Enhance the scalability, resilience, and performance of blockchain DLT platforms with enterprise-grade DevOps and SRE practices.
Client
A leading provider of real-world asset (RWA) tokenization, digital currency, and interoperability solutions to the world’s largest financial players
Goal
To optimize blockchain DLT platforms for scalability, resilience, and seamless operations through enterprise-grade DevOps and SRE practices
Tools and Technologies
R3 Corda 5, Azure, AWS, G42, Docker, Kubernetes, Helm Charts, Terraform, Ansible, GitHub Actions, Azure DevOps, Jenkins, Prometheus, Grafana, Slack Integration
Business Challenge
Complex Multi-Node Deployments require a mechanism to upgrade CorDapps, notaries, and workers across network participants without downtime or compatibility issues. Meanwhile, security and compliance risks demand strict access controls, network segmentation, and security hardening to protect Corda nodes and ledger operations.
For infrastructure scalability and automation, an efficient approach was required for onboarding new participants and managing network topology across cloud environments. The lack of a Real-Time Monitoring system necessitated the detection of transaction failures, tracking node health, and providing proactive alerts.
To address security vulnerabilities, continuous scanning and security enforcement across CorDapps, containerized nodes, and CI/CD pipelines were required.
Solution
- Enabled zero-downtime CorDapp deployments with automated rollback and stateful upgrades, ensuring stability and ledger integrity
- Secured Corda nodes with RBAC, network segmentation, and security hardening, while optimizing autoscaling for dynamic ledger workloads
- Automated Corda network topology and participant onboarding using modular Terraform & Ansible configurations, ensuring scalability and repeatability
- Implemented real-time monitoring with Prometheus & Grafana, with Slack-based alerts for transaction failures and node health anomalies
- Ensured high availability and auto-healing for Corda network nodes and ledger operations
- Integrated DevSecOps with automated vulnerability scanning for CorDapps, containerized nodes, and CI/CD pipelines
Outcomes
- Accelerated blockchain deployment cycles through CI/CD automation increased deployment frequency by 40% and reduced failures by 60%
- Optimized kubernetes workloads for Corda 5 through efficient resource management resulted in 15% cost savings and improved ledger performance
- Scalable & secure blockchain infrastructure reduced manual intervention by 30%, enabling seamless scaling of Corda network participants
- Proactive incident management for DLT networks through real-time monitoring cut response time by 50% for blockchain issues, ensuring high availability
- Automated workflows accelerated development cycles by 25%, enhancing collaboration across blockchain and DevOps teams
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Transforming payment processing for banking channels
Streamlined payments architecture delivers flexible workflow orchestration, system scalability, and improved data reporting.
Client
A leading Australian bank
Goal
Streamline the payment transaction lifecycle to handle increasing volume and complexity
Tools and Technologies
Jenkins, Kubernetes, Spring, Oracle, PostgresSQL, AWS, Docker, Kafka, Java
Business Challenge
Multiple banking channels - mobile, internet and branch - initiate various payment requests (20+ types such as ACH, mandate and book transfer) that need to be processed. Depending on the payment type, the channel was required to invoke one or more services in a specific order as per the associated business rules.
Changes to these payment workflows stemming from introduction of new payment types or revisions of business rules introduced complex and repeated changes to the bank’s systems, hindering scalability.
Solution
- To support lifecycle management of various payment transactions, including defining different payment workflows, we designed an event-driven architecture comprised of 40+ microservices (e.g., limit, eligibility, and fraud checks, etc.) supported by a Kafka message queuing system
- The architecture involved building an orchestration engine (landing service), acting as a front controller for all payment workflow requests from the various banking channels, such as mobile, internet and branch
- The landing service in turn invokes the corresponding service (limit, eligibility, etc.) based on the payment type and business rules associated with it
- Data flow between these microservices (resulting from further invocations) and other downstream systems is facilitated asynchronously with the help of a distributed messaging system (Kafka)
- Using Jenkins, we built a CI/CD pipeline to streamline the workflow by automatically building, testing and deploying code changes as they are committed
Outcomes
- Significantly eased the management of payment workflows, including those related to the addition of new payment types (resulting from an acquisition)
- Enabled systems to scale without introducing complex changes at the channels
- Improved reporting, resulting from faster access to data through dedicated microservices
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Unified automation strategy enhances efficiency
Automated platform engineering solution improves reliability and lowers costs by 20-50% each for a leading payroll and HR solutions provider.
Client
Leading payroll and HR solutions provider
Goal
Develop automation strategy and framework that accommodates growth and ensures efficiency
Tools and Technologies
Ansible, AWS, Dynatrace, Gremlin, Groovy, Jenkins, Keptn, KICS, Python, Terraform
Business Challenge
The SRE (Site Reliability Engineering) shared services team faced a diverse set of needs relating to automation of infrastructure and services provisioning, configuration, and deployment.
The team was encountering resource constraints, as limited in-house expertise in certain automation tools and technologies was causing delays in meeting critical automation requirements. They also needed to ensure system reliability and were challenged to scale automation solutions to accommodate increasing demands as operations grow.
