Trying to gauge the workload of a database on any given day can pose quite a challenge. A straightforward question supported by basic Database Activity Monitoring might not yield an insightful answer if it’s stripped of context, cluttered with arbitrary numbers, and missing crucial details.
So, what’s the right way to address this query?
It may seem that the companies entangled in the web of Oracle and its ecosystem have a limited set of options when it comes to performance tuning. It’s either – pay for extra functionalities and navigate Oracle’s complex licensing, risking non-compliance penalties. This often leads to a conservative approach to optimization, stifling innovation due to the fear of overstepping licensing terms.
But do we always have to go the hard way?
There’s a much simpler route that doesn’t involve trembling with fear of clicking the wrong thing. That’s what we will be talking about today.
While big players have little to no choice but to go for the cloud, some businesses might weigh the choice between traditional on-premises setups and cloud solutions. On one hand scalability, flexibility, and cost savings that traditional databases struggle to match. The ability to scale resources up or down on demand, pay only for what you use, and offload maintenance and security tasks to experienced providers presents a compelling case for moving to the cloud.
On the other hand, traditional on-premises databases offer a level of control and security that some businesses are reluctant to use. The physical control over the database infrastructure can provide a sense of security, particularly for organizations with highly sensitive data or stringent regulatory compliance requirements. Additionally, for companies with stable data loads that don’t require frequent scaling, the initial investment in on-premises hardware might not seem as daunting.
The only thing more abundant than coffee in a developer’s life is, well, technical documentation. It seems simple enough – you have a problem, you go through a few pages, and get your answer, that simple. Is it, though? Anyone who’s ever tumbled down the rabbit hole of Stack Overflow threads at 2 AM or squinted at API docs with the growing suspicion they’re written in an ancient, forgotten dialect will tell you: not quite.
Tutorials skip crucial steps, reference guides resemble dense textbooks, and help forums, while helpful, can send you on a wild goose chase for that one golden nugget of information. But there’s a light in the tunnel, and we’re here to help you find it.
Where “OR” and “IS NULL” condition frolic unchecked, queries often find themselves stumbling down the performance rabbit hole—a place where CPU cycles burn faster than a comet tail and I/O operations multiply with the fervor of rabbits in spring.
A database deadlock occurs when two or more transactions in a database system hold locks on resources the others need. Each transaction waits for the others to release their locks, and just like two drivers who are not sure who has the right of way, none can proceed.
It would be lovely to be able to enumerate the causes of a database deadlock and address all of them. Sadly, it’s way too complex. It can be said, though, that a database deadlock is most likely to stem from poor application design, lack of proper transaction management, or the inevitable complexity of highly concurrent systems.