High-Performance Systems

Engineered for Scale and Reliability.

Specialists in building high-throughput, low-latency systems that power critical business operations

UK-based | Established 2011 | 20+ Years Experience
What we do
1. Performance-Critical Systems

Design and build software that handles high transaction volumes with consistently low latency and reliability. Relevant for financial platforms, billing systems, and multi-tenant SaaS applications where downtime or slow performance directly impacts revenue or regulatory obligations.

  • Processing pipelines handling millions of daily transactions
  • Real-time data processing with sub-second response times
  • Message queue architectures for asynchronous processing at scale

Key technologies: Java, Python, AWS Lambda, SQS, PostgreSQL, Redis

2. Cloud Architecture & Migration

Design scalable AWS solutions and migrate legacy systems to modern cloud infrastructure. Includes infrastructure planning, cost optimization, and gradual migration strategies that minimize business disruption.

  • Zero-downtime migrations from on-premises to cloud
  • Horizontally scalable microservices and serverless architectures
  • Infrastructure cost reduction through right-sizing and optimization

Key technologies: AWS (EC2, ECS, Lambda, RDS, DynamoDB, S3), Terraform, Docker

3. Performance Optimization

Address performance bottlenecks and reduce operational costs in existing applications. Work includes system profiling, efficiency improvements, memory management, and strategic re-architecting of underperforming components.

  • Memory and resource management for high-throughput applications
  • Database and caching strategies for data-intensive workloads
  • Critical path analysis and selective refactoring to eliminate bottlenecks

Key technologies: Java profiling tools, database optimization, caching strategies

Technical capabilities overview
Core Expertise:
  • High-volume, low-latency data processing
  • System integration and complex business rules
  • ETL pipelines and data warehousing
  • Authentication and security (OAuth 2.0 / 2.1, AWS Cognito)
  • Database design and performance optimization
  • Security & compliance (data classification, encryption, access control, secure development practices)

Primary Stack: Java | Python | TypeScript | AWS | Terraform | PostgreSQL | MySQL | Docker | Linux

AWS Services – Core:
  • Compute & Runtime: EC2, ECS, Fargate, Lambda
  • Storage & Data: S3, RDS, DynamoDB, Redshift, ElastiCache
  • Integration & Messaging: SQS, SNS, API Gateway
  • Identity & Security: IAM, KMS, Cognito
AWS Services – Supporting & Infrastructure:
  • Networking & Delivery: VPC, Route53, CloudFront
  • Storage Infrastructure: EBS, EFS
  • Security & Protection: WAF
  • Container Management: ECR
How We Work
Engagement Style

Engagements are hands-on and engineering-led, typically working directly with in-house teams. We take ownership of complex or high-risk areas while ensuring knowledge transfer and long-term maintainability.

Project Delivery

End-to-end management from requirements through deployment. Projects include comprehensive testing (unit, integration, end-to-end, performance) appropriate for complex business rules. Post-delivery support is provided to ensure smooth integration and operational stability.

Expertise

Joseph Consulting brings over 20 years of commercial software development experience with a computer science engineering background. Deep expertise in performance-critical systems, cloud architecture, and complex integrations.

Extended Capabilities

Professional relationships with external specialists provide access to additional capabilities when projects require extended team support.

Security & Compliance

Security and compliance are treated as first-class concerns. We follow industry best practices for secure development, data classification, encryption, access control, and data retention. Ongoing training and awareness ensure security considerations are embedded throughout delivery.

TYPICAL ENGAGEMENTS

Joseph Consulting works with organizations where software reliability, performance, and scalability are business-critical.

  • SaaS companies operating at scale with multi-tenant platforms
  • Financial services and billing platforms handling sensitive data
  • Organizations with complex data processing and ETL requirements
  • Businesses maintaining critical legacy systems
  • Teams requiring senior engineering expertise for specific initiatives
  • Long-term or mission-critical engagements rather than short, exploratory projects
Selected Experience

Disclaimer: Due to confidentiality agreements, client names are not disclosed.

Case Study1: Authentication Modernization

Summary: Zero-downtime migration to OAuth 2.1 with AWS Cognito, enabling SSO across multiple platforms.

Industry: SaaS Billing Platform

Challenge: Migrate multi-tenant SaaS application and sister BI platform from database-based authentication to AWS Cognito OAuth 2.1 while maintaining service continuity across both systems.

Solution:

  • Implemented dual-mode authentication supporting both traditional and Cognito
  • Enabled tenant-by-tenant migration with zero downtime
  • Custom Lambda functions for user migration and JWT token enrichment
  • Integrated both the primary platform (Java/Spring/Hibernate) and BI platform (Apache Superset/Python)
  • Bidirectional synchronization between application database and Cognito

Result: Successful migration with no service disruption. Enabled single sign-on across both platforms. Improved security posture and reduced authentication maintenance overhead.

Technologies: AWS Cognito, Lambda, Java, Spring, Python, Apache Superset, OAuth 2.1

Case Study 2: Memory Optimization

Summary: JVM and caching optimization reducing memory footprint by 85% and eliminating performance bottlenecks across multiple applications.

Industry: Enterprise Data Processing

Challenge: ETL engine loading millions of records experienced severe memory bloat from duplicate strings, causing frequent full garbage collections and performance degradation. Traditional caching strategies were also contributing to memory pressure.

Solution:

  • Migrated to G1 garbage collector with string deduplication enabled
  • Redesigned caching strategy to reduce memory overhead without breaking existing functionality
  • Optimized memory allocation patterns across critical paths

Result:

  • Reduced memory footprint by 85% (245MB → 36MB on sample data)
  • Eliminated frequent garbage collection pauses
  • Client applied optimizations to other applications within the SaaS platform
  • Significant infrastructure cost savings across multiple services

Technologies: Java, JVM tuning, G1GC, caching optimization

Case Study 3: Archive Generation at Scale

Summary: Redesigned archive generation to handle very large archives with hundreds of thousands of files without memory failures.

Industry: SaaS Billing Platform

Challenge: Billing product’s archiving component failed with memory errors when generating large archive files containing hundreds of thousands of documents. Time constraints and complex legacy codebase made extensive refactoring impractical.

Solution: Redesigned archiving module using parallel processing with thread pools and batch processing to manage memory efficiently. Implemented support for large file formats and optimized S3 fetch operations.

Result:

  • Eliminated all memory-related failures
  • Successfully handled archives containing hundreds of thousands of files
  • Tested with archive sizes ranging from 5GB to over 50GB.
  • Improved generation speed through parallelization
  • Avoided need for major system re-architecture

Technologies: Java, Apache Commons Compress, AWS S3

Case Study 4: Storage Infrastructure Migration

Summary: Migrated legacy storage infrastructure to cloud object storage, eliminating single points of failure and improving scalability.

Industry: SaaS Billing Platform

Challenge: Legacy billing system relied on network file storage creating a single point of failure, scaling difficulties, and continuous capacity monitoring requirements.

Solution:

  • Migrated all product applications from NFS to AWS S3
  • Updated UI components and reporting applications to use S3-based file access
  • Implemented new file access patterns across the application stack

Result:

  • Eliminated single point of failure
  • Improved scalability and reliability
  • Reduced operational overhead for capacity management
  • Enhanced disaster recovery capabilities

Technologies: AWS S3, Java

Contact Info
  • For inquiries regarding performance, scalability, or reliability challenges, contact us for an initial discussion.
  • Initial enquiries are typically responded to within one business day.
0044 74245 59580
info@josephconsulting.uk
124 City Road, London, England, EC1V 2NX