Voice of the DBA

Tag: career

  • Salaries in Job Ads

    Hiring at Basecamp is interesting. I caught this interview and think it’s a good look at a process most of us have gone through, but perhaps not thought about. Maybe we ought to try and not start out our relationship as employer/employee with a “I got one over on you”.

    Of course, many companies are not interested in treating employees well and just assume they’ll hire/fire/turnover often. Makes sense in some places (McDonalds type work), but less sense in our industry.

    I do think that we hide salaries too much in our industry. Certainly this aids in favoritism and entitlement for works with seniority. I’d really prefer to see salary ranges published for jobs, both internally and in the description. And not some huge range, but put something like a junior DBA from US$35,000-50,000. Or whatever range you think is appropriate.

    This would do a few things for me. First, it ensures that candidates that want to work for that range will apply. It also ensures you don’t waste time with a developer that wants to move to DBA work, but really needs $70,000 for their financial commitments. This also helps you determine if you’re range is correct for the market.

    I am a big proponent of disclosing more info up front and finding a good match between employer and employee.

  • The Aware DBA

    A long time ago, at least, a long time in the eyes of my kids, I worked for a large organization as a production DBA. We had a generic monitoring tool, but it wasn’t SQL Server specific. I ended up writing my own enhancements for the tool that used its data, as well as gathering other SQL Server specific items into a local database on each instance. From there, I had this data copied to a central location each night and a report generated. This helped us with ISO certification (originally) and later, Sarbanes-Oxley compliance.

    I was reminded of that when I read Pamela Mooney’s post on Things You Should Know About Your Server. She follows the simple method of ensuring each server monitors itself and rolls up that data. This works well, even if I’d never want to do this again. The time I spent building a monitoring system wasn’t really time well spent. These days I’d buy some monitoring software and then query that data, bother the vendor for enhancements and have either a notebook or a smaller set of processes that gathered specific data I might need. Likely I’d use XE and some stored query data, but if I monitor infrastructure, I don’t want to have to worry about building and maintaining monitoring software.

    The main point from Pamela’s post, however, is that she seeks awareness of how the systems work. That’s the key for a successful sysadmin of any system. You should not, and do not want to, check each system every day, but you do want to know how to find out what is “normal” quickly and be aware of changes. We want to quickly narrow down potential and possible problems because of our experience and history with some server/instance/application/etc.

    Most of us get calls on a few systems regularly. We may know those well, but often we’re fire fighting and normal can be an elusive definition. There are often many systems that we rarely get called to examine, but most good DBAs I know have some idea of how almost every system performs. Having a little data available quickly allows us to diagnose whether a problem is real or imaginary, chronic or transient, as well as how to proceed to resolve any issue.

    Awareness is an important skill when dealing with anything on a regular basis in your life. Certainly in parts of life outside of work, but even at work, paying attention and having some idea how how your environment should work will help you catch, diagnose, and solve issues. The best DBAs might do this before the client even calls.

    Steve Jones

    Listen to the podcast at Libsyn, Stitcher or iTunes.

  • Learning Kubernetes Security Concepts

    This post continues looking at my process of learning more about Kubernetes. I’ve been working through the 50 days of Kubernetes (K8s). Here I continue on with a few videos on secrets, configuration management and RBAC.

    Secrets

    I am glad that the idea of storing data securely has come to so many applications. Authentication, authorization, privileges, and more are complex and hard to get right. We continually see problems with passwords, certificates, and the link not being managed well.

    Kubernetes has the concept of secrets, which can be values or file contents (like a certificates). These can then be sent or mounted to containers for use.

    One problem, these are stored in the Kubernetes etcd (keyvalue store) in an unencrypted format. Kubernetes has new concepts to integrate into key management areas, like Azure Key Vault, to protect secrets, though Kubernetes privilege controls are still needed.

    A gross simplification, but I learned a little more about what secrets are.

    Configuration Management

    This is interesting to me, because I like abstracting things away. In Kubernetes, we abstract a configuration object as a separate entity, which can then be applied to a container/pod later. This also works through deployments, allowing configurations to be part of the rolling deployment, which can prevent issues.

    If you have good testing/evaluation of what is healthy. This is likely easier than comprehensive unit testing, but still.

    A good idea, just not sure if this is too much.

    RBAC

    I always think of this as row-based, but it’s really role-based, so maybe that should be the way I translate RBAC in my head.

    Like most systems that use RBAC, there is, of course, a role. The video wanders a bit in the explanation, but I’ll try to summarize what I learned. There are two facets to roles. First, these are verb/noun pairs that determine what permission is available for what resource. Like get/list for the verb, and pod, volume, service, etc. for the noun. These are setting up the permission side.

    However, there is another facet. These roles can be set as cluster roles, similar to server roles for SQL Server, or at the namespace level, more like a database role. In either case, you are scoping permissions. Obviously, be careful with cluster roles.

    The other side of this is the user. We can have users or groups used for these roles, similar to what is in SQL Server.

    A simple explanation, but at least I have some idea of the concept.

  • More Kubernetes Concepts

    This post continues looking at my process of learning more about Kubernetes. I’ve been working through the 50 days of Kubernetes (K8s). Now that I had a break from some travel, I went through a few videos in a short period of days. This post combines a few looks at Scenarios, storage, and stateful sets

    Scenarios

    This was a good look at how one of the founders see the Kubernetes being used. The initial idea was microservices, where many services each live in a container and communicate. Managing lots of containers, and lots of instances of each, is where Kubernetes excels.

    The second scenario is the diurnal or cyclical scenario where a load goes up and down each day/night, week/weekend, etc. Having Kubernetes manage the increase and decrease of workload is valuable, and if you’re in the cloud, then you’re not investing heavily in hardware that is unused.

    The third is with complex workflows, where one thing, then another, then another happens. I’m less sold here, but I do see that spin up/spin down, and having these workloads/processes in containers rather than on certain machines makes sense.

    Lastly, AI/ML places where all parts of your flow can access the Kubernetes API and spin things up and down or move workloads to better hardware, like GPU/FPU concentrated systems, that can help keep things moving.

    Good to see the different ways that this might be useful, though I was wondering if I’d see anything database related. I didn’t.

    Volumes and Storage

    The important thing for database workloads is storage. This is a constant question when I talk containers. What about the disks and storage and how does this work.

    This is a basic video, just noting that volumes are objects in K8s. They are attached to pods, but can be mounted (or not) inside containers in the pod. There is temp storage (/emptydir, need to look this one up), but we can also abstract away other storage with Persistent Volume Claims. These are the aspirational storage requirements that the container/pod needs.

    I’m not completely clear on these, and the explanation is a little light, so I’ll have to learn more later.

    Stateful Applications

    The last set of learning for this post. More relevant because SQL is a stateful application. Or so I thought.

    This really looks at stateful sets in Kubernetes, which are the ways in which we want orderly copies in a replica set. This means hostnames and DNS entries in stateful sets are ordered, and 0 based indexed. If I have a host of SalesSQL with 3 sets, I’ll get

    • SalesSQL-0
    • SalesSQL-1
    • SalesSQL-2

    Likewise, I may have salessql.mydomain.com, but I’ll also have the –0, –1, –2 DNS entries as well. The Kubernetes platform also will scale up and down from the end, adding or removing the next ordered element container.

    There can also be volumes associated here, or not, as your stateful application may have the need to use the same volume (like a clustered SQL Server) or separate volumes, like AGs. In any case, it’s a light explanation that I need to know more of.

    One thing I didn’t really like is that the data stores were associated as “cloud native storage applications”, not data stored or data platforms. Application developers I think sometimes forget there’s more to data than storage.