Tech Stack

Thanks to a state-of-the-art tech stack – mainly written in Golang, TypeScript, and Scala – which is deployed by Gitlab CI to modern container orchestration systems, our event-driven backend platform handles over few billion requests and/or events daily.
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Rest API
1 Billion Requests per Day
Our mobile SDK is integrated into publisher apps and communicates to our backend via Rest. We then pull our data from backend APIs to serve insights into our dashboards.
AWS Load Balancer
45 LBs & 295 TGs
The Load Balancers distribute all incoming requests to the right target application in different availability zones.
CONTAINER ORCHESTRATION SYSTEM
AWS Elastic Container Service
Over 500 Containers Running
ECS’s simplicity and stability allow us to reduce management effort and through our use of Spot Instances we are able to keep our AWS serve costs low.
Auto Scaled Docker Containers
480k Lines of Code
Our application is built in Golang and split into over 120 independent microservices.
EVENT LAYER
AWS SNS/SQS
Over 200M Events per Day
We believe in event-driven architecture, with our main event bus system being SNS+SQS.
AWS DynamoDB Streams
417M Processed Items per Day
Allows for effortless generation of events based on DynamoDB database activity.
AWS Kinesis
600 GB Processed Data per Day
Similar to Kafka, we use a managed large-scale event streaming bus.
AWS CloudFront
60 TB per Month
The AWS CDN provides high global availability, which gives us the opportunity to serve videos and images to users.
Logging and Metrics Layer
ELK Stack
300M Logs per Day
The self-hosted Elasticsearch allows us to process, store, and search billions of log events daily.
Fluentbit
Cheaper than CWL
To remain cost efficient we ship our logs from Docker to Elasticsearch.
AWS Cloudwatch
541 Different Metrics
Responsible for our infrastructure, monitoring, and alarms to be fast and efficient.
Grafana
Written in Go & Typescript
Advanced visualization tool to analyse our system performance.
Sentry
1102 solved bugs
Comprehensive application error tracking that informs our team of any challenges the Go Microservices may encounter.
Squadcast
35 New Alarms in 2021
Our core incident management tool that prevents us from missing outages or degradations of service.
Database Layer
AWS Elasticache Redis
Over 210M Queries per Day
Used for caching and performance boosts.
AWS DynamoDB
150 Tables in Use
Our central data store that is fast, reliable, and scales automatically.
AWS Redshift
500 GB Aggregated Data
Powers our statistics and analytics dashboards.
Big Data
Data Lake Pipeline
AWS Kinesis
5TB of Data per Day
Processes every possible amount of data and throughput in real-time.
AWS Firehose
6 TB Logs to s3 per Day
Firehose makes it possible to write this data in optimal size and format (parquet) for querying.
AWS Lambda
81 Lambda Functions
Connected to DynamoDB streams, captures table activity and sends it to Kinesis.
AWS Glue
140 Tables to Fill
Glue is the backbone of the pipeline. It holds schema and table information, which is used for both processing and querying.
Data Science
AWS EMR
100 CPUs in Use
Gives our business the ability to transform and analyze our data from the Datalake into unique and valuable insights that otherwise would not be possible.
Spark MLlib
>400 T ML Predictions per Day
Used to develop machine learning models and algorithms to scale our business’ performance.
AWS Athena
>88k Generated Queries
Our serverless solution to querying the Datalake through SQL in seconds.
Deep Storage
AWS S3
100 TB Data
Storage for both our Datalake and additional static content.
Rest API
1 Billion Requests per Day
Our mobile SDK is integrated into publisher apps and communicates to our backend via Rest. We then pull our data from backend APIs to serve insights into our dashboards.
AWS Load Balancer
45 LBs & 295 TGs
The Load Balancers distribute all incoming requests to the right target application in different availability zones.
AWS CloudFront
60 TB per Month
The AWS CDN provides high global availability, which gives us the opportunity to serve videos and images to users.
CONTAINER ORCHESTRATION SYSTEM
AWS Elastic Container Service
Over 500 Containers Running
ECS’s simplicity and stability allow us to reduce management effort and through our use of Spot Instances we are able to keep our AWS serve costs low.
Auto Scaled Docker Containers
480k Lines of Code
Our application is built in Golang and split into over 120 independent microservices.
Logging and Metrics Layer
ELK Stack
300M Logs per Day
The self-hosted Elasticsearch allows us to process, store, and search billions of log events daily.
Fluentbit
Cheaper than CWL
To remain cost efficient we ship our logs from Docker to Elasticsearch.
AWS Cloudwatch
541 Different Metrics
Responsible for our infrastructure, monitoring, and alarms to be fast and efficient.
Grafana
Written in Go & Typescript
Advanced visualization tool to analyse our system performance.
Sentry
1102 solved bugs
Comprehensive application error tracking that informs our team of any challenges the Go Microservices may encounter.
Squadcast
35 New Alarms in 2021
Our core incident management tool that prevents us from missing outages or degradations of service.
EVENT LAYER
AWS SNS/SQS
Over 200M Events per Day
We believe in event-driven architecture, with our main event bus system being SNS+SQS.
AWS DynamoDB Streams
417M Processed Items per Day
Allows for effortless generation of events based on DynamoDB database activity.
AWS Kinesis
600 GB Processed Data per Day
Similar to Kafka, we use a managed large-scale event streaming bus.
Big Data
Data Lake Pipeline
AWS Kinesis
5TB of Data per Day
Processes every possible amount of data and throughput in real-time.
AWS Firehose
6 TB Logs to s3 per Day
Firehose makes it possible to write this data in optimal size and format (parquet) for querying.
AWS Lambda
81 Lambda Functions
Connected to DynamoDB streams, captures table activity and sends it to Kinesis.
AWS Glue
140 Tables to Fill
Glue is the backbone of the pipeline. It holds schema and table information, which is used for both processing and querying.
Data Science
AWS EMR
100 CPUs in Use
Gives our business the ability to transform and analyze our data from the Datalake into unique and valuable insights that otherwise would not be possible.
Spark MLlib
>400 T ML Predictions per Day
Used to develop machine learning models and algorithms to scale our business’ performance.
AWS Athena
>88k Generated Queries
Our serverless solution to querying the Datalake through SQL in seconds.
Deep Storage
AWS S3
100 TB Data
Storage for both our Datalake and additional static content.
Database Layer
AWS Elasticache Redis
Over 210M Queries per Day
Used for caching and performance boosts.
AWS DynamoDB
150 Tables in Use
Our central data store that is fast, reliable, and scales automatically.
AWS Redshift
500 GB Aggregated Data
Powers our statistics and analytics dashboards.

Interested in Our Tech Stack?

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