In a previous blog post, we talked about Amazon Relational Database Service (RDS). RDS is one of the most popular cloud-based database services today and extensively used by Amazon Web Services (AWS) customers for its ease of use, cost-effectiveness and simple administration.

DevOps is no longer just about breaking the silo between developers and operations. That’s why every manual operation in your delivery pipeline needs to be evaluated to determine if it can be automated. Database changes are indeed a tedious process and therefore deserve to be considered in your DevOps implementation.

Oracle Database has long been a mainstay of the business world. Companies use it to handle data sets backing a wide variety of complex applications, including data warehouses or OLTP systems. Oracle Database includes enterprise-friendly features that emphasize scalability, advanced partitioning, and optimized availability of data across a large, potentially disparate infrastructure, as well as real-time backup and recovery tools.

Once your Rails app begins seeing consistent traffic, you're bound to have slow SQL queries. While PostgreSQL and MySQL can log slow queries, it's difficult to gleam actionable information from this raw stream. The slow query logs lack application context: where's the LOC generating the query? Is this slow all of the time, or just some of the time? Which controller-action or background job is the caller? Enter Scout.

The Django ORM makes it easy to fetch data, but there's a downside: it's easy to write inefficient queries as the number of records in your database grows. One area where the ease of writing queries can bite is you is with N+1 queries. Expensive N+1 queries go undiscovered in small development databases. Finding expensive N+1 queries is an area where Scout is particularly helpful.

We already wrote about monitoring posgresql queries, at the time we thought that we completely understood how PostgreSQL works with various server resources. Working regularly with the statistics of PostgreSQL queries, we noticed some anomalies and decided to dig a bit deeper for better understanding. Through this process, we found that while the behavior of postreSQL is kind of strange at first glance (or at least very peculiar), the clarity of its source code is quite admirable.

In our previous posts, I showed you how to copy your DB and Aurora snapshots to ensure they are preserved beyond the lifetime of your RDS instance. However, those copies were simply second copies in the same region as the original. In this post, I’ll show you how to copy your RDS snapshots to a second region for extra protection. Please note that I will restrict this post to unencrypted snapshots. Copying encrypted snapshots is more involved, so I’ll show that in a separate post.

RDS snapshots can be unencrypted or they can be encrypted at rest. Today, best practice is to use encryption-at-rest on your RDS instances and clusters, and to encrypt your RDS snapshots. When you create an RDS snapshot from an RDS instance or cluster, the resulting snapshot will be encrypted if the source instance or cluster is encrypted. But if the source is not encrypted, then your RDS snapshot is not encrypted. When you create an RDS snapshot, you are not given the option to encrypt it.

RDS DB snapshots are snapshots created from Amazon RDS DB instances. Those being MySQL, PostgreSQL, MariaDB, Oracle, and Microsoft SQL Server. Amazon Aurora also has snapshots, however, those are considered “cluster snapshots” and are handled differently.