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2020 Blog, Blog, Featured, RLCatalyst Blog, ServiceNow

Relevance Lab in partnership with ServiceNow and AWS has launched a new solution (ServiceNow scoped application) to consume Intelligent Automation BOTs from within ServiceNow self-service Portal with 1-Click automation of assets and service requests using the Information Technology Service Management (ITSM) governance framework. This RLCatalyst BOTs Service Management (RLCatalyst BSM) connector is available for private preview and will very soon be also available on ServiceNow Marketplace. It integrates with ServiceNow self-service Portal and Service Catalog to dynamically publish an enterprise library of BOTs for achieving end to end automation across infrastructure, applications, service delivery and Workflows. This solution builds on the concept of “Automation Service Bus” architecture explained in a blog earlier.

The biggest benefit of this solution is a transition to a “touchless” model for automation within ServiceNow Self Service Portal with a dynamic sync of enterprise automation libraries. It provides an ability to add new automation without a need to build custom forms or workflows inside ServiceNow. This makes creation, publishing and lifecycle management of BOTs automation within the existing governance models of ITSM and Cloud frictionless leading to faster rollout and ROI. Customers adopting this solution can optimize ServiceNow and Cloud operations costs significantly with self-service models. A typical large enterprise Service Desk team gets a huge volume of inbound tickets on a daily basis and more than 50% of these can be re-routed to self-service requests with a proper design of service catalog, automation and user training. With every ticket fulfilment cost (normally US $5-7) now handled by BOTs there is a significant and measurable ROI along with faster fulfilment, better user experience and system based compliance that helps in audits.

Following are the key highlights of this solution

  • Rendering of RLCatalyst BOTs under ServiceNow Service Catalog for 1-Click order and automation with built in workflow approval models.
  • Ability of ServiceNow Self Service users to order any Automated Service Request from this standard catalog covering common workflows like.
    • Password Reset Requests.
    • User Onboarding.
    • User Offboarding.
    • AD/SSO/IDAM integration.
    • Access and Control for apps, tools, and data.
    • G-Suite/O365/Exchange Workflows.
    • Installation of new software.
    • Any standard service request made available by enterprise IT in a standard catalog.
  • Security and approvals integrated with existing ServiceNow and AD user profiles.
  • Ability to involve any BOT from the RLCatalyst BOTs server that provides integration to agent base, agent-less, Lambda function, scripts, API based, UI based automation functionality.
  • A pre-built library of 100+ BOTs provided as out-of-the-box solution.

As a complementary solution to AWS Service Management connector customers can achieve complete automation for their Asset and Service Requests with Secure Governance. For assets being consumed on non AWS footprints like VMWare, Azure, On-prem systems, the solution supports automation with Terraform templates to address hybrid-cloud platforms.

What are BOTs?
Any Automation functionality dealing with common DevOps, TechOps, ServiceOps, SecurityOps and BusinessOps. BOTs follow an Intelligent Automation maturity model as explained in this blog earlier.

  • BOTs Intelligent Maturity Model
    • Task Automation.
    • Process Automation.
    • Decisioning Driven Automation.
    • AI/ML Based Automation.

BOTs vs Traditional Automation

  • BOTs are reusable – separation of Data and Logic.
  • BOTs support multiple models – AWS Lambda Functions, Scripts, Agent/Agentless, UIBOTs etc with better coverage.
  • BOTs are managed in a Code repository with Config Management (Git Repo) – this allows the changes to be “Managed” vs “Unmanaged scripts”.
  • BOTs are wrapped in YAML Definitions and exposed as Service APIs – this allows BOTs to be involved from Third-Party Apps (like ServiceNow).
  • BOTs are “Managed & Supervised Runs” – BOT Orchestrator manages the lifecycle to bring in Security, Compliance, Error Handling and Insights.
  • BOTs have a Lifecycle for Intelligent Maturity.
  • Open Source Platform that can be extended and integrated with existing tools on a journey to achieve AIOps Maturity.
  • Very deeply embedded with ServiceNow and leverages data and transaction integration in a bi-directional way.

The following image explains the RLCatalyst BOTs Service Management Architecture.

