Best Top 10 Things to Monitor for Amazon RDS

                                               
                                                       

Amazon's Relational Database Service (RDS) is one of the world's most popular database services, used by 47% of AWS companies according to the AWS Scorecard 2015 2nd Watch. Although media buzz tends to focus on the new Big Data and NoSQL data stores, relational databases continue to be the battleground for many websites and applications. 

Companies like Qubole and Zenefits rely on relational databases such as Postgres and MySQL to scale millions of active users daily. Amazon Web Services (AWS) made it easy to scale thousands of requests per second and terabytes of data under administration. However, tracking all the metrics of a large, complex database remains a major challenge. 

These are the key things you should monitor that can affect availability, performance, and cost Availability You should know quickly when there is a disruption, latency, or even a downward trend in your database availability.

 This can cause a problem in the application's performance and, ultimately, loss of data. 

Group integrity: 

If you have a distributed database, you should know that each instance and its group are generally in good condition. Although Amazon has the ability to track the availability of each instance, a better status indicator will indicate whether instances respond to requests in an expected and error-free time.

 Realistically, if your queries take longer than expected, you are not getting enough value from the database. Most importantly, from a product standpoint, a high latency in your queries is not only an indication of possible database integrity issues, but also a poor end-user experience for your application. Therefore, it is also important to think about availability metrics in the context of high-level strategic policies. 

Windows Maintenance: 

Databases may no longer be available or may not be upright for a variety of reasons. All RDS databases include weekly maintenance windows for patches and security updates. Although most maintenance can be completed with minimal performance impact, some may require zone failover with multiple zones. 

Even so, it is possible that an update could cause an unexpected outage or performance problem with your application. You can find details about previous updates by looking at the records in the RDS console. 

Using System Resources and Errors: 

Databases may also be unavailable because of limits on resource usage, including the file size limit. table in MySQL, the maximum number of database connections allowed per instance, and capacity constraints during periods of increased demand. You should also check the database error log in the RDS console for clues about errors internal to the database. 

Human error:

A database can also be disconnected because of an accidental change of one of the databases. members of your team. You can take a look at the CloudTrail log to audit changes made by your team through the console or API calls. A misconfigured schema or a desynchronized cluster may also make the database appear unavailable. 

Viewing your error rate after making changes to the schema or group can highlight this type of problem Action:

 Each application will achieve some sort of performance threshold as it expands. It is important to know what that limit is so that you can monitor and optimize it. All of these performance improvements rely on a robust monitoring system to identify the bottlenecks you can optimize. You should look at each of these limits continuously, because even if you are below them, you can exceed them on average during periods of explosion or peak demand 

RDS metrics:

  if you have a larger database, you should be careful about the limits that can affect your performance. RDS databases include the boundaries of RDS as a whole and of each specific database engine, such as MySQL. For example, RDS databases include limits on the maximum number of database connections allowed per instance and the maximum table size.

 To optimize your performance, consider whether your database is heavier in readings (selection) or writes (insert, update, delete). If readings abound, you can take advantage of indexes, replica readings, materialized views, or caches up. 

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