Summary:
MoveInSync’s workplace module was built with passion and grit. We dedicated ourselves to developing the product despite the chaos of the pandemic.
However, as we grew and onboarded more clients, the exponential increase in traffic led to latency in loading dashboards.
Our team’s relentless pursuit of improving the module has led to a significant improvement in our product’s performance. We have achieved a remarkable 97% faster load times, a testament to our dedication and ingenuity.
Read on to find out how we achieved this feat!
Article:
The MoveInSync Workplace module, a brainchild born in the midst of the pandemic’s chaos, has grown from strength to strength. Our team’s dedication and hard work have transformed it into the robust and mature product it is today.
That said, it has gone through its fair share of challenges.
One of the most pressing challenges was the scalability of our dashboards. As our client base expanded, we experienced a significant surge in traffic. This led to a noticeable increase in dashboard loading time, adversely affecting the user experience.
Workplace dashboards would have data that needed to be queried instantly, often spanning data from the previous 7 days, 1 month, and 3 months. Populating such large amounts of booking-related data had a knock-on effect. It affected the entire system, increasing the load on several other services.
The tech team set out to solve this conundrum. Various potential solutions were considered –
Microstream frameworks, Kafka streams for real-time aggregation, and ElasticSearch. After comparing the pros and cons listed below, we made a conclusive decision.
| Potential Solution | Pros | Cons |
| Microstreams | - Scalability
- Isolation
- Async development
- Fault isolation
| - Complexity
- Increased overhead
- Inconsistencies
- Deployments
- Monitoring & Debugging
|
| Kafka streams | - Scalability
- Real-time processing
- High responsiveness, low latency
- Fault tolerance
- High integrity
| - High learning curve
- Operational complexity
- High resource requirements
- Complex state management
- High coupling and dependency with Apache
|
| Elastic | - Performance
- Distributed architecture
- Real-time Data analysis
- Flexible Data modeling and querying
| - Resource intensive
- Performance tradeoff over data consistency
- Indexing overhead
|
After thoroughly considering the pros and cons, we decided to proceed with ElasticSearch.
With the help of ElasticSearch, a whole new “Inventory” service was written, and several parent services began using it. As we started load testing this new service, the results were precise.
Ladies and gentlemen, we had a game-changer!
Below is the response time of the data loading times before and after the implementation of the Inventory Service using ElasticSearch.
In conclusion, by leveraging ElasticSearch, MoveInSync has significantly enhanced its Workplace module’s performance, achieving 97% faster dashboard load times.
This milestone reflects our unwavering commitment to innovation and efficiency. Our journey toward even greater optimization continues, as we strive to deliver the best user experience possible.
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