud, Automation, Analytics, DevOps, Digital
Level-2 Focus on Certifications – Basic & Advanced Promoting “Industry Certifications” to benchmark the competencies against the global standards and make this part of every developer’s career enhancement goal
Level-3 Solutions and Best Practices (Process & Tools) Focus on customer solutions and recurring use cases to build a knowledge base of best practices across software engineering, operations excellence, business domains
Level-4 Platform Focus “Codified Knowledge” in the form of Platforms for Data Analytics, DevOps, Cloud & Automation with source code in re-usable formats. Well-Architected Frameworks and leveraging open-source platforms with custom component enhancements & integrations to save effort, time, and improved quality with each new engagement
Level-5 Product Offerings Prescriptive and pre-created products that customers can use in a “touchless” manner as SaaS or Marketplace offerings like a typical ISV solution with little or no dependency on associated professional services. Major benefit in enabling frictionless jumpstart on specific business problems.

Summary
Relevance Lab has made significant investments in creating IT and Business Transformation platforms that provide us a key competitive advantage in unlocking value for our customers across DevOps, Analytics, Cloud, Automation and Digital Engineering. By following a service maturity model that goes beyond just headcount and competencies we have been able to bring the value of platform and products to solve the digital transformation puzzle for our 50+ customers.

To know more about how can our products and platforms help feel free to contact us marketing@relevancelab.com.



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