Why Canonicalization Should Be a Core Component of Your SQL Server Modernization (Part 1)
Tue, 23 Mar 2021 12:37:40 -0000|
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The Canonical Model, Defined
A canonical model is a design pattern used to communicate between different data formats; a data model which is a superset of all the others (“canonical”) and creates a translator module or layer to/from which all existing modules exchange data with other modules . It’s a form of enterprise application integration that reduces the number of data translations, streamlines maintenance and cost, standardizes on agreed data definitions associated with integrating business systems, and drives consistency in providing common data naming, definition and values with a generalized data framework.
SQL Server Modernization
I’ve always been a data fanatic and forever hold a special fondness for SQL Server. As of late, my many clients have asked me: “How do we embark on era of data management for the SQL Server stack?”
Canonicalization, in fact, is very much applicable to the design work of a SQL Server modernization effort. It’s simplified approach allows for vertical integration and solutioning an entire SQL Server ecosystem. The stack is where the “Services” run—starting with bare-metal, all the way to the application, with seven integrated layers up the stack.
The 7 Layers of Integration Up the Stack
The foundation of any solid design of the stack starts with . Dell Technologies is best positioned to drive consistency up and down the stack and its supplemented by the company’s subject matter infrastructure and services experts who work with you to make the best decisions concerning compute, storage, and back up.
Let’s take a look at the vertical integration one layer at a time. From tin to application, we have:
- Infrastructure from Dell Technologies
- Virtualization (optional)
- Software defined – everything
- An operating system
- Container control plane
- Container orchestration plane
There are so many dimensions to choose from as we work up this layer cake of both hardware and software-defined and, of course, applications. Think: Dell, VMware, RedHat, Microsoft. With the progress of software, evolving at an ever-increasing rate and eating up the world, there is additional complexity. It’s critical you understand how all the pieces of the puzzle work and which pieces work well together, giving consideration of the integration points you may already have in your ecosystem.
Determining the Most Reliable and Fully Supported Solution
With all this complexity, which architecture do you choose to become properly solutioned? How many XaaS would you like to automate? I hope you answer is – All of them! At what point would you like the control plane, or control planes? Think of a control plane as the where your team’s manage from, deploy to, hook your DevOps tooling to. To put it a different way, would you like your teams innovating or maintaining?
As your control plane insertion point moves up towards the application, the automation below increases, as does the complexity. One example here is the Azure Resource Manager, or ARM. There are ways to connect any infrastructure in your on-premises data centers, driving consistent management. We also want all the role-based access control (RBAC) in place – especially for our data stores we are managing. One example, which we will talk about in Part 2, is Azure Arc.
This is the main reason for this blog, understanding the choices and tradeoff of cost versus complexity, or automated complexity. Many products deliver this automation, out of the box. “Pay no attention to the man behind the curtain!”
One of my good friends at Dell Technologies, Stephen McMaster an Engineering Technologist at Dell, describes these considerations as the Plinko Ball, a choose your own adventure type of scenario. This analogy is spot on!
With all the choices of dimensions, we must distill down to the most efficient approach. I like to understand both the current IT tool set and the maturity journey of the organization, before I tackle making the proper recommendation for a solid solution set and fully supported stack.
Dell Technologies Is Here to Help You Succeed
Is “keeping the lights on” preventing your team from innovating?
Dell Technologies Services can complement your team! As your company’s trusted advisor, my team members share deep expertise for Microsoft products and services and we’re best positioned to help you build your stack from tin to application. Why wait? Contact a Dell Technologies Services Expert today to get started.
Stay tuned for Part 2 of this blog series where we’ll dive further into the detail and operational considerations of the 7 layers of the fully supported stack.
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Why Canonicalization Should Be a Core Component of Your SQL Server Modernization (Part 2)
Tue, 23 Mar 2021 12:59:44 -0000|
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In Part 1 of this blog series, I introduced the Canonical Model, a fairly recent addition to the Services catalog. Canonicalization will become the north star where all newly created work is deployed to and managed, and it’s simplified approach also allows for vertical integration and solutioning an ecosystem when it comes to the design work of a SQL Server modernization effort. The stack is where the “services” run—starting with bare-metal, all the way to the application, with seven layers up the stack.
In this blog, I’ll dive further into the detail and operational considerations for the 7 layers of the fully supported stack and use by way of example the product that makes my socks roll up and down: a SQL Server Big Data Cluster. The SQL BDC is absolutely not the only “application” your IT team would address. This conversation is used for any “top of stack application” solutions. One example is Persistent Storage – for databases running in a container. We need to solution for the very top (SQL Server) and the very bottom (Dell Technologies Infrastructure). And, many optional permutation layers.
