A Software Defined Data Center (SDDC) – a term coined by VMware, also known as a Virtual Data Center (VDC) is a datacenter where all infrastructure components are delivered as virtual devices. Using software, the components’ configurations are controlled and deployment is automated. A SDDC typically includes Software Defined Computing (SDC), Software Defined Storage (SDS), and Software Defined Networking (SDN).
A SDDC is the basis for cloud computing. It enables (end) users and systems managers to create and deploy new infrastructures using user friendly software. The software allows the user to select the needed infrastructure components and their sizing and required availability and automatically configures the SDDC components to deliver the required infrastructure implementation. The SDDC software also provides tools for costing, logging, reporting, scaling (up and down), and decommissioning of the infrastructure (components).
SDDC is not the solution for all problems – there are a large number of application(stacks) that need a much more custom-designed infrastructure than the standard building blocks SDDC provides. Examples are SAP HANA, High performance databases, OLTP, High secure bank or stock trade transaction systems, and SCADA systems.
This entry was posted on Thursday 30 April 2015
One model can be used for virtualization technologies, such as Software Defined Compute (SDC), Software Defined Networking (SDN), and Software Defined Storage (SDS), as shown in the picture below.
The model shows 3 layers: at the bottom, physical devices, then a virtualization layer that creates abstract system resources, and at the top a number of virtual devices that are compiled using the abstract system resources. It is a well-known way of implementing a virtual machine environment, but it also applies to networking and storage.
When the virtualization layer is programmable, using APIs, it can be controlled by (external, third party) software, to support software defined computing, software defined storage, or software defined networking.
The number of physical devices is typically independent of the number of virtual devices. The physical devices can be commodity hardware, or enterprise grade hardware, or a mixture. Because of the virtualization layer the physical hardware can be upgraded, replaced or phased out independent of the operation of the virtual devices.
The virtualization layer provides a resource pool that enables virtual devices to be configured. Ideally, the virtualization layer should decrease the performance, as delivered by the physical devices, by no than 10%.
The virtualization layer can provide advanced features, such as:
- Storage (SDS): deduplication, RAID, Snapshots;
- Compute (SDC): Live migration, virus scanning;
- Networking (SDN): VLANs, filtering, IDS, firewalls, virus scanning;
and provides APIs for scripting (orchestration), as provided by software such as OpenStack.
This entry was posted on Thursday 23 April 2015
Software Defined Computing
While virtualization has been around for many decades, it was mainly focused on the virtualization of computing power – the use of multiple virtual machines running on one physical machine. This allowed a better use of the physical computer’s resources, as most of the physical machines ran at a fairly low CPU and memory utilization. A hypervisor is used as a layer between the physical and virtual machines. Apart from providing virtual machines, this hypervisor also allowed for additional functionality, like managing virtual machines from one management console, adding virtual memory of CPU cores to a virtual machine, high availability by restarting failing machines, and dynamically moving running machines between physical machines to allow load balancing and maintenance. This extra functionality (that the virtual machines are not aware of) can be called Software Defined Computing (SDC), as the hypervisor is controlled by software. In addition, SDC provides open APIs to enable third party software to monitor and control the SDC’s hypervisor(s).
Not only compute resources can be virtualized. Lately, virtualization of networking and storage resources is becoming more popular. This allows not so much for a better utilization of the hardware – as this is not necessarily solved by this virtualization, but does allow for software defined storage (SDS) and software defined networking (SDN).
Software Defined Storage
With SDS, the physical storage pool is virtualized into virtual storage pools (LUNs). This is nothing new, this was possible for many years. In addition to this, SDS provides extra functionalities, like the connection of heterogeneous storage devices and using open APIs.
SDS enables to use storage devices from multiple vendors and manage them as one storage pool by using open APIs and by allowing to physically couple physical storage devices together.
Software Defined Networking
With SDN a relatively simple physical network can be used to provide a complex virtual network. Technologies like vLANs have been around for a long time, but they require complex configurations on a number of devices to work properly. SDN provided one point of control to configure the network in a dynamic way.
In a SDN environment, the physical network is typically based on a spine and leaf topology, as shown below.
This topology has a number of benefits:
- Each server is always exactly four hops away from every other server
- The topology is simple to scale: just add spine or leaf servers
- Since there are no interconnects between the spine switches, the design is highly scalable
Because of the relatively flat hierarchy and the fixed number of hops, the topology can easily be virtualized using vLANs. The virtual network can then have an hierarchical, complex and secured virtual structure that can easily be changed without touching the physical switches. The network can be controlled from a single management console and open APIs can be provided to manage the network using third party software.
This entry was posted on Wednesday 15 April 2015
I found that there is no clear definition of the number of concurrent users a system must support.
When a system is used by a large group of users, not all users are active all the time. For instance, if your organization has 10,000 employees, not everyone is in the office working every day. People have holidays, or can be sick. And if they are in the office, they are not behind their desks all the time, as they can be in meetings, standing at the coffee machine, etc. And when they are at their desk, using the system, they are not always active using the system’s back-end systems. For instance, when they are reading an article fetched from the internet, only the fetching of the document puts a load on the system. The time the user is reading the text, does not put a load on the system.
