Description

Introduction

As financial institutions and data-driven enterprises modernize their infrastructure, deploying kdb+ on cloud platforms has become essential for scalability, resilience, and cost optimization. This training provides a comprehensive guide to implementing kdb+ & q in cloud-native environments using AWS, Microsoft Azure, and Google Cloud Platform (GCP).

Participants will learn how to design cloud architectures for kdb+, manage distributed systems, implement high availability, optimize performance, and control infrastructure costs across leading cloud providers.

This course combines architectural concepts with hands-on deployment practices to help organizations build secure, scalable, and production-ready kdb+ cloud solutions.

Prerequisites

1. Basic understanding of kdb+ architecture
2. Working knowledge of q programming
3. Familiarity with Linux/Unix environments
4. Basic knowledge of networking concepts (TCP/IP, ports, firewalls)
5. Introductory understanding of cloud computing concepts (VMs, storage, networking)
6. Prior experience with on-premise kdb+ deployment
7. Basic knowledge of Docker or containerization

Table of Contents

Module 1: Cloud Computing Fundamentals for kdb+

1. Cloud Service Models (IaaS, PaaS, SaaS)
2. Regions, Availability Zones, and Multi-Region Design
3. Compute, Storage, and Networking Overview
4. Cloud Security Basics
5. Comparing AWS, Azure, and GCP for kdb+

Module 2: kdb+ Architecture in the Cloud

1. Single-node vs Distributed kdb+ in Cloud
2. HDB/RDB/TP Architecture in Cloud Environments
3. Separating Compute and Storage
4. Stateless vs Stateful Services
5. Cloud-Native Design Principles

Module 3: Deploying kdb+ on AWS

1. EC2 Instance Selection for kdb+
2. EBS vs Instance Store for Time-Series Data
3. S3 Integration for HDB Storage
4. VPC, Subnets, and Security Groups
5. Auto Scaling & Load Balancing
6. Monitoring with CloudWatch
7. Backup & Disaster Recovery Strategies

Module 4: Deploying kdb+ on Microsoft Azure

1. Azure VM Configuration for kdb+
2. Azure Managed Disks vs Blob Storage
3. Virtual Networks and Network Security Groups
4. Azure Availability Sets & Zones
5. Monitoring with Azure Monitor
6. Cost Optimization Strategies

Module 5: Deploying kdb+ on Google Cloud Platform (GCP)

1. Compute Engine for kdb+
2. Persistent Disk vs Local SSD
3. Cloud Storage Integration
4. VPC and Firewall Configuration
5. High Availability with Managed Instance Groups
6. Monitoring with Cloud Operations Suite

Module 6: Containerizing kdb+

1. Introduction to Docker for kdb+
2. Building kdb+ Docker Images
3. Managing Stateful Workloads
4. Introduction to Kubernetes
5. Deploying kdb+ on EKS, AKS, and GKE
6. Scaling and Rolling Updates

Module 7: High Availability & Disaster Recovery

1. Multi-AZ Deployment Strategies
2. Cross-Region Replication
3. Data Backup Automation
4. Failover Strategies
5. Testing DR Plans

Module 8: Performance Optimization in Cloud

1. I/O Performance Tuning
2. Memory Optimization for RDB/HDB
3. Network Latency Optimization
4. Autoscaling Strategies
5. Benchmarking kdb+ in Cloud

Module 9: Security & Compliance

1. IAM Roles and Access Control
2. Encryption at Rest and In Transit
3. Secure IPC Configuration
4. Secrets Management
5. Compliance Considerations (Financial Services)

Module 10: Cost Management & Governance

1. Cloud Cost Models
2. Storage Tier Optimization
3. Reserved Instances & Savings Plans
4. Monitoring Usage and Billing
5. Governance & Resource Tagging

Module 11: Real-World Architecture Case Studies

1. Market Data Platform on AWS
2. Trading Analytics Platform on Azure
3. Research Data Platform on GCP
4. Hybrid Cloud kdb+ Deployment
5. Migration from On-Prem to Cloud