300 points by 6 months ago flag hide 14 comments
postgres-expert-1990 6 months ago next
Fascinating read, thanks for sharing! We've been using PostgreSQL for years but haven't had to hyperscale yet. Any tips for teams just starting to explore this kind of scale?
scaler-jockey-2000 6 months ago next
Start with analyzing your write and read patterns so you can horizontally scale accordingly. Tools such as pg_stat_statements and pgtop are helpful to see what's really happening inside your system.
dba-newbie-2040 6 months ago prev next
How did you deal with the huge volume of connections that came with hyperscaling?
bigdata-dba-2020 6 months ago next
Increasing shared buffers and max_connections did wonders for our production environments. However, we also implemented a connection pooler (PgBouncer) to handle even larger loads.
database-guru-2010 6 months ago prev next
Great post! This kind of knowledge sharing and documentation is critical for the community. How did you manage hot backups when capacity expanded?
bigdata-dba-2020 6 months ago next
We utilized tools like repmgr and Patroni for hot standby servers, but we needed Kubernetes (EKS) to manage Kafka streams. We wrote Kubernetes operators for handling automatic failover and backups.
cloud-custodian-2030 6 months ago next
Interesting! I've worked with Patroni and know its potential. What factors will make you choose Kubernetes for managing databases, and what specific issues did that resolve?
data-engineer-2050 6 months ago prev next
What was your step-by-step setup for integrating PostgreSQL with Kafka, the reason behind this integration and which tools did the job?
bigdata-dba-2020 6 months ago next
We used Debezium to listen to PostgreSQL events and then Apache Kafka for data streaming. The challenge came in customizing the connector to capture only schema and table changes, reducing data in transit.
event-driven-dev-2060 6 months ago next
I know Debezium quite well, and you're right that significant customization is required, making it even more challenging when scaling. What monitoring did you implement to ensure consistency and low latency?
bigdata-dba-2020 6 months ago next
We implemented Prometheus and Grafana for metric collection and visualization. For real-time monitoring, we used Kafka's built-in consumer group monitoring and our application-level Request ID traces.
startup-advisor-2070 6 months ago prev next
Thanks for the detailed tutorial on hyperscaling PostgreSQL! With the growing need for data-intensive applications, these tips could help fellow startups optimize their own solutions.
hn-reader-2080 6 months ago next
Absolutely, it's important to learn from these experiences. Any tips for avoiding pitfalls during such a huge transition to Postgres hyperscaling?
bigdata-devops-2090 6 months ago next
Well, thorough planning and testing are essential. Conducting different failure scenarios will shed light on potential problems. Also, automating deployments, tests, and database backups is key.