Inigra Software House

Tag: Banking

  • Automated Cloud Patching & Compliance for a Bank

    Automated Cloud Patching & Compliance for a Bank

    Overview

    Automated cloud patching and compliance monitoring framework for a global financial institution. The solution ensures secure, compliant, and efficient management of thousands of AWS resources with zero production downtime.

    Client

    • Country of origin: EU-based global bank with international operations

    • Industry: Financial services / banking

    • Scale: Tens of thousands of employees, multi-country presence, strict regulatory environment (EU & global)

    • Client type: Enterprise (regulated industry, mission-critical systems)

    • Website: (confidential, NDA)

    Challenge

    The bank’s previous patching process was manual, slow, and prone to downtime, requiring large service windows that disrupted production. After migrating to AWS, the frequency and complexity of updates grew due to:

    • Regulatory and political requirements for frequent patching,

    • Strict internal security SLAs (30/60/120 days depending on severity),

    • Need to patch thousands of EC2 instances plus OS, databases, and network configurations,

    • Maintaining full visibility of compliance and encryption posture across AWS services.

    Solution

    We designed and delivered a fully automated AWS-native patching and remediation framework using AWS Systems Manager, including:

    • Parallel patching of EC2 instances to minimize service windows.

    • Automated updates of OS packages, middleware, and application layers.

    • Enforcement of network security policies alongside patching.

    • Continuous monitoring of encryption compliance:

      • EBS encryption enforced,

      • S3 SSL-only policies,

      • RDS encryption enforced,

      • CloudTrail encryption enabled.

    • Real-time dashboards in CloudWatch for SLA adherence, patch compliance, and encryption status.

    • Pre/post-patching audits and automated application testing to validate updates.

    • Framework aligned with AWS Well-Architected best practices for security and operational excellence.

    Results

    • 95% faster patching cycles (days → hours).

    • Zero production downtime during security updates.

    • 100% compliance with internal patching SLAs (30/60/120 days).

    • Improved audit readiness with continuous compliance monitoring.

    • Reduced manual effort for IT staff, freeing resources for strategic projects.

    Supporting Information

    • Key Technologies: AWS Systems Manager, CloudWatch, CloudTrail, EC2, RDS, S3, IAM, AWS Config.

    • Security & Compliance: Alignment with ISO 27001, PCI DSS, GDPR, and internal banking regulations.

    • Team: Cloud architects, DevOps engineers, security specialists.

    Process

    1. Assessment & Discovery – review of current patching workflows and regulatory SLAs.

    2. Architecture Design – AWS-native framework blueprint for automation and monitoring.

    3. Implementation – Systems Manager automation documents (SSM), compliance baselines.

    4. Testing – pre/post patching validation, automated app regression testing.

    5. Rollout – staged rollout across dev → test → production.

    6. Handover & Training – client’s IT operations team enabled to manage patching autonomously.

    Client Testimonial

    “With the automated patching framework, we not only reduced downtime to zero but also achieved a level of compliance that auditors immediately recognized. Our IT team can now focus on delivering new services instead of firefighting patch cycles.”
    — name withheld due to NDA

  • Design and rollout of a scalable transaction data storage and processing platform

    Design and rollout of a scalable transaction data storage and processing platform

    Overview
    A robust backend platform to store, process, and analyze high volumes of transaction data in real time. Designed for scalability, resilience, and integrity, it powers reporting, analytics, and system integrations for business-critical operations.

    Client

    • Country: (confidential / US-based)

    • Industry: Financial services / transaction processing

    • Scale: Millions of transactions daily across multiple systems

    • Type: Enterprise (Fortune 500)

    • URL: Confidential

    Challenge
    “Our transaction data kept growing beyond the limits of our legacy systems. Reporting lagged by hours, queries timed out, and compliance teams lacked reliable audit trails. We needed a scalable, resilient backend that could ingest millions of events per day without bottlenecks.”

    Solution

    • Delivered a backend platform with:

      • Scalable Data Ingestion via Apache Kafka for high-frequency streams

      • Reliable Storage Layer combining PostgreSQL (transactions) and ClickHouse/BigQuery (analytics)

      • Stream Processing Pipelines using Apache Flink & dbt for real-time transformations and enrichment

      • Security & Compliance with encryption, RBAC, and audit logs

      • Integration-Ready APIs exposing curated datasets to BI, finance, and ML systems

    • Backend & Data Tech: Kafka, Flink, dbt, PostgreSQL, ClickHouse/BigQuery, Python

    • Infrastructure: Kubernetes, Terraform, AWS/GCP with encrypted S3 backups

    • Team: 2 backend/data engineers, 1 DevOps, 1 project manager

    Result

    • Ingestion throughput: >50,000 transactions/second without degradation

    • Reporting latency reduced from hours to seconds

    • Regulatory audits completed 30% faster due to reliable logs

    • Enabled real-time dashboards for finance and operations teams

    • Provided integration endpoints for machine learning models and BI platforms

    Additional Information

    • Key numbers: 5B+ rows stored, 7 TB processed daily, 99.99% uptime

    • Technologies: Kafka, Flink, dbt, PostgreSQL, ClickHouse, Kubernetes, Terraform, AWS/GCP

    • Security: OAuth2, encryption at rest & in transit, full audit trail

    Process

    • Discovery → mapped transaction flows, compliance needs, and reporting SLAs

    • Architecture → designed multi-tier storage and streaming pipelines

    • Implementation → iterative rollouts with blue/green deployments on Kubernetes

    • Validation → performance tests at 2× peak traffic; compliance validation with anonymized data

    • Go-live → phased migration from legacy, followed by 24/7 monitoring and support

    Client Testimonial

    “With this new platform, we finally trust our data. Reports run in seconds, regulators are satisfied, and our systems scale as the business grows.”