How does RLCatalyst BOTs Service Management work?
Integrating your ServiceNow instance with RLCatalyst BOTs Server helps you to publish self-service driven automation to your ServiceNow Service Portal without the need for custom coding or form design. Your users can order items from the Service Catalog which are then fulfilled by BOTs while maintaining record of the transactions in ServiceNow via Service Requests.

The ServiceNow administrator first downloads the scoped application and installs it in her ServiceNow instance. The application can be deployed from the Github repository provided by Relevance Lab. In the near future, this application will also be available from the ServiceNow Application Store.

Once installed, the application is configured by the ServiceNow Administrator. The person will fill the “BOTs Server Configuration” form. The required parameters are BOTs Server URL, Server Name, Is Default, Username and Password. This information is stored in the ServiceNow instance and is then used to discover and publish BOTs from the RLCatalyst BOTs Server.

The application administrator clicks on the Discover BOTs screen to retrieve the list of latest BOTs available on the BOTs Server. Once this list is displayed, the administrator can choose the BOTs person wants to publish and select the kind of workflow person wants to associate with that BOT (none, single or multi-level approvals). Then person clicks on the Publish button on doing which the BOTs are published to the Service Portal along with all the Forms associated with the BOT for input.

End-users can then use the self-service Catalog items to request fulfilment by BOTs.

What is the standard library of RLCatalyst BOTs available with this solution?
RLCatalyst provides a library of 100+ BOTs for common Service Management tickets and can help achieve up to 30-50% automation with out-of-the-box functionality across multiple functionalities as explained in diagram below.

  • User Onboarding and Offboarding.
  • Cloud Management.
  • DevOps.
  • Notification Services.
  • Asset Management.
  • Software and Applications Access Management.
  • Monitoring and Remediation.
  • Infrastructure Provisioning with integration to AWS Service Catalog.

Summary of Solution benefits
The RLCatalyst BOTs Service Management connector is providing an enterprise wide automation solution integrating ServiceNow to Hybrid Cloud assets with an ability to have self-service models. The automation of Asset and Service requests provides significant productivity gains for enterprises and in our own experience has resulted in achieving 10 FTE productivity, 70% automation of inbound requests and more than US $500K of annual savings on operations costs (including reduced headcount), ITSM license costs, Cloud assets optimized usage with compliance and 50% efficiency gains on internal IT Workflows.

Following are some key blogs with details of solutions addressed with this RLCatalyst BSM connector.


For more details, please feel free to reach out to marketing@relevancelab.com



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2020 Blog, Blog, Featured, ServiceNow

With growing use of AWS Cloud across different industry segments for frictionless business, the use case of “Enabling Scientific Research” leveraging Cloud has unique benefits. Research is a very specialized field driven by a community of “Researchers” who want to focus on “Discovering Science than Servers”. Researchers day-to-day work requires processing data, collaborating online, and trying to maintain labs remotely. There is a need to democratize research computing so that everyone can use that easily.

Working closely with our AWS partners, Relevance Lab is creating an AWS “Research Workbench” powered by Intelligent Automation that can enable use of Cloud by Research Institutions and Researcher’s a frictionless manner.

Core functionality needed

  • Basic need of High End and Research focused enterprises to be able to leverage AWS products seamlessly for research oriented business needs.
  • Specialized roles – Principle Investigator, Researchers under one or many Research projects with different funding sources (Public and private).
  • Ability to collaborate with Intramural and Extramural researchers.
  • Specialized tools and software needs for an Analytics solution – AWS SageMaker, EMR, AI/ML, HPC, data security, secure Workspaces, large data sets sharing capability etc.
  • Need for proper AWS Management & Governance with the ability to manage Self-Service (ITSM or custom portals) based lifecycle management (Provisioning, Managing, De-provisioning of users and assets).
  • Proper cost and budget management and controls.

Additional challenges for Research Projects

  • Massive Volumes of Data.
  • Cross functional research teams.
  • Research data management with compliance and security considerations.
  • Leveraging new techniques of AI/ML, serverless computing, spot instances for HPC etc.

Scientific community has to adapt these challenges and AWS Cloud provides the platform for collaboration, on-demand resources and scale in a secure and compliant manner. Bringing together relevant AWS tools to create a bundle of Research Workbench makes this easier.

