What are the most common DBMS configuration mistakes?

Know your application: Understand the data volume, data structure, and expected workload for your application Data model: Opt for the most suitable data structure, including options like relational, document-based, key-value, graph Scalability: Determine whether your application requires horizontal scalability or vertical scalability Community and Support: Check the availability of a supportive community and vendor support for the chosen database

Firstly you need to understand where the database tier will be hosted - on-prem or in the cloud. Then you need to understand which database type will fit application needs better - relational (OLTP/OLAP), document-based, key-value, time-series or graph. You need to ensure which licensing/resource cost is appropriate for your budget maybe your choice will be only open-source DBMS. Determine which DBs are business critical and estimate HA/DR requirements and ensure that chosen DBMS can provide such functionality.

What to consider? I would start with a few questions: -Are your database Mission Critical? -Structured Data? -Hosting: where the data will reside? -The data: from where it's coming? Another Cloud or OnPrem? -Usability, CLI, APIs, Web Console, Dashboards -Query Accelerators -Built-in Security options -Scalability, DR, HA -Cost$ -Online Updates -Ease of Integration -Support? Community?

Are you sure that you really have a backup? Do you know how many time to recover your environment? Are you mirrroring data and apps? Or only data? Are your data distributed in different Data Centers? Or even Devices? -I would consider both Recory Time & Recovery Point Objective -Periodic Recovery Tests, Simulations to ensure backup restore process enhancements -Backup storage location - at least 3 if we talk about Mission Critical Systems -Ensure Backups are all valid - incremental pieces validation -Maybe a mix with a stand-by strategy... would be great.

Inadequate security settings in a DBMS can cause data breaches, leading to stolen or altered information. Data loss, compliance violations, and legal repercussions can follow, impacting reputation and finances. Operations can be disrupted, and intellectual property might be stolen. Identity theft, fraud, and reputational damage are further risks. Implementing robust security measures like strong authentication, encryption, and regular audits is crucial to mitigate these threats.

IDC has a survey that says that 80% of security problems have started in lack of knowledge or wrong setup -Only Federated users allowed to connect in database -Only receive and answer requests coming from allowed CIDRs -NextGEN firewall attached to the db's virtual network -Allow only specific ports and protocols in security lists or NSGs -Avoid overprivileged users in DB -Discover sensitive data -Data Masking

Performance tuning involves optimizing DBMS settings like memory allocation, disk space, indexes, and query execution for efficient data operations. However, many users overlook or misconfigure these settings, leading to slow response times, resource wastage, or errors. It's crucial to tailor tuning based on workload and DBMS features, avoiding pitfalls like excessive memory use, redundant indexes, or inefficient queries. Evaluating and adjusting tuning parameters according to performance goals is key for optimal DBMS performance.

If you are talking about a modern database at some cloud, maybe we will have handy: Auto-Index Auto-Gather Stats Sharding In-Memory query accelerators ML to understand eventual processing peaks at this specific workload A few points to consider also, independent if this is a OnPrem or at Cloud database: -Partitioning (sometimes by range of time is better) -Avoid blocking sessions. How? -Tune the queries's execution plan -Consider change cache related initialization db parameters -Linux Hugepages? Semaphores?

Properly documenting and maintaining a DBMS configuration is often overlooked but crucial. Without it, tracking changes, resolving errors, and ensuring data quality become challenging. Neglecting documentation or maintenance, like not recording settings or skipping backups, can cause confusion, miscommunication, and data issues. Regular, accurate documentation and maintenance are essential to prevent errors, data loss, and maintain a consistent, reliable database environment.

Maintaining thorough documentation for every task undertaken not only benefits the organization but also fosters personal and professional growth for a DBA. In a past workplace, we established a practice where each DBA assumed the responsibility of delivering comprehensive Root Cause Analyses (RCAs) for critical incidents. These RCAs were meticulously detailed, outlining the steps taken and the controls implemented. They were made accessible to all DBAs through a centralized platform. I still follow that for myself to maintain record of the tasks I've undertaken, the challenges I've encountered, and the effective solutions I've implemented. It's also needed much in Knowledge Transfer if you are planning to switch for better opportunities.

In my opinion the number one mistake is to use the same physical/logical path for all type of files of the RDBMS. In the past this mistake was a major reason for regressed performance but these days with the use of storage clusters the problem doesn't rely on performance but in administration. To be able to easily manage disk usage, restore/move databases and for the isolation of each RDBMS part, you should use different logical path for each of one of them. For example you should better have different path for OS, different for system databases, different for tempdb, different for user databases, different for log files, different for backups etc.

Continuous education is vital for DBAs to stay relevant and proficient. With the ever-evolving landscape of DBMS products and cloud offerings, ongoing learning ensures familiarity with new features, enhancements, and best practices. Adapting to advancements in technology helps DBAs optimize database performance, implement efficient solutions, and address emerging challenges. It also enables them to leverage the capabilities of different DBMS products and cloud services, making informed decisions based on specific business needs. Embracing continuous education fosters expertise, enhances problem-solving skills, and empowers DBAs to provide valuable contributions in an ever-changing data environment.

Perhaps Data location versus latency is the very first point to start thinking how to manage, store and distribute your data.