Cloud DBA and Management: What an Expert Needs to Know
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What does a cloud computing expert need to know? This is the last of a three part guide to interviewing for a cloud operations position. You can find them here – part one Operations Interviewand part two Deployment Interview.
Here’s my guide to do just that.
1.Database administration experience
Although in some shops the DBA role is a completely separate one, there are many others where the Linux and Operations teams manage these services as well. We do have a some other material Oracle DBA Interview questions and MySQL DBA Interview Guide. Here’s a taste of what to expect.
o What is RAID? Which type is best?
RAID is a way to share a whole bunch of disks on one server. Databases like Oracle or MySQL do a lot of writing and reading from disk. If there are more disks sharing this work, it’s like you have more waiters in your restaurant. Faster serivce.
Although some folks still hang onto RAID 5 as an option, it’s generally a very bad one. It has a serious write penalty because of parity checking it must perform. Most databases do a lot of writing, even when user transactions are not doing INSERT or UPDATE. What’s more if a disk fails, RAID 5 although technically online, will be so slow as to be effectively unusable while the long slow rebuild happens.
What’s the answer then? RAID 10! It mirrors each volume, and then stripes across those mirrored sets. Fast I/O, fast recovery. Done & done.
o What are the tradeoffs with more indexes versus fewer?
In all relational databases, you build indexes on data. Indexes are just like the ones you think of in the yellow pages, phonebooks of yore. An index on first name means you can look up Obama by Barack as well. Index on street addresses means you can lookup on the White House. So the more indexes you have, the more different ways you can search for & fetch what you want.
On the other hand the penalty here, is that whenever you add new data & records to this database, all those indexes must be updated. That’s overhead, which slows down writes.
So the tradeoff is more indexes – faster fetching, slower writing. Fewer indexes slower fetching, faster writing.
o What do NoSQL databases eliminate? How do they achieve great speed?
There are quite a few different types of NoSQL databases. So I’m generalizing quite a lot here. One thing NoSQL databases eliminate is the ability to JOIN data across different columns. By removing this great feature of relational databases, they dramatically simplify the underlying implementation. No free lunch!
What else? Many of these databases cut corners on what’s called durability. What is durability? Imagine you are in a lecture hall and bring your notebook or are waiting tables, and taking orders. It might be quicker to do so without writing things down. You keep it all in your head. Great, but what if you forget something? You have to go ask for the order again! It may be faster, but more prone to error. Losing data is not something to be taken lightly. NoSQL databases don’t always flush data to permanent storage.
o What is Amazon RDS? When should I use it?
Amazon has a managed relational database solution called RDS. It’s basically MySQL, Oracle or SQL Server, but modified so you can’t shoot yourself in the foot. Administrative tasks are simplified, but so are your configuration options.
I wrote an in-depth Amazon RDS use cases article. It mostly covers MySQL, but the general rules apply to Oracle & SQL Server. At the end of the data RDS is a lot less configurable and flexible. But if you don’t have a regular DBA on staff, it will probably simplify your administration of these servers.
o What are read-replicas? What about Multi-az?
Read-replicas are read-only copies of your data. Using MySQL these are fairly stock master-slave configurations. Note since they’re the standard technology, they’re still asyncronous. So yes the read-replica can lag behind.
Multi-az is a proprietary technology, and Amazon doesn’t disclose what’s under the hood. However it’s likely running on top of something like DRBD which is a distributed filesystem. This allows the underlying disk I/O to be mirrored across the internet, and to another availability zone. You’ll enjoy syncronous copies of your data, and no data consistency problems. Keep in mind those that the alternate server is offline or cold and can take time to come online.
o What is the primary bottleneck of hosting databases in the cloud? How has Amazon recently addressed this?
As I explained above disk I/O remains the largest bottleneck for relational databases, even if the entire dataset fits in memory. Why? Because sorting, joining, and rearranging data can take orders of magnitude more memory to magically do in memory. And that’s not even talking about durability guarentees.