Catering to research needs special attention to the use-cases that may come up. For example a researcher may be working on a data science project using AWS Sagemaker notebooks and a large volume of research data in an S3 bucket. Given the sensitive nature of data, the access to the bucket may need to be secured within the organization and accessible only from within the specific network. Also a researcher may only need to access his own data and computing resources. We have developed a security model around the same which addresses such needs. The researchers can only access the resources from a Workspace created for them for that purpose.


To cater to the above the solution encompasses a “Research Portal” for user interactions and a specialized “Research Workbench” for collaborating on tools and data.

  • Research Portal – Managed with existing ITSM Self Service Portals like ServiceNow.
  • Research Workbench – Created by using AWS standard products, Service Catalog and Control Tower to enforce governance.

The above features allow creating and managing the lifecycle of a Research within an enterprise by leveraging investments in existing ITSM Portal and providing a seamless experience for AWS consumption. The solution leverages existing best practices of AWS Control services with Control Tower, Service Catalog, secure Access and automated provisioning/deprovisioning of resources. A critical part of such a Research Portal is proper cost management and tracking of research budgets and consumption against the same.

The following diagram explains the building blocks of a Research Workbench solution deployed with integration to ITSM Platforms like ServiceNow and using the AWS Service Management connector.


The reference deployment architecture using AWS Control Tower (CT) best practices is explained below. The access is controlled using AWS Simple AD and IAM roles.


The entire cycle of onboarding new researchers and provisioning assets for their research is automated using RLCatalyst BOTs solution with 1-Click deployment while still following the ITSM best practices as explained below.


Research Workbench Features
Following is a sample list of features planned (this is an indicative list only and not comprehensive)


Summary of Solution benefits
Based on the pre-built functionality of ServiceNow Self Service Portal, AWS standard products and our custom solutions are integrating the two platforms with a specialized research focussed use case. The following benefits includes:


  • Quick start solution targeting Academic and Research Institutions – New and existing AWS customers.
  • Existing customers with ITSM investments.
    • Using existing ITSM platforms (ServiceNow, Jira Service Desk, Freshservice).
  • Focusing on primarily “Built on AWS Solution” with standard products.
    • AWS Control Tower, Service Catalog, ITSM Connector, Sagemaker, Workspaces, EC2, S3, RDS, EMR etc.
  • Deployment options.
    • Per customer Research Solution deployment (using customer Cloud and ITSM resources).
    • Hosted solution offered to customers with (Managed Services based Cloud and ITSM platforms).
  • RLCatalyst leveraged Solution(Automation, Service Portal, Observability and Cost Governance) add-ons.
  • Pre-built solution to address 80-90% standard needs with scope of some customer specific customizations.
  • Ability to on-board new customer in 3-4 weeks based on pre-built offering with agility and low onboarding costs.

For a demo video please click here

For more details, please feel free to reach out to marketing@relevancelab.com



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2020 Blog, Blog, Featured, ServiceOne, ServiceNow

AWS provides a Service Management Connector for ServiceNow and Jira Service Desk end users to provision, manage and operate AWS resources securely via ITSM Portal. However, a similar solution does not exist for FreshService. The same maturity of end to end automation for Freshservice customers can be provided by using Relevance Lab’s RLCatalyst BOTs solution. It will provide an Automation Service Bus between ITSM tools and AWS Cloud assets.

Freshservice is an Intelligent Service Management platform, which comprises of all the essential modules like Incident Management, Problem Management, Change Management, Release Management, Project Management, Knowledge Management and Asset Management including Hardware, Software and Contracts. It also provides consolidated reports including analytics.

Many customers are adopting Freshservice as an ITSM cloud based solution and orchestrating self-service requests for organizations. One of the common automation needs is for User and Workspace onboarding and offboarding that involves integration with HR systems, AWS Service Catalog and AWS Control Tower for proper management and governance. Similarly using Infrastructure As Code model, organizations are using Cloud Formation based template models for complex workloads provisioning with 1-Click models.

