Ways To Overcome The Obstacles Associated With SMS Messaging Load Testing At 10 Million Sends

Overview  

Communication as an operation comes hand-in-hand with load and stress testing. Not long ago, I had the honor of executing an SMS use case of sending 10 million messages in SMS: performing sending it in mass. Obviously, every test was beyond the bare minimum. Dominant successes needed to be achieved on benchmarks like performance, scalability, and resilience. In this blog post, I will outline the obstacles faced during the high throughput SMS tests and explain the ways these challenges were met on a multidisciplinary planning, and tooling basis with coordination and foundational frameworks. 

Challenge #1 Infrastructure bottlenecks

Challenge: 

Messaging 10M Concurrent SMS Messages comes with great database requisites, throughput limits, computer requisites, as well as bandwidth. Certain blocks/environments like our SMS messaging test environment were – and to some degree still are: Not set for this framework, causing regular timeouts and failures in services. 

Result: 

Increased the scope of monitoring the instance as a result of working together with Devops to enforce Auto-scaling groups and Load balanced instances. 

Challenge #2: Queue & Throughput Limitations

Problem:  

 The messaging system depended on message queues (like RabbitMQ). Each of these queues reached their individual throughput ceilings which created performance lags in message processing upto 4:30 hours for 10 million SMS at the time interval of 10 to 30 minutes, and it reaches the CPU Usage of 100%.

Solution:  

•  Implemented batch message publishing for more efficient queue operations.  
•  Prefetch limits, acknowledgment methods, and consumer scaling were optimized within the queue configurations.
• Choke points were actively identified using Prometheus + Grafana alongside real-time monitoring to expedite the flow of systems under strain.  

Challenge #3: Outbox Timeout at Scale

Problem:  

 During the test, once I scaled up to 10 million contacts, the outbox service became increasingly unresponsive and started returning timeout errors. Messages encountered a bottleneck in the system and were unable to be transitioned to the next processing stage.  

Solution:  

• Developments of this swirling problem were attributed on-the-spot to the message dispatching layer alongside DevOps which designated their control sliders for the outbox servicing system.
• Set adjusted timeouts on other dependent services while also increasing overall box service throughput.  
• The system metrics and logs were actively monitored post-tuning to ensure the desired velocity of flow was attained and thus validate the outcome.

Challenge #4: Test Data Management 

Problem:

 Duplicates were inefficiently managing and contending with the test data for 10 million unique SMS messages. Overlapping numbers or malformed payloads could skew results. 

Solution:

• Used Python scripts to automate the creation of unique, valid phone numbers alongside distinct message templates. 
• Before dispatch, monitored payload integrity with purpose built data validators. 

Challenge #5: Performance Metrics Monitoring 

Problem:

 Collecting meaningful parameters and metrics (latency, delivery rate, failure rate) with such a massive volume was disorderly at first. 

Solution:

•  Applied APM integration for backend and message path tracing with New Relic, DataDog and other similar tools. 
• Set the following key SLAs: end-to-end latency, SMS delivery success rate, and retry rate. 
• With custom dashboards, filtered non-relevant metrics and visualized them in near real time.

Challenge #6: Failure Recovery and Retry Mechanisms

Problem: 

The primary reason was a great deal of temporary network malfunctions and external SMS gateway problems.

Solution:

Challenge #7: Cross-Team Collaboration

Problem:

The scope of such a test was large scale, capturing the synergy between multiple participants at QA, DevOps, Backend.

Solution:

• Developed war rooms and live dashboards for the duration of the testing window.
• Designed ACTs for resolution tracking, escalation, and rapid issue resolution.
• Compiled logs of timestamped root causes for all issues captured for post-mortem review.
• Verified fundamental initial pre-test strategy derived observations. 
• Planning determines everything – environment readiness, data strategy, and coordination need to be locked before the test.

Conclusion 

Quality Assurance (QA) has so far remained a one shot deal with me for testing 10 million SMS messages, honing and blending all the skills together in single unit tests. It never failed to challenge me; rather, it was deeply gratifying. This taught us a myriad of lessons about system scalability, fault tolerance, and teamwork. In my experience, these multifaceted challenges remind me how critical QA is in a business and its sophisticated technologies. It also reminds us about the importance of performance surpassing targets regarding said objectives. As gatekeepers of robust systems, we uncover shortcomings through agile drills.