Messaging & Streaming Platform
Asynchronous messaging and streaming infrastructure for decoupled, reactive systems — from simple queues/topics to log-based streams and processing, with comprehensive security and observability.
Messaging & Streaming Platform Architecture
Detailed view showing components, connections, and data flow
Enables Architectural Patterns
Event-Driven Architecture
Systems communicate through events, enabling loose coupling, async workflows, and reactive behavior.
Microservice Architecture
Independent, deployable services aligned to business domains, communicating via APIs, events, or streams.
CQRS
Separate write and read models to optimize for different workloads; often paired with events.
What it is
A comprehensive platform capability that provides messaging and streaming infrastructure to enable event-driven architectures. It spans simple messaging (queues/topics) and streaming (partitioned logs) with retention and replay, integrated with enterprise-grade security and observability.
Modes
- Simple messaging: queues & topics for work dispatch, decoupling, and back-pressure (e.g., RabbitMQ, SQS)
- Streaming: append-only, partitioned logs for high-throughput events, replay, and stateful processing (e.g., Kafka, Pulsar)
- Hybrid: combining messaging reliability with streaming scale and retention
Core Responsibilities
- Durable delivery, ordering where required, and intelligent routing
- Consumer groups, auto-scaling, circuit breakers, and dead letter queues
- Schema governance, compatibility, and event catalog management
- End-to-end observability with distributed tracing and metrics
- Security: encryption, authentication, authorization, and audit trails
- Compliance: data retention policies, GDPR/privacy, and regulatory requirements
Security & Compliance Capabilities
- End-to-end encryption (TLS 1.3, mTLS) and data-at-rest encryption
- Fine-grained access control (RBAC, ABAC) with service identities
- Audit logging and compliance reporting for regulated industries
- Data sovereignty and residency controls
- Vulnerability scanning and security patching automation
- Zero-trust networking with service mesh integration
Observability & Monitoring
- Distributed tracing with OpenTelemetry integration
- Real-time metrics: throughput, latency, consumer lag, error rates
- Automated alerting on SLA breaches and system anomalies
- Log aggregation and correlation across event streams
- Performance profiling and bottleneck detection
- Business metrics: event volume, processing success rates, data quality
Architecture Patterns
- Pub/sub topics with competing consumers and load balancing
- Transactional outbox and saga orchestration patterns
- Event sourcing + CQRS with snapshotting and replay
- Streaming ETL with windowing and stateful processing
- Event-driven microservices with circuit breakers
- Change Data Capture (CDC) with exactly-once processing
Performance & Reliability Patterns
- Partitioning strategies for horizontal scaling
- Backpressure handling and flow control mechanisms
- Idempotent processing and duplicate detection
- Graceful degradation and chaos engineering readiness
- Multi-region replication and disaster recovery
- Auto-healing and self-balancing consumer groups
Tech Examples
- Apache Kafka (with Kafka Streams, ksqlDB, Schema Registry)
- Redpanda (high-performance Kafka-compatible)
- RabbitMQ (with clustering and federation)
- AWS MSK, EventBridge, SQS/SNS
- Azure Event Hubs, Service Bus
- Google Pub/Sub, Cloud Tasks
KPIs/SLIs/SLOs
- End-to-end latency (P50, P95, P99) and throughput
- Message delivery success rate and duplicate rates
- Consumer lag/backlog and processing time
- System availability and MTTR for incidents
- Security: unauthorized access attempts and compliance violations
- Cost efficiency: resource utilization and scaling events