The Freshservice workflow automator with RLCatalyst BOTs integration helps in automation of simple repetitive tasks like assignment of tickets to the right groups, and setup of multi-level approvals. It is a simple drag and drop interface which can help to automate most of the simple use cases. In addition, the webhook option allows automation of complex workflows or use cases by integrating with the right automation tools. In addition to this, the business rules for forms feature will enable you to describe conditional logic and actions to create complex dynamic forms.

The below diagram illustrates the Integration Architecture between FreshService, AWS and RLCatalyst.


Using the integrated solution, organizations can automate use cases related to both End User Computing (EUC) and other standard Server side workloads provisioning. Two common examples are :

  • User and Workspace Provisioning : Onboard a new user and request for an AWS workspace where the original request is generated by Workday/Taleo.
  • Server Infrastructure Provisioning, Application Deployment and Configuration Updates : Request for provisioning of a complex multi-node workload using Service Catalog item fulfilled with an AWS Cloud Formation template and post provisioning setup.

The below diagram illustrates the following EUC automation.


The steps to Onboard a new user and Workspace in an automated are as follows.

  • RLCatalyst enables Freshservice to create an Service Request(SR) using the file generated from Workday or Taleo.
  • Once an SR is created, the workflow automator of Freshservice triggers the approval workflow for either auto approval, cost based approval or role-based approval.
  • Based on the approval workflow defined, and successful execution of the same, the next step is to request RLCatalyst to trigger the onboarding workflow within RLCatalyst.
  • RLCatalyst, then enables the BOT 1for creation of a user in simple AD.
  • BOT 2 sends out a request for provision of AWS workspace, while the BOT3 looks for the status of the workspace creations.
  • Once the status is received on the successful provision by the BOT3, the workflow instructs the AWS SNS to send out a notification email to the end user with the workspace details and login credentials.
  • Finally, RLCatalyst sends a request back to Freshservice for the successful closure of the SR.
  • In case of failure of workspace provision, RLCatalyst will instruct Freshservice to create an Incident to check for the Root Cause Analysis(RCA).

Similarly, a user can request for a multi-node application stack deployment in AWS using Freshservice service catalog. The below diagram illustrates the following :


  • Create the infrastructure with multiple AWS resources (EC2, S3, RDS etc).
  • Deploy one or more applications on the instances created (Web Tier, App Tier, DB Tier).
  • Configure the application with the run-time information. e.g. DNS endpoint creation, bind the listening IP address of an application to the IP address of the instance created. Then update YAML files with environment variable values etc.
  • Deploy the monitoring agents like Infra health, App health, Log monitoring and Service Registry.
  • Setup network configurations like hosted zones, routes etc and setup security configurations like SSL certificates.

The multi-stage orchestration requires a workflow for state and context management during the lifecycle and this is provided by using RLCatalyst Workflow capabilities.

Relevance Lab is a solution partner of Freshservice. We assist the enterprises to adopt AWS Cloud with intelligent automation using RLCatalyst BOTs. Relevance Lab also offers a pre-integrated solution of ServiceOne with Freshservice.

For a demo video and for more details,  please click here.

For more details, please feel free to reach out to marketing@relevancelab.com



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2020 Blog, Blog, Featured, ServiceNow

ServiceNow is the dominant platform used by the organizations for IT Service Management. Organizations are using ServiceNow to build digital workflows and drive frictionless business. By leveraging DevOps & Automation, organizations can speed up software release and upgrade cycles.

With two major releases per year and quarterly updates of security patches, ServiceNow, has ensured that the new features are up to date as per the current industry trend and in compliance with the security mandates. However, to ensure that the customer gets the benefit of all these new features and security updates, organizations need to ensure they update to the latest version on a timely basis. The onus is on the individual organizations to ensure all their customizations are tested thoroughly after every upgrade or security update. Some of these upgrades can run into a few hundreds of test cases in an organization. Testing each of these features after every upgrade would typically take a few weeks to a few months based on the number of test cases. Many organizations are building custom applications on top of the ServiceNow platform, which adds burden on testing during upgrades.

ServiceNow has come out with an Automated Test Framework (ATF) from Istanbul version and above, which can automate testing and reduce the time taken from a few weeks to a few days. ATF is intended for Regression Testing and will ensure that your existing functionality remains intact. It enables no-code and low-code users to create automated test scenarios with ease. ATF reduces bottlenecks related to upgrades by reducing manual testing significantly, with minimal business impact and fasten development efficiency.

