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33 resultsDatabase Schema Migration Strategies
Expand-contract pattern, zero-downtime migrations, and tooling.
REST API design principles we follow
Versioning, error formats, pagination, and auth patterns used across all Intersysop-built APIs.
JWT Authentication — Implementation and Security Patterns
Access tokens, refresh tokens, rotation, revocation, and common mistakes.
Privacy-First Data Design — PII Handling Patterns
Tokenisation, pseudonymisation, encryption at rest, and right-to-deletion workflows.
Multi-Tenancy Patterns — Database-per-Tenant, Schema-per-Tenant, and Row-Level
Tradeoffs for SaaS data isolation, compliance, and operational complexity.
Resilience Patterns — Circuit Breaker, Retry, Bulkhead, and Timeout
Prevent cascading failures with proven resilience patterns.
Designing a Data Lake on AWS S3
Folder structure, naming conventions, lifecycle policies, and access patterns.
Data Lake vs Data Warehouse vs Lakehouse
Practical comparison of the three architectures and how to choose.
Batch vs Streaming Pipelines — Choosing the Right Pattern
Lambda architecture, Kappa architecture, and practical guidance for choosing.
ETL vs ELT — Which Pattern Should You Use?
Understand the difference between Extract-Transform-Load and Extract-Load-Transform and when each fits.
Real-Time Analytics Architecture Patterns
Lambda, Kappa, HTAP, and choosing the right pattern for sub-second analytics.
Running Data Workloads on Kubernetes
Spark on K8s, Airflow on K8s, resource requests, and storage patterns.
Secrets Management for Data Platforms
HashiCorp Vault, AWS Secrets Manager, and patterns for rotating credentials safely.
MongoDB Schema Design Patterns
Embedding vs referencing, the subset pattern, and indexing strategy.
Implementing Rate Limiting in APIs
Token bucket, sliding window, fixed window — algorithms and implementation patterns.
Idiomatic REST API Design Patterns
Naming conventions, filtering, sorting, sparse fieldsets, and HATEOAS considerations.
Serverless Architecture — When Functions Work and When They Don't
Cold starts, event-driven patterns, cost model, and the right use cases.
API Pagination — Cursor, Offset, and Keyset Patterns
When each method works, performance tradeoffs, and implementation details.
API Gateway — Responsibilities and Implementation Patterns
Authentication, rate limiting, routing, request aggregation, and when not to use a gateway.
Message Queue Patterns — SQS, RabbitMQ, and Dead Letter Queues
Fan-out, work queues, priority queues, and poison message handling.
PostgreSQL Replication — Streaming, Logical, and Read Replicas
Set up read replicas, understand WAL, and choose between streaming and logical replication.
gRPC Service Design — Protocol Buffers and Production Patterns
Proto file design, streaming, deadlines, interceptors, and error handling.
Database Connection Patterns in PHP
PDO, prepared statements, connection pooling, and transaction management.
Redis Caching Patterns for Production Applications
Cache-aside, write-through, TTL strategy, and cache invalidation approaches.
Infrastructure as Code for Data Platforms with Terraform
Managing cloud data infrastructure reproducibly with Terraform.
Predictive maintenance for fleet management
Time-series models reduced unplanned downtime by 18% across a mixed heavy equipment fleet.
Feature Flags — Safe Deployment and Gradual Rollout
Types of flags, implementation patterns, and avoiding flag sprawl.
Amazon Redshift — Architecture and Query Optimization
Distribution styles, sort keys, VACUUM, ANALYZE, and WLM tuning.
Kubernetes Deployment Patterns for Production Services
Deployments, Services, Ingress, HPA, and resource management.
Event-Driven Data Architecture Patterns
Event sourcing, CQRS, outbox pattern, and when event-driven beats request/response.
Extracting Microservices from a Monolith
The strangler fig pattern, identifying seams, and avoiding the distributed monolith.
Microservices Communication — Sync vs Async Patterns
REST, gRPC, message queues, and choosing the right pattern for each interaction.
Async/Await Patterns and Common Pitfalls
Concurrency, parallelism, error handling, and avoiding common async bugs.