The cloud has traditionally lagged quite a lot behind physical servers in terms of disk I/O so some internet firms have shyed away from moving to the cloud. EBS volumes were typically limited to a few hundred IOPs.
Amazon’s recently announced Provisioned IOPs. It’s a mouthful of a name for a very big development. It means you can provision how fast you want those virtual disks to be. For individual volumes the limit seems to be 2000 IOPs but you can also software raid across many of those virtual disks. For Amazon RDS the limit is reportedly 10,000 IOPs. This new feature will make a huge difference for hosting large high I/O databases in Amazon’s cloud.
2.Architecture & Management Questions
o Why does the API battle between Amazon & Eucalyptus (FOSS) matter?
As large applications are architected to build hardware components, and resources in the cloud, the API they work through becomes key. Sticking to an open standard for this API means you can change cloud vendors and/or build on multiple ones. We talked about this multi-cloud solution as a key way to avoid outages like AirBNB and Reddit experienced when AWS had an outage.
Following on the heels of that article, we were quoted about multi-cloud by Brandon Butler in his Network World piece .
o Do you use command line tools? Why?
A good web operations candidate should be very comfortable with command line tools. Everything in Linux is command line. It’s like broadway acting to movie acting, or literature to books. It’s the original source, much more powerful, what’s more it indicates and requires much stronger theoretical knowledge of the underlying systems being managed.
o What can go wrong with backups? How do we test them?
Everything can go wrong with them. They can fail to complete. Be backups of the wrong service or resource. Even the backup software itself can have bugs. The only way to sleep well at night is if you run firedrills and restore your application and data top to bottom.
o Should we encrypt filesystems in the cloud? What are the risks?
This depends on your environment and how sensitive your data is. If you’re collecting credit card data for instance, it may be key. However some surprising blips may push other applications to encrypt as well. Bugs in the hypervisor could potentially make your data vulnerable. What’s more if the cloud provider gets subpeonaed, it may well capture your server and data into the net. Better safe than sorry. Remember you don’t know where your data actually resides, but you do control who has access if you’re encrypted.
We wrote a very in-depth piece on Deploying on Amazon EC2 where we discuss questions such as encryption in more depth.
o Should we use offsite backups?
It’s definitely worth doing this. One more layer of insurance.
o What is load balancing? Why is it difficult with databases?
Load balancing puts a digital traffic circle into your infrastructure, giving you two roads or paths to resources. However those resources have to be exactly the same. With databases you are constantly writing to tables, and updating records. When you scale those horizontally, it becomes impossible to keep track of changes.
o Why use a package manager? Can we install from source?
Package managers simplify the installation of software components. A team such as Redhat, Ubuntu or Debian builds a distribution, and compiles all components storing them in a repository. Installing packages this way allows your setup to be standard across servers. This allows more automation, and is simpler for another admin to figure out what you have, down the line when it passes to someone elses shoulders.
Installing from source is generally a bad idea. Although it allows you to tweak and configure each piece of software the way you want, tightly and efficiently, it also means everything is custom. No commoditization advantages.
o What is horizontal scalability?
This involves adding more hardware, more individual servers to service the same application and users.
o What is vertical scalability?
This means scaling up or growing your existing single server, so it is larger, has more memory, cpu or faster disk.
o What can go wrong with automatic failover?
Just about everything. Applications and services can stall, disks can fail, servers can hang. What’s more networks can exhibit latency. Automatic failover is ultimately a piece of software or algorithm trying to diagnose and handle situations. And it does so based on a very small list of rules or heuristics. The real world is messy, so this can often lead to false failure detection, and potentially loss of data.
o How do cloud vendors implement vertical scalability?
This may vary dramatically between cloud providers. Ultimately, however since virtualization allows you to boot a disk image onto any hardware, you can snapshot your current root volume or disk and then boot it on another server, one that is larger, smaller and so forth. About the only thing you need to watch out for is 32 versus 64 bit questions.
Published at DZone with permission of Sean Hull. See the original article here.
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