[ X: 1045, Y: 890, Z: 200 ]
Conversational Business Intelligence

Ignis Analytics:
Serverless AWS Migration Platform

Large-scale migration and infrastructure automation moving a conversational AI-driven business intelligence platform from legacy on-prem systems to a serverless, event-driven AWS architecture.

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[ 01 ]

The
Challenge

Ignis Analytics, a conversational AI-driven business intelligence platform, was running on legacy on-premises infrastructure that couldn't support the real-time data ingestion and sub-second query latency the product needed. Migrating a live BI platform to serverless AWS architecture without disrupting existing users or losing data integrity required careful sequencing across multiple accounts and environments.

Beyond the migration itself, the client needed enforceable security standards and full observability baked into the new infrastructure from day one, rather than retrofitted after launch.

Additionally, the existing deployment processes were highly manual and error-prone, severely limiting how fast new features could be released. The engineering team needed a fully automated, resilient CI/CD pipeline that could safely deploy serverless microservices multiple times a day without risking production outages.

What stood in the way

  • Legacy Infrastructure

    On-premises hardware could not support real-time ingestion

  • Latency Ceiling

    The product needed sub-second query response

  • Manual Deployments

    Error-prone releases capping how fast features shipped

  • Security & Observability

    Enforceable standards baked in from day one

Unified platform
  • AWS CodePipeline
  • AWS Lambda
  • CloudFormation
  • CloudWatch
  • Python
  • EventBridge
[ 02 ]

The
Solution

Toadster architected and implemented an AWS Lambda-based ingestion pipeline triggered by EventBridge rules and SQS, enabling real-time event processing with sub-second latency and enterprise-grade reliability. Infrastructure provisioning was fully automated using Terraform modules and AWS CloudFormation stacks across multiple accounts and environments, eliminating manual configuration drift.

We built end-to-end CI/CD pipelines with GitHub Actions and AWS CodePipeline to deploy serverless functions and microservices reliably, and defined and enforced security best practices throughout — IAM least-privilege policies, VPC isolation, and KMS encryption for all data at rest and in transit.

Measurable Impact

The Project
Overview

SYSTEM_DIAGNOSTICS: OPTIMAL
MODULES: ONLINE
Sub-second

Latency for Real-Time Analytics

34%

Infrastructure Cost Reduction

5x

Deployment Frequency Increase

SEQ.01_IMPACT

Delivered Impact

Ignis Analytics now runs on a fully serverless, event-driven AWS architecture delivering sub-second latency for real-time data ingestion and analytics, with automated infrastructure provisioning, enforced security policies, and full-stack observability across every environment.

  • Reports
  • Answers
  • Insights
AI Engine
  1. 01

    Connect

    Bring your data sources together

  2. 02

    Analyze

    AI finds patterns and answers

  3. 03

    Deliver

    Grounded insights that drive action

CLIENT SIGNAL
“The migration wasn't just a lift-and-shift — Toadster rebuilt our infrastructure to be event-driven from the ground up, and the latency improvement was immediately visible to our users.”
— CTO, Ignis Analytics
  • ReliableConsistent data you can depend on
  • AuditableFull traceability and transparency
  • ActionableInsights that drive real outcomes
Architecture

Enterprise
Architecture

Built with modern, scalable technologies designed for production reliability.

Core & Application

AWS LambdaEventBridgeSQSDynamoDBTerraformCloudFormationGitHub Actions

Infrastructure & Delivery

AWS CodePipelineCloudWatchELKPrometheusGrafanaPython

Frequently asked Questions

Common questions about the AWS Serverless Migration

It means moving compute and data workflows off physical or self-managed servers onto AWS's managed serverless services — such as Lambda, EventBridge, and SQS — so infrastructure scales automatically with demand and requires no server maintenance.

By using event-driven services like AWS Lambda triggered through EventBridge rules and SQS queues, which process incoming events immediately rather than waiting for scheduled batch jobs, keeping end-to-end latency in the sub-second range.

Infrastructure as code, using tools like Terraform and CloudFormation, defines cloud infrastructure in version-controlled configuration files rather than manual console setup, preventing configuration drift and making infrastructure changes auditable and repeatable.

Through IAM least-privilege policies that restrict each service to only the permissions it needs, VPC isolation to segment network access, and KMS encryption applied to data both at rest and in transit.

Often yes — because serverless services like Lambda charge per execution rather than for idle server time, combined with practices like resource rightsizing and scheduled shutdowns of non-production environments, total cloud spend typically drops compared to always-on legacy infrastructure.

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