First, a Word About Kubernetes
One of my good friends at Microsoft, Buck Woody, never fails to mention a particular truth in his deep-dive training sessions for Kubernetes. He says, “If your storage is not built on a strong foundation, Kubernetes will fall apart.” He’s absolutely correct.
Kubernetes or “K8s” is an open-source container-orchestration system for automating deployment, scaling, and management of containerized applications and is the catalyst in the creation of many new business ventures, startups, and open-source projects. A Kubernetes cluster consists of the components that represent the control plane and includes a set of machines called nodes.
To get a good handle on Kubernetes, give Global Discipline Lead Daniel Murray’s blog a read, “Preparing to Conduct Your Kubernetes Orchestra in Tune with Your Goals.”
The 7 Layers of Integration Up the Stack
Let’s look at the vertical integration one layer at a time. This process and solution conversation is very fluid at the start. Facts, IT desires, best practice considerations, IT maturity, is currently all on the table. For me, at this stage, there is zero product conversation. For my data professionals, this is where we get on a white board (or virtual white board) and answer these questions:
- Any data?
- Any way?
Answers here will help drive our layer conversations.
From tin to application, we have:
The foundation of any solid design of the stack starts with Dell Technologies Solutions for SQL Server. Dell Technologies infrastructure is best positioned to drive consistency up and down the stack and its supplemented by the company’s subject matter experts who work with you to make optimal decisions concerning compute, storage, and back up.
The requisites and hardware components of Layer 1 are:
- Memory, storage class memory (PMEM), and a consideration for later—maybe a bunch of all-flash storage. Suggested equipment: PowerEdge.
- Storage and CI component. Considerations here included use cases that will drive decisions to be made later within the layers. Encryption and compression in the mix? Repurposing? HA/DR conversations are also potentially spawned here. Suggested hardware: PowerOne, PowerStore, PowerFlex. Other considerations – structured or unstructured? Block? File? Object? Yes to all! Suggested hardware: PowerScale, ECS
- Hard to argue the huge importance of a solid backup and recovery plan. Suggested hardware: PowerProtect Data Management portfolio.
- Dell Networking. How are we going to “wire up”—Converged or Hyper-converged, or up the stack of virtualization, containerization and orchestration? How are all those aaS’es going to communicate? These questions concern the stack relationship integration and a key component to getting right.
Note: All of Layer 1 should consist of Dell Technologies products with deployment and support services. Full stop.
Now that we’ve laid our foundation from Dell Technologies, we can pivot to other Dell ecosystem solution sets as our journey continues, up the stack. Let’s keep going.
Considerations for Layer 2 are:
- Are we sticking with physical tin (bare-metal)?
- Should we apply a virtualization consolidationfactor here? ESXi, Hyper-V, KVM? Virtualization is “optional” at this point. Again, the answers are fluid right now and it’s okay to say, “it depends.” We’ll get there!
- Do we want to move to open-source in terms of a fully supported stack? Do we want the comfort of a supported model? IMO, I like a fully supported model although it comes at a cost. Implementing consolidation economics, however, like I mentioned above with virtualization and containerization, equals doing more with less.
Note: Layer 2 is optional (dependent upon future layers) and would be fully supported by either Dell Technologies, VMware or Microsoft and services provided by Dell Technologies Services or VMware Professional Services.
Choices in Layer 3 help drive decision or maturity curve comfort level all the way back to Layer 1. Additionally, at this juncture, we’ll also start talking about subsequent layers and thinking about the orchestration of Containers with Kubernetes.
Considerations and some of the purpose-built solutions for Layer 3 include:
- Software-defined everything such as Dell Technologies PowerFlex (formally VxFlex).
- Network and storage such as The Dell Technologies VMware Family – vSAN and the Microsoft Azure Family on-premises servers – Edge, Azure Stack Hub, Azure Stack HCI.
As we are walking through the journey to a containerized database world, at this level, is where we also need to start thinking about the CSI (Container Storage Interface) driver and where it will be supported.
Note: Layer 3 is optional (dependent upon future layers) and would be fully supported by either Dell Technologies, VMware or Microsoft and services provided by Dell Technologies Services or VMware Professional Services.
Ah, we’ve climbed up four rungs on the ladder and arrived at the Operating System where things get really interesting! (Remember the days when OS was tin and an OS?)
Considerations for Layer 4 are:
- Windows Server. Available in a few different forms—Desktop experience, Core, Nano.
- Linux OS. Many choices including RedHat, Ubuntu, SUSE, just to name a few.
Note: Do you want to continue the supported stack path? If so, Microsoft and RedHat are the answers here in terms of where you’ll reach for “phone-a-friend” support.
Option: We could absolutely stop at this point and deploy our application stack. Perfectly fine to do this. It is a proven methodology.
