Data Cloud & AI Summit Round-Up: What’s New In Cloud SQL


ICYMI: Google Cloud just hosted the third annual Data Cloud & AI Summit, where we unveiled new product innovations to help you take advantage of open data cloud solutions, while embracing a vibrant partner ecosystem. In this round-up, we’re highlighting some of the most exciting Cloud SQL launches you might have missed.

Cloud SQL is a fully-managed relational database service for MySQL, PostgreSQL, and SQL Server, built on trusted Google Cloud infrastructure and integrated with the best of Cloud. It makes it easier than ever to get your databases up and running with built-in enterprise capabilities your workloads need, such as; high availability, automated maintenance, data protection, and security. In an IDC survey, Cloud SQL customers achieved an average three-year ROI of 246% as a result of the value and efficiencies Cloud SQL delivers as a managed service. 

Cloud SQL’s newest launches enhance an integrated platform that works for you, offering new configuration flags so you have flexibility for the features you need, building in data protection and security by default, and continuously delivering new insights that make sure you’re getting the most out of your data. Let’s jump into what’s new!

Compatibility with commonly —used relational database engines

Cloud SQL enables you to use the same MySQL, PostgreSQL, and SQL Server capabilities you’re already leveraging on-premises or on self-managed cloud infrastructure. Here are recent launches that let you take advantage of deeper database-specific features:

  • Cloud SQL for MySQL launched support for more than 100 additional MySQL flags, including:
    • innodb_max_dirty_pages_pct, which helps you to optimize performance by controlling disk I/O related to dirty page flushing
    • connection_timeout, which allows you to control the probability of clients losing connections
    • innodb_open_files, which defines how many files innodb can have open at one time and can help to optimize performance
  • You can use linked servers with Cloud SQL for SQL Server, making it easy to access data stored on remote SQL Server instances.
  • Migrating to Cloud SQL for SQL Server is faster than ever, with support for SQL Server multi-file backup imports which can substantially reduce downtime during migration.
  • To better serve your reporting needs, you can right-size read replicas for Cloud SQL for PostgreSQL by creating replicas with less CPU or memory than the primary.
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Built-in protection for your workloads

Cloud SQL provides enhanced data protection and security capabilities so you can meet your organization’s requirements across the spectrum of your workloads’ needs.

  • Cloud SQL supports point-in-time-recovery (PITR) for SQL Server, letting you recover from accidental data deletion by restoring a single database or your whole instance to a previous time. All three database engines now support PITR.
  • Cloud SQL for PostgreSQL stores transaction logs in Google Cloud Storage for instances that newly enable PITR at no additional cost, which helps ensure predictable storage consumption on disk.
  • Automatic IAM database authentication for MySQL lets you hand off requesting and managing access tokens to an intermediary Cloud SQL connector, such as the Cloud SQL Auth proxy.
  • As part of Cloud SQL’s integration with the Security Command Center for proactive detection and prevention, we launched a new Event Threat Detection rule that alerts you when an admin database user writes to user tables.

End-to-end integration with other Google Cloud services

Your applications are more powerful when you use all of the rich capabilities Google Cloud offers, so Cloud SQL makes it easy for you to integrate with other services so you can build high scale, data-driven applications:

  • With federated queries from BigQuery, you can quickly analyze operational data stored in Cloud SQL without creating data pipelines. You can now perform those federated queries to private IP-enabled Cloud SQL instances — ensuring that you can keep analytical query traffic within Google Cloud perimeters.
  • If you’re using Cloud SQL with GKE, connecting your workloads to Cloud SQL is easier than ever with the Cloud SQL Proxy Operator (available in public preview) — an open-source Kubernetes operator that automates connecting from a GKE cluster to Cloud SQL databases.
  • Network Analyzer can help you troubleshoot connectivity issues with your Cloud SQL instance with zero setup required. The alerts recommend steps to resolve the identified issues.
  • If you’re using Managed Active Directory for authentication to your Cloud SQL for SQL Server instance, the Active Directory Diagnosis tool can help you troubleshoot your Active Directory integration between an on-premises Active Directory domain and Managed AD.
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Intelligent observability to optimize your databases

Cloud SQL makes it easy to understand how your databases are performing. We’ve built in recommendations about steps you can take to better serve your application workloads, and give detailed metrics to understand your instance’s state:

  • Underprovisioned instance recommenders, in Preview, help you proactively identify Cloud SQL instances that have high CPU or memory utilization so you can better size the instances for your workloads’ demands.
  • Cloud SQL for SQL Server supports 38 additional metrics that help you monitor the health of your instance and bring new observability capabilities for identifying performance issues and resource bottlenecks. For example, you can monitor SQL Server locks with three new metrics: ‘deadlock_count’, ‘lock_wait_count’, and ‘lock_wait_time’.

More than 90% of Google Cloud’s top 100 customers use Cloud SQL. Want to learn more? Watch the Cloud SQL in a minute video, and then start your journey with a Cloud SQL free trial.

By: Sujatha Mandava (Director, Product Management) and Isabella Lubin (Senior Product Manager)
Originally published at: Google Cloud Blog

Source: Cyberpogo

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