Consider the following example.
|Total number of employees
|Only 80% is at the office
| 70% of their time is spent at their desk
| At their desk, they use the system 70% of the time
In that time, they only perform actions that put a
load on the infrastructure for 5% of the time
This means that during the day, on average, of all employees, only 196 people are actively using the infrastructure at any given moment.
As an alternative, we can use the ratio between usage of the system and “thinking time”. In our example, the percentage thinking time is 100% - 10000/196 = 98%.
A further breakdown could show how the system is used:
||Open file in an office application (like Excel or Word)
||Save document from an office application
||Open file explorer
|Send HTTP request
||Push a button in a browser-based application, leading to sending data, or use AJAX calls
|Receive HTTP data
||Receive data from a webserver when using a browser-based application, or use AJAX calls
|Send data to the Internet
||Push a button on an internet page, use AJAX calls or send data using protocols like FTP
|Receive data from the Internet
||Receive a web page from the internet, use AJAX calls or receive data using protocols like FTP
||Send a typed email to the email server, or update calendar items
|Receive email/calendar updates
||Receive new emails from the email server
|Send VDI/SBC data
||In a SBC or VDI environment, send keyboard and mouse input to the server
|Receive VDI/SBC data
||In a SBC or VDI environment, receive screen output from the server
|Send and receive data from DNS
||Use DNS to resolve IP addresses
|Send and receive data from AD
||Use AD to handle login/logout or to check credentials
||Other uses of the infrastructure
Using such a categorization, the actual load on the infrastructure can be calculated, if we know how the system is setup, how the actions relate to a certain load and what a typical user’s behavior is. Not all users are alike. By observing groups of people, their typical behavior can be mapped to the defined categories over time. For instance, a group called secretaries will typically:
- Open 25 existing Word documents
- Save 40 Word documents (including new documents)
- Send 25 emails
- Receive 25 emails
Based on these numbers, and with the insight in the setup of the system, the actual load on the various parts of the infrastructure can be calculated. This calculation can then be used to shape performance tests.
This entry was posted on Friday 23 January 2015
The availability of an IT component can be obtained by measuring (monitoring) the performance of that component. If the performance is below a certain threshold, the IT components is reported unavailable.
Monitoring IT systems can be done using a variety of tools. Vendors like IBM, HP, BMC and others provide tools to:
- Measure performance
- Capture logging
- Generating alarms based on thresholds
- Report the collected data in dashboards or other overviews
Typically, the number of measuring points in an IT landscape is quite overwhelming. When installed out of the box, monitoring tools will typically detect many issues per second, leading to many false alarms. Therefore, it is essential to tune the monitoring system to only generate useful alarms and to create reports containing useful information for specific stakeholders.
Performance measurement (and as derivate – availability detection) can be done on multiple levels:
- Business process level
- Application component level
- Infrastructure component level
It is important to have separated performance measurements on all three levels and to have processes to solve issues on all individual levels.
For the end user of the system, only the business process level is important – as soon as the performance of this level is too low, the end users will be in trouble. Therefore, the business process level should be measured. Today’s tools are able to measure individual business process steps either by measuring their normal use or by measuring the effect of generated business actions. For instance, it can be measured how long it takes to print an invoice and it can be measured how long a simulated fake order takes to be processed in a certain business step.
If the performance on the business process level is below the set threshold, first the performance of the underlying application component(s) should be verified. Since every layer is responsible for its own performance, it could be that there is a problem in the application component layer causing the performance issue in the business process layer. And the application component layer could have performance issues due to a performance issue in the infrastructure component layer. Therefore it is important to separate these layers and give systems managers specific responsibilities for a certain layer. Between the layers, service level agreements should be agreed (Service Level Agreements – SLAs).
If the performance of the business process level is too low and there is no problem in the underlying application components, the solution to the performance issue must be found in the business process layer itself. If this is not the case, then there is a mismatch between the layers – a certain business process issue is apparently not detected in the lower application service layer.
Of course, this reasoning is also valid for the relation between the application components layer and the infrastructure component layer.
On the application component level, performance can be measured effectively if the application components contains “hooks” that the monitoring tool can use to verify the performance of a software component. Without these hooks, measuring can only be done on a much lower granularity. Especially when bespoke software is developed it is advised to invest in building these hooks in the software as part of the regular development process. Typical measurements are the number of times a (part of an) application component is used and how long it takes to finish a certain task. In software, typically there are some hot spots – parts of the code that are used much more frequently than others. By measuring using hooks in the software, these hot spots can be found, monitored, and optimized for performance.
On the infrastructure component level, the performance of each individual component can be measured. Examples are:
- CPU load
- Memory usage
- Network response time
- Network load
- Storage response time
- Storage load
Based on these measurements, low performance, or even unavailability of a certain component or a set of components can be detected.
Systems managers can react on the detection of low performance by addressing the issue at hand. It is important to acknowledge that early detection and resolving of performance issues is essential to avoid performance problems at the higher layers. Early detection and resolving keeps the systems managers busy, but reduces the risk that end users experience performance issues.
It is like the people who work hard to keep the trains running on time. If they do their work well, no one will notice…
This entry was posted on Friday 09 January 2015