Benefits of ServiceNow ATF:

  • Free and Out of Box (OOB) feature without any add-on cost.
  • Fast track upgrade and development time by shifting manual testing to automated testing.
  • Validate all your customizations with every change/update/upgrade.
  • Reduction of manual errors due to consistency in the way the test cases are run.
  • Reusable and simple to use.
  • Testing can be executed along with development resulting in better quality output.

As shown in the above example, a test case with about 10 scenarios which would typically take 10 hours in a normal scenario would take only about an hour with ServiceNow ATF. This can be achieved creating and running batches of tests with automated test suites. Tests can be grouped together using test suites and this enables to run a group of test cases as a single job.

What is the Automated Test Framework?
ATF is a tool to streamline the upgrade and QA processes by building automated tests to check if software or configuration changes have potentially ‘broken’ any existing functionality. It also means developers would no longer be required to start operational activities like code refactoring to generate new test cases.


Customer Solution :
Relevance Lab has helped a large US based Digital learning company benefit from Intelligent Automation of their ServiceNow instance with their ATF. The customer uses ServiceNow extensively for ITSM, IT Asset Management, GRC, IT Operations Management, Vulnerability Remediation life cycle. Relevance Lab has implemented extensive automation of servicenow tickets (Incident, Problem, Change, Service Requests, Vulnerability Incident tickets, CMDB etc.) using their RLCatalyst product. The automation has implemented a number of customised forms, workflows and data schema which needs to be validated everytime a servicenow instance is upgraded. The normal cycle of upgrade would take about a week, but ensuring complete testing post upgrade took upto 3 weeks. To cut down on the cycle time and increase the quality, the entire upgrade cycle and associated functionalities were automated for testing using ServiceNow ATF. This helped in reduction of testing effort of 3 weeks for 400 test cases (104 flows) to 0.5 days using ServiceNow ATF with over 90% reduction in testing efforts and more accurate quality output.

The test cases varied across the below top categories

  • SAML SSO.
  • Okta Provision.
  • User Access Requests.
  • Bot Automation.
  • Asset Catalog.
  • Change Management.
  • Surveys.
  • Contract Management.
  • Asset Management.
  • Knowledge Management
  • Reports & Dashboards.
  • GRC & GDPR.

Relevance Lab is a partner of ServiceNow and helps organizations extract maximum ROI of the ServiceNow Platform. As part of this, we help organizations adopt the automated test reusable framework for all change requests, security updates or even major version upgrades.


For a demo of ServiceNow ATF, please click here.

For more details, please feel free to reach out to marketing@relevancelab.com

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2020 Blog, Blog, DevOps Blog, Featured, ServiceOne, ServiceNow

Using GIT configuration management integration in Application Development to achieve higher velocity and quality when releasing value-added features and products


ServiceNow offers a fantastic platform for developing applications. All infrastructure, security, application management and scaling etc.is taken up by ServiceNow and the application developers can concentrate on their core competencies within their application domain. However, several challenges are faced by companies that are trying to develop applications on ServiceNow and distribute them to multiple customers. In this article, we take a look at some of the challenges and solutions to those challenges.



A typical ServiceNow customization or application is distributed with several of the following elements:


  • Update Sets
  • Template changes
  • Data Migration
  • Role creation
  • Script changes

Distribution of an application is typically done via an Update Set which captures all the delta changes on top of a well-known baseline. This base-line could be the base version of a specific ServiceNow release (like Orlando or Madrid) plus a specific patch level for that release. To understand the intricacies of distributing an application we have to first understand the concept of a Global application versus a scoped application.


Typically only applications developed by ServiceNow are in the global scope. However before the Application Scoping feature was released, custom applications also resided in the global scope. This means that other applications can read the application data, make API requests, and change the configuration records.


Scoped applications, which are now the default, are uniquely identified along with their associated artifacts with a namespace identifier. No other application can access the data, configuration records, or the API unless specifically allowed by the application administrator.


While distributing applications, it is easy to do so using update sets if the application has a private scope since there are no challenges with global data dependencies.


