Ibrar Ahmed

Disks fail, RAM runs short, software breaks, and human error strikes, and data loss follows fast. This talk presents a direct recovery path built on concrete steps used in production: detect corruption through log checks and checksum validation, stop the service to contain further damage, restore from backups that pass verification, use point in time recovery to reach a clean state, extract readable tables when backups fall short, keep pg_resetwal as a last resort when no clean recovery remains, and strengthen the cluster with routine checksums, tested backups, WAL archiving, and replicas that support failover. The session focuses on reliable commands, clear failure patterns, and practical actions applied without guesswork.

PostgreSQL is one of the leading open-source databases. Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. Nowadays, production systems have quite expensive machines, which require extra configuration for PostgreSQL. In this talk, users will see how to configure PostgreSQL for a Read/Write/Read-Write intensive load. This talk will explain every important configuration parameter with real-time examples.

Artificial intelligence, machine learning, and deep learning are intertwined capabilities that attempt to solve problems that defy traditional computational solutions --- problems including fraud detection, voice recognition, and search result recommendations. While they elude simple computation, they are computationally expensive, involving the calculation of perhaps millions of probabilities and weights. These computations can be done outside the database, but there are specific advantages of doing machine learning inside it, close to where the data is stored.