Since the 21c was public available the Data Guard per Pluggable Database – DG PDB – was intended to be there, but Oracle needed more time to make things work and some weeks ago released the feature with the 21.7 version. Here in this post, I will show to configure it and also how to troubleshoot, and the pitfalls of using it. As usual, all the steps, logs, and outputs are covered here and I hope that it helps you understand the whole DG PDB process.
The environment that I am using here is:
Two databases running in RAC mode (two nodes in each cluster).
ASM: same DATA and RECO diskgroups names in each cluster.
About the databases I have:
ORADBDC1, that have the pdb PDBDC1. So, they represent the DC1.
ORADBDC2, that have the pdb PDBDC2. So, they represent the DC2.
Each of these clusters is in a separate environment, this means that both are primary databases inside each datacenter. So, they have no DG configured between them.
The main target for this post is to have the pdb from DC2 protected by the ORADBDC1 at the DC1. I used RAC and ASM because this is usually the normal configuration for the MAA (following the recommended architectures baseline) when using DG. This increases the protection and reduces the SPOF of your environment.
The idea of DG PDB differs a little from what we see commonly for Data Guard, here each container have own life. This means that only the pdb is protected and not the entire cdb. This puts the DG PDB close to Cloud than On-Prem because it fit perfectly at the OCI structure since you can create your pdb in one region and choose another region to protect it. And even closer if you think for Autonomous Database that your ownership is pdb only. I will not say that is good or not, but is linked to how Oracle works with OCI. Personally, I prefer to have normal DG configured to protect my databases and I choose where I want to open my pdb (maybe they add this feature in the future).
My first post of 2021 is just Thank You. Thanks for reading my posts and following me on my social media (Twitter/LinkedIn/Blog). Thanks for all of the 41.000 site access during the last year and for all that attended my sessions at the online events. I hope that was possible to help you with something about Oracle.
When you change the parameters for the database is possible to specify the db_unique_name and allow more control where you want to apply/use it. This is very useful to limit the scope, but you need to be aware of some collateral effects. Even not present at the official doc, you can use it. But check here some details that you need to take care of.
Understand metrics for Exadata Storage Server is important to understand how all the software features are being used and all the details from that. Here I will discuss one case where the FC_IO_BY_R_SEC metric can show not precise values. And I will discuss one missing metric that can save a lot.
If you have doubts about metrics, you can check my post about metrics, it was an introduction, but cover some aspects of how to read and use it. You can check my other post where I show how to use metric DB_FC_IO_BY_SEC to identify database problems that can be hidden when checking only from the database side.
Metrics for Exadata deliver to you one way to deeply see, and understand, what it is happening for Exadata Storage Server and Exadata Software. Understand it is fundamental to identify and solve problems that can be hidden (or even unsee) from the database side. In this post, I will explain details about these metrics and what you can do using them.
My last article about Exadata Storage Server metrics was about one example of how to use them to identify problems that do not appear in the database side. In that post, I showed how I used the metric DB_FC_IO_BY_SEC to identify bad queries.
The point for Exadata (that I made in that article), is that most of the time, Exadata is so powerful that bad statements are handled without a problem because of the features that exist (flashcache, smartio, and others). But another point is that usually, Exadata is a high consolidated environment, where you “consolidate” a lot of databases and it is normal that some of them have different workloads and needs. Using metrics can help you to do a fine tune of your environment, but besides that, it delivers to you one way to check and control everything that’s happening.
In this post, I will not explain each metric one by one, but guide you to understand metrics and some interesting and important details about them.
ZDLRA can be used from a small single database environment to big environments where you need protection in more than one site at the same time. At every level, you can use different features of ZDLRA to provide desirable protection. Here I will show how to reach zero RPO for both primary and standby databases. All the steps, doc, and tech parts are covered.
You can check the examples the reference for every scenario int these two papers from the Oracle MAA team: MAA Overview On-Premises and Oracle MAA Reference Architectures. They provide good information on how to prepare to reduce RPO and improve RTO. In resume, the focus is the same, reduce the downtime and data loss in case of a catastrophe (zero RPO, and zero RPO).
If you looked both papers before, you saw that to provide good protection is desirable to have an additional site to, at least, send the backups. And if you go higher, for GOLD and PLATINUM environments, you start to have multiple sites synced with data guard. These Critical/Mission-critical environments need to be protected for every kind of catastrophic failure, from disk until complete site outage (some need to follow specific law’s requirements, bank as an example).
And the focus of this post is these big environments. I will show you how to use ZDLRA to protect both sites, reaching zero RPO even for standby databases. And doing that, you can survive for a catastrophic outage (like entire datacenter failure) and still have zero RPO. Going further, you can even have zero RPO if you lose completely on site when using real-time redo for ZDLRA, and this is not written in the docs by the way.
The idea for Real-Time Redo is to reach zero RPO for every kind of database and this includes ones with and without DG. As you can see in my last post, where I showed how to configure Real-Time Redo for one database, some little steps need to be executed and they are pretty similar than a remote destination for archivelog for DG.
Virtual Full Backup probably is the most know feature of Oracle Zero Data Loss Recovery Appliance (ZDLRA) and you can check here how it works. In this post I will show how virtual full backup works internally and integrate INDEX_BACKUP task with tables like PLANS, PLAN_DETAILS, CHUNKS, and BLOCKS.
The base for this article is virtual full backup and incremental forever strategy. I explained both at “ZDLRA, Virtual Full Backup and Incremental Forever” and I included hot it’s work integrated with rman backup. Basically, after an initial backup level 0, you execute just level 1 backups and ZDLRA generated a virtual backup level 0. But here, in this post, I will show you how it works in some internal details.
For ZDLRA, the task type INDEX_BACKUP it is important (if it is not the most) because it is responsible to create the virtual full backup. This task runs for every backup that you ingest at ZDLRA and here, I will show with more details what occurs at ZDLRA: internals steps, phases, and tables involved.
As you saw in my previous post, ZDLRA opens every backup that you sent and read every block of it to generate one new virtual full backup. And this backup is validated block a block (physically and logically) against corruption. It differs from a snapshot because it is content-aware (in this case it is proprietary Oracle datafile blocks inside another proprietary Oracle rman block) and Oracle it is the only that can do this guaranteeing that result is valid.