The second challenge is with customizations done after distributing an application. There are two possible scenarios.


  • An application release has been distributed (let’s call it 1.0).
  • Customer-1 needs customization in the application (say a blue button is to be added in Form-1). Now customer 1 has 1.0 + Blue Button change.
  • Customer-2 needs different customization (say a red button is to be added in Form-1)
  • The application developer has also done some other changes in the application and plans to release the 2.0 version of the application.

Problem-1: If application 2.0 is released and Customer-1 upgrades to that release, they lose the blue-button changes. They have to redo the blue-button change and retest.



Problem-2: If the developer accepts blue button changes into the application and releases 2.0 with blue button changes, when Customer-2 upgrades to 2.0, they have a conflict of their red button change with the blue-button change.



These two problems can be solved by using versioning control using Git. When the application developers want to accept blue button changes into 2.0 release they can use the Git merge feature to merge the commit of Blue button changes from customer-1 repo into their own repo.


When customer-2 needs to upgrade to 2.0 version they use the Stash feature of Git to store their red button changes prior to the upgrade. After the upgrade, they can apply the stashed changes to get the red button changes back into their instance.


The ServiceNow source control integration allows application developers to integrate with a GIT repository to save and manage multiple versions of an application from a non-production instance.


Using the best practices of DevOps and Version Control with Git it is much easier to deliver software applications to multiple customers while dealing with the complexities of customized versions. To know more about ServiceNow application best practices and DevOps feel free to contact: marketing@relevancelab.com


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2020 Blog, Blog, Featured, RLAws Blogs, ServiceNow

Using ServiceNow, AWS Service Catalog and RLCatalyst to create a 1-Click model


AWS Service Catalog allows organizations to create and manage catalogs of IT services that are approved for use on AWS. These IT services can include everything from virtual machine images, servers, software, and databases to complete multi-tier application architectures. AWS Service Catalog allows you to manage commonly deployed IT services centrally. It helps you achieve consistent governance and meet your compliance requirements while enabling users to implement only the approved IT services they need quickly.


Working closely with AWS and ServiceNow partnership teams, we have created an integrated solution for enterprises to enable Frictionless User Onboarding and Offboarding in these challenging times of COVID-19. The solution brings together the following building blocks.


Automation:


  • Auto-notification from HR systems for new Employee Onboarding or Offboarding or with Self Service Portals.
  • Workflow Automation in ServiceNow for user-driven or event generated request handling and auto-workflow trigger.
  • Cloud automation with appropriate compliance and policy checks.
  • Orchestration dealing with multiple enterprise systems adapters, complex workflows with integrated approval management based on company policies.
  • Hyper-Automation using a “Service Bus” Model with BOTs across Cloud and Datacenter workloads of Systems and Apps. These cover End User Computing devices (desktops) & Servers with a combination of Windows and Linux workloads.

Integration Service Bus:


  • Integration with Taleo or Workday HR systems that manage the People Management workflows.
  • Integration with Organization Identify and Access Management Tools (Active Directory, SSO, IDAM).
  • Integration with existing ITSM Tools, CMDB/Asset Management and Self Service Portals.
  • Integration with Cloud Infrastructure and Hybrid setups with appropriate policy controls with cost & governance management.
  • Integration with Automated Vulnerability and Patch management lifecycle for all Dynamic Assets.

Intelligent Compliance:


  • Existing SOX processes for assets and resource access controls and compliance.
  • Software Asset Management (SAM) controls as appropriate for the organization (Dynamic Systems and Software CMDB updates).

The following diagram explains the end to end orchestration.



In the sample flow simulated both single-user and bulk user onboarding is supported with an automated multi-stage process that covers Service request creation, AD User provisioning, AWS Workspace provisioning, and notification to end-user post provisioning.


Using RLCatalyst Intelligent automation product the entire solution can be downloaded by customers from a marketplace and enabled in their environments. It is pre-bundled for deployment inside a secure customer environment and includes:


  • A ServiceNow plug-in.
  • An RL BOTs server deployment.
  • AWS Service Catalog integration and BOTs server deployment inside a secure environment of the customer.

For more details, please feel free to reach out to marketing@relevancelab.com

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