bongoDev

Loading...

Empowering technology learners worldwide with professional online live trainings. Transform your IT career with expert-led courses.

Facebook Instagram LinkedIn Github

Company

About Us
Careers
Blog
Events

Legal

Privacy Policy
Refund Policy
Terms and Conditions

Contact us

[email protected]
01757258398 01978367094 01576641348
01757258398

Our office

Flat 5/A, Shimanto Plaza, Plot #26/D, Main Road-03, Section #11, Mirpur, Dhaka 1216

© 2026 bongoDev. All rights reserved. | ই-ট্রেড লাইসেন্স: TRADEDNCC/015304/2024

Courses Job Success

Blog Events Free Assessment Login

bongoDev | Poison Messages: Detect Deterministic Consumer Failure - Event-Driven Reliability Pro

TopicEvent-Driven Reliability Pro

01Event-Driven Reliability Mental Model: Publish, Persist, Deliver, Process, AcknowledgePreview
02Synchronous vs Asynchronous Architecture: Choose Failure Semantics Deliberately
03Event, Message, Command, Notification & Task: Model Intent Correctly
04Queues, Topics, Streams & Logs: Pick the Right Delivery Shape
05Producer → Broker → Consumer: Responsibility Handoffs & Failure Windows
06Delivery Semantics: At-Most-Once, At-Least-Once & Exactly-Once Boundaries
07Message Envelope Design: IDs, Correlation, Causation, Time, Source & Version
08Event Naming & Domain Semantics: Facts Should Survive Implementation Changes
09Schema Evolution: Backward, Forward & Full Compatibility
10Schema Registry & Contract Governance
11Event Time vs Processing Time: Reason About Late and Delayed Events
12Ordering Guarantees: Define the Scope Before Depending on Order
13Partitioning & Sharding: Scale Without Losing Per-Key Correctness
14Hot Partitions, Hot Keys & Skew
15Retention, Replay & Event History
16Consumer Groups & Competing Consumers
17Acknowledgements, Visibility Timeouts & Processing Leases
18Acknowledge After the Durable Side Effect
19Producer Confirms & Publish Durability
20Ambiguous Publish Outcomes & Producer Deduplication
21Idempotent Consumers: Make Redelivery Safe
22Deduplication Stores, Unique Constraints & Retention Windows
23Transactional Outbox: Database State and Event Publication as One Intent
24Inbox Pattern: Atomic Consumer Deduplication & State Change
25Change Data Capture (CDC): Reliability Between Database Log and Event Stream
26Saga Pattern: Distributed Business Transactions Without a Global Lock
27Orchestration vs Choreography
28Exactly-Once Processing: Define the Transactional Boundary
29Retry Classification: Transient, Persistent & Business Failures
30Exponential Backoff & Jitter for Consumers
31Retry Topics / Retry Queues: Keep Failure Delays Out of Hot Consumers
32Poison Messages: Detect Deterministic Consumer Failure
33Dead-Letter Queues: Quarantine, Not a Graveyard
34Safe DLQ Redrive: Repair Before Replay
35Message TTL, Expiration & Delayed Work
36Backpressure: Let Downstream Capacity Control Upstream Work
37Prefetch / Max In-Flight: Throughput vs Fairness vs Recovery
38Queue Depth vs Consumer Lag vs Oldest Message Age
39Drain Time & Recovery Capacity
40Event-Driven Autoscaling: Scale on Work, Not Only CPU
41Overload Protection: Admission Control, Quotas & Load Shedding
42Head-of-Line Blocking
43Slow Consumers & Consumer Starvation
44Consumer Rebalances, Ownership Changes & Duplicate Windows
45Request/Reply over Messaging: Correlation, Timeouts & Orphans
46Publish/Subscribe Fan-Out & Independent Consumer Failure
47Work Queue / Competing Consumer Pattern
48Event Log / Stream Pattern: Replayable State Changes
49Kafka Reliability Integration: What This Track Adds Beyond Kafka Pro
50RabbitMQ Reliability: Publisher Confirms, Manual Acks, Quorum Queues & DLX
51Amazon SQS Reliability: Visibility, Long Polling, DLQ & FIFO Message Groups
52Google Cloud Pub/Sub Reliability: Ack Deadlines, Ordering & Exactly-Once Scope
53Azure Service Bus Reliability: Peek-Lock, Sessions, DLQ & Duplicate Detection
54NATS JetStream Reliability: Streams, Consumers, Acks & Redelivery
55Choose the Messaging Platform by Semantics, Not Popularity
56Multi-Tenancy, Quotas & Noisy-Neighbor Isolation
57Authentication, Authorization, TLS & Least Privilege
58Sensitive Data, PII & Event Payload Minimization
59Auditability & Event Lineage
60Event Observability: Producer, Broker, Consumer & Business Signals
61Distributed Tracing Across Asynchronous Boundaries
62OpenTelemetry Messaging Spans, Links & Async Causality
63Structured Logging & Correlation for Event Pipelines
64SLOs for Asynchronous Systems: Freshness, Completion & Loss
65Alerting on Backlog: Page on Impact, Not Every Queue
66Capacity Planning for Event Pipelines
67Backlog Storage, Retention & Disk Risk
68High Availability & Broker Failure Domains
69Multi-Region Event Architecture: Active/Passive, Active/Active & Conflict Risk
70Disaster Recovery for Messaging: Restore the Pipeline, Not Just the Broker
71Event Replay Safety: Rebuild Derived State Without Repeating External Effects
72Backfills & Historical Reprocessing
73Stateful Stream Processing: Checkpoints, State Stores & Recovery
74Windowing, Watermarks & Late Events
75Release Engineering for Producers & Consumers
76Consumer Version Skew & Rolling Deployments
77Configuration & Secret Changes in Event Systems
78Testing Event-Driven Systems: Contracts, Integration, Replay & Failure
79Deterministic Consumer Tests with Duplicate & Out-of-Order Events
80Load & Soak Testing Event Pipelines
81Chaos & Resilience Testing for Messaging
82Event-Driven Incident Patterns: Lost, Duplicated, Delayed, Reordered & Stuck
83Incident: Queue Backlog & Consumer Lag
84Incident: Duplicate Business Side Effects
85Incident: Poison Message & Retry Storm
86Incident: Broker Healthy, Business Pipeline Broken
87Lab: Reliable Order Pipeline with Outbox, Idempotent Consumer & DLQ
88Lab: Retry Storm, Backpressure & Controlled Recovery
89Lab: Poison Message, DLQ Repair & Canary Redrive
90Lab: Consumer Lag, Autoscaling & Downstream Capacity Guardrail
91Lab: Kafka/RabbitMQ/SQS Semantics Comparison
92Lab: Regional Failure & Replay-Based Recovery
93Event-Driven Reliability Troubleshooting Playbook
94Event-Driven Command & Evidence Playbook
95Event-Driven Reliability Pro Cheatsheet

Englishবাংলা

Knowledge Hub/Event-Driven Reliability Pro/Poison Messages: Detect Deterministic Consumer Failure

Event-Driven Reliability Pro

Paid lesson · Intermediate · 36 min read

Poison Messages: Detect Deterministic Consumer Failure

Recognize messages that will never succeed without code, data or configuration change.

This lesson is locked

This lesson is part of the paid course.

View free previews

PreviousRetry Topics / Retry Queues: Keep Failure Delays Out of Hot ConsumersLocked NextDead-Letter Queues: Quarantine, Not a GraveyardLocked

Discount price

৳ 320.00৳ 120.00Save ৳ 200.00