Solution
- Development of a comprehensive automation strategy to align with objectives, encompassing Terraform, Ansible, Python, Groovy, and other relevant technologies in the AWS environment
- Leveraging our expertise to bridge the knowledge gap, provide training, and augment the client team in handling complex automation tasks
- Implementation of a chaos engineering framework using Gremlin, Dynatrace, Keptn, and EDA tools, to proactively identify weaknesses and enhance system resilience
- Creation of a scalable automation framework that accommodates growing needs and ensures long-term efficiency
Outcomes
- A unified automation strategy that streamlined processes, reduced manual effort, and enhanced overall efficiency by 30%
- The implementation of chaos engineering and self-healing practices, which increased reliability between 20% and 50%
- A reduction in manual interventions along with improved efficiency that will result in cost savings of 25% - 50%
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Quality engineering optimizes a DLT platform
Reliability, availability, scalability, observability, and resilience ensured; release cycles and testing time improve 75% and 80%.
Client
A leading provider of financial services digitization solutions
Goal
Reliability assurance for a digital ledger technology (DLT) platform
Tools and Technologies
Kotlin, Java, Http Client, AWS, Azure, GCP, G42, OCP, AKS, EKS, Docker, Kubernetes, Helm Chart, Terraform
Business Challenge
A leader in Blockchain-based digital financial services required assurance for non-GUI (Graphic User Interface), Command Line Interface (CLI), microservices and Representational State Transfer (REST) APIs for a Digital Ledger Technology (DLT) platform, as well as platform reliability assurance on Azure, AWS services (EKS, AKS) to ensure availability, scalability, observability, monitoring and resilience (disaster recovery). It also wanted to identify capacity recommendations and any performance bottlenecks (whether impacting throughput or individual transaction latency) and required comprehensive automation coverage for older and newer product versions and management of frequent deliveries of multiple DLT product versions on a monthly basis.
Solution
- 130+ Dapps were developed and enhanced on the existing automation framework for terminal CLI and cluster utilities
- Quality engineering was streamlined with real-time dashboarding via Grafana and Prometheus
- Coverage for older and newer versions of the DLT platform was automated for smooth, frequent deliverables for confidence in releases
- The test case management tool, Xray, was implemented for transparent automation coverage
- Utilities were developed to execute a testing suite for AKS, EKS, local MAC/ Windows/ Linux cluster environments to run on a daily or as-needed basis
Outcomes
- Automation shortened release cycles from 1x/month to 1x/week; leads testing time was reduced by 80%
- Test automation coverage with 2,000 TCs was developed, with pass rate of 96% in daily runs
- Compatibility was created across AWS-EKS, Azure-AKS, Mac, Windows, Linux and local cluster
- Increased efficiency in deliverables was displayed, along with an annual $350K savings for TCMs
- An average throughput of 25 complete workflows per second was sustained
- Achieved a 95th percentile flow-completion time that should not exceed 10 seconds
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Release automation reduces testing time by 80%
DevOps implementation and release automation improved testing time, product quality, and global reach for a leading multi-level marketing company.
Client
A leading multi-level marketing company
Goal
Shorten the release cycle and improve product quality
Tools and Technologies
Amazon CloudWatch, Elasticsearch, Bitbucket, Jenkins, Amazon ECR, Docker, and Kubernetes
Business Challenge
The client's Commercial-off-the-shelf (COTS) applications were built using substandard code branching methods, causing product quality issues. The absence of a release process and a manual integration and deployment process were elongating release cycles. Manual configuration and setup of these applications were also leading to extended downtime. Missing functional, smoke, and regression test cases were adding to the unstable development environment. The database migration process was manual, resulting in delays, data quality issues, and higher costs.
Solution
- Code branching and integration strategy for defects / hotfixes in major and minor releases
- Single-click application deployment, including environment creation, approval and deployment activities
- Global DevOps platform implementation with a launch pad for applications to onboard other countries
- Automated configuration and deployment of COTS applications and databases
- Automation suite with 90% coverage of smoke and regression test cases
- Static and dynamic analysis implementations to ensure code quality and address configuration issues
Outcomes
Automation of release cycles delivered the following benefits to the client:
- Release cycle shortened from once a month to once per week
- MTTR reduced by 6 hrs
- Downtime decreased to <4 hours from 8 hours
- Product quality and defect leakage improved by 75%
- Testing time reduced by 80%
- Reach expanded to global geographies
- Availability, scalability, and fault tolerance enhanced for microservices-based applications
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Tech stack automation expedites development by 3x
Manual processes across the multi-technology stack were severely affecting the script development cycles in terms of time, effort and cost. Iris application agnostic Test Automation framework and DevOps integration helped the client reduce the script development time and cost significantly.