Container technology – the ability to isolate one process from another – dates back to 1979. How is it that I didn’t pick this technology when I was 9 years old? Now, the age of containers is finally upon us. It cannot be ignored. It should not be ignored. If you have read my previous blogs, especially “The New DBA Role – Time to Get your aaS in Order,” you are already embracing SQL Server on containers. Yes!
Considerations and options for Layer 5, the “Container Control plane” are:
- VMware VCF 4.
- RedHat OpenShift (with our target of a SQL 2019 BDC, we need 4.3+).
- AKS (Azure Kubernetes Service) – on-premises with Azure Stack Hub.
- Vanilla Kubernetes (The original Trunk/Master).
Note: Containers are absolutely optional here. However, certain options, in these layers, that will provide the runway for containers in the future. Virtualization of data and containerization of data can live on the same platform! Even if you are not ready currently. It would be good to setup for success now. Ready to start with containers, within hours, if needed.
The Container Orchestration plane. We all know about Virtualization sprawl. Now, we have container sprawl! Where are all these containers running? What cloud are they running? Which Hypervisor? It’s best to now manage through a single pane of glass—understanding and managing “all the things.”
Considerations for Layer 6 are:
Finally, we have reached the application layer in our SQL Server Modernization. We can now install SQL Server, or any ancillary service offering in the SQL Server ecosystem. But hold on! There are a couple options to consider: Would you like your SQL services to be managed and “Always Current?” For me, the answer would be yes. And remember, we are talking about on-premises data here.
Considerations for Layer 7:
- The application for this conversation is SQL Server 2019.
- The appropriate decisions in building you stack will lead you to Azure Arc Data Services (currently in Preview), SQL Server and Kubernetes is a requirement here.
Note: With Dell Technologies solutions, you can deploy at your rate, as long as your infrastructure is solid. Dell Technologies Services has services to move/consolidate and/or upgrade old versions of SQL Server to SQL Server 2019.
The Fully Supported Stack
In terms of considering all the choices and dependencies made at each layer of building and integrating the 7 layers up the stack, there is a fully supported stack available that includes services and products from:
- Dell Technologies
Also, there are absolutely many open-source choices that your teams can make along the way. Perfectly acceptable to do. In the end, it comes down to who wants to support what, and when.
Dell Technologies Is Here to Help You Succeed
There are deep integration points for the fully supported stack. I can speak for all permutations representing the four companies listed above. In my role at Dell Technologies, I engage with senior leadership, product owners, engineers, evangelists, professional services teams, data scientists—you name it. We all collaborate and discuss what is best for you, the client. When you engage with Dell Technologies for the complete solution experience, we have a fierce drive to make sure you are satisfied, both in the near and long term. Find out more about our products and services for Microsoft SQL Server.
I invite you to take a moment to connect with a Dell Technologies Service Expert today and begin moving forward to your fully-support stack / SQL Server Modernization.
Dell Technologies partners with Microsoft and Red Hat running SQL Server Big Data Clusters on OpenShift
Mon, 06 Jul 2020 18:39:56 -0000|
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Introduced with Microsoft SQL Server 2019, SQL Server Big Data Clusters allow customers to deploy scalable clusters of SQL Server, Spark, and HDFS containers running on Kubernetes. Complete info on Big Data Clusters can be found in the Microsoft documentation. Many Dell Technologies customers are using Red Hat OpenShift Container Platform as their Kubernetes platform of choice and with this and many other solutions we are leading the way on OpenShift applications.
In Cumulative Update 5 (CU5) of Microsoft SQL Server 2019 Big Data Clusters (BDC), OpenShift 4.3+ is supported as a platform for Big Data Clusters. This has been a highly anticipated launch as customers not only realize the power of BDC and OpenShift but also look for the support of Dell Technologies, Microsoft, and Red Hat to run mission-critical workloads. Dell Technologies has been working with Microsoft and Red Hat to develop architecture guidance and best practices for deploying and running BDC on OpenShift.
For this effort we utilized the Databricks’ TPC-DS Spark SQL kit to populate a dataset and run a workload on the OpenShift 4.3 BDC cluster to test the various architecture components of the solution. The TPC-DS benchmark is a popular database benchmark used to evaluate performance in decision support and Big Data environments.
Based on our testing we were able to achieve linear scale of our workload while fully exercising our OpenShift cluster consisting of 12 Dell EMC R640 PowerEdge Servers and a single Dell EMC Unity 880F storage array.
Total time of all queries run for 10,20,and 30TB datasets
As a result of this testing, a fully detailed OpenShift reference architecture and a best practices paper for running Big Data Clusters on Dell EMC Unity storage are under way and will be published soon. More information on Dell Technologies solutions for OpenShift can be found on our OpenShift Info Hub. Additional information on Dell Technologies for SQL Server can be found on our Microsoft SQL webpage.