Client
A leading building supplies manufacturing company
Goal
To support 30+ applications stack for UI, E2E, APIs, performance, mobile automation along with DevOps pipeline integration
Tools and Technologies
.NET Core, PeopleSoft, Salesforce, WMS, JavaScript, Angular, Foxpro, C#, Selenium, SpecFlow, RestSharp, Nunit, Mobile Center/Emulators, Allure, Jira, Azure Pipeline, GitHub
Business Challenge
The client had technology stacks comprising of diverse technologies that were difficult to manage. Substantial manual effort and time were spent on integrating the checkpoints, elongating the development process. Validating end-to-end business flows across different applications was the prime challenge. Reporting processes were also scattered across the entire application stack, making it vulnerable.
Solution
Iris developed a robust application agnostic Test Automation framework to support the client’s multiple-technology stacks. Following the Behavior-driven Development (BDD) approach to align the acceptance criteria with the stakeholders, we built business and application layers of the common utilities in the core framework.
Our experts identified E2E business flows to validate the downstream impact of the change and automated the entire stack through the shift-left approach. Azure DevOps integration enabled a common dashboard for reporting. The client attained complete version control to track production health and enforce strong validations.
Outcomes
Iris Automation solution enabled the client to surpass several business goals. The key outcomes of the delivered solution included:
- ~65% Increase in automation coverage
- 100+ Pipelines for in-scope applications across multiple environments
- 3700+ Test Automation scripts execution per sprint cycle achieved across applications
- 3X Faster script development of behavior-driven test cases
- Multi-day manual test effort reduced to a few hours of automated regression
- 70% Reduction in effort
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Software transformation gets compliance for bank
Risk & Compliance
Software transformation gets FDIC compliance for bank
World’s renowned investment bank gets timely compliant with new QFC (Qualified Financial Contracts) and FDIC (Federal Deposit Insurance Corp.) regulations through holistic system transformation and extensive QA & testing.
Client
A global investment bank
Goal
To have a unified functional validation system for FDIC compliance
Tools and Technologies
SQL Server, Sybase, Data Lake, UTM, .NET, DTA, Control-M, ALM, JIRA, Git, RLM, Nexus, Unix, WinSCP, Putty, Python, PyCharm, Confluence, Rabacus, SNS, and Datawatch
Business Challenge
The client mandated to comply with new QFC (Qualified Financial Contracts) regulations. The client also needed to perform in-depth functional validation across a revamped data platform to ensure it could timely process, review and submit to the FDIC (Federal Deposit Insurance Corp.) required daily reports on the open QFC positions of all its counterparties.
The project entailed immediate availability and processing of accurate QFC information at the close of each business day to swiftly assess data and note exceptions and exclusions for early corrective action. It also aimed to help the client meet stringent deadlines with varied report formats. Any breach or delay in compliance could attach hefty fines and reputational damage to the bank.
Solution
Iris revamped the entire system and performed end-to-end quality assurance and testing across the new regulatory reporting platform. This meant validating the transformed multi-layer database, user interface (UI), business process rules, and downstream applications.
We identified and solved workflow design gaps affecting data reporting on all open positions, agreements, margins, collaterals, and corporate entities, thus enhancing the capability for addressing irregularities. Our experts established an integrated and collaborative system, commanding transaction and reference data within a single platform by incorporating 166 distinct controls pertaining to data completeness, accuracy, consistency, and timeliness within a strategic framework.
Outcomes
Our quality assurance and testing solution delivered the following impacts:
- Faster and more efficient internal analysis with highly accurate QFC open positions
- 100% compliance with timing and format of required daily QFC report submissions to the FDIC
- Significant decrease in exceptions before the platform went go-live and critical defect delivery drastically reduced post-implementation
- An intuitive UI dashboard reflecting the real-time status of critical underlying data volumes, leakages, job run, and other stats
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Gain speed to market with DevOps solutions
A wealth management firm moved from a legacy application environment to a microservices ecosystem. The switch reduced the production time and expedited the roll-out of releases.
Client
The client is a leading wealth management firm in the U.S.
Goal
DevOps strategy to shorten production timelines and speed time-to-market
Tools and Technologies
JIRA, Jenkins, GitHub, AWS, ECR, Docker, EKS and Helm
Business Challenge
The client used multiple legacy applications with a highly complex codebase to run its operations. As a result, it had long production lifecycles and spent several person-hours in integration and deployment.
On the technology front, the client faced challenges in the way server-side applications were defined, stored and managed. Its IT team also had to manage the deployment of multiple Kubernetes manifest files.
Solution
Iris recommended that the client move to a microservices ecosystem. Here’s how we deployed the solution:
- We defined an enterprise-level DevOps strategy using Helm
- Identified the scope of apps that needed to be onboarded across the enterprise
- Implemented a DevOps pipeline for microservices on the Kubernetes cluster
- Deployed the infrastructure, dependencies and applications with Kubernetes using Helm
- Delivered continuous improvement through Helm release updates and rollbacks
Outcomes
The DevOps pipeline significantly improved time-to-market for new releases.
- 20x faster release cycle
- 40% improvement in quality with end-to-end traceability
- 15x improvement in the mean time to deployment (MTTD)
We also put in place robust security control and validation processes, and provided auditable release requests.
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