Private cloud deployments: Beating the blind spots and bottlenecks

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Source is ComputerWeekly.com

Organisations retain, or migrate to, private cloud on-premise environments for their own legacy, security or compliance reasons. They still want the benefits of cloud and cost-effective capacity to meet demand, without the risk of blind spots or bottlenecks.

But Tiago Fernandes, lead cloud solutions architect at IT distributor Tech Data, says this can be complicated, requiring detailed scrutiny of the environment and resources, before right-sizing the central processing unit (CPU) and memory allocation for virtual machines (VM).

“If a VM isn’t being used, shut it down – as long as there are no processes going behind to clean up, for example,” says Fernandes. “I don’t see why you can’t do snoozing in private cloud as well.”

Processes must be in place and routinely reviewed to pinpoint, for example, any larger VMs that are not using all their allocated resources, such as VMs running end-of-month payments or batch processing screens that are idle the rest of the time, or eating up 80% of the CPU because they are old or dealing with multiple reports or scripts. Hypervisors that can manage over-committed memory can also help redistribute memory to more idle VMs.

“Keep a close eye on all that – sometimes storage latency comes from a CPU or memory bottleneck,” says Fernandes.

Scope out, monitor and manage dormant resources, he says. Ask about projects or plans that may affect demand, including marketing campaigns and new offerings, and find out what capacity will be required in future. This means IT working much more closely with parts of the organisation than has been typical in many businesses.

Review all the metrics and look for hidden problems before investing in more capacity. Also, check and stress-test all recommendations for applications and workloads before they go live.

“Capacity management affects return on investment [ROI] and everybody in the business,” says Fernandes. “Everybody looks at other departments and says: you didn’t forecast. However, IT needs to be connected with the business to be able to predict future demand.”

Effective capacity management

Organisations may assume on-premise private cloud deployments will deliver optimised resources in ways that enhance ROI. Yet effective capacity management entails strong reporting and ongoing governance of all resources, aligning through regular business discussions with all stakeholders, including suppliers, on lead times and processes, including consideration of times of emergency, says Fernandes.

“As per the Flexera 2021 State of the cloud report, everywhere there is a need for automatically scanning and optimising cloud costs,” he adds.

For Chris Royles, field CTO for Europe, the Middle East and Africa (EMEA) at Cloudera, right-sizing private-cloud capacity requires resource isolation, which means running a mix of workloads and carving out sets of resources specifically for certain tasks or types of problem.

Separating architecture tiers with different layers of storage and compute can add enough granularity to enables separate management and scaling, with a control plane and automation delivering resources to handle workloads, he says.

“It’s like having multiple data warehouses running against the same data collection,” says Royles. “You’ve got to have a network group to link these things together, and can then connect between your public cloud instances and your private cloud. Of course, that’s where hybrid really comes into play.”

In that separation of storage and compute within the technology stack, a tier manages the user experience types of application such as the data warehouse tools or machine learning elements, designed to meet the requirements of data scientists, he says. This tier then orchestrates the elastic experiences on top, and below that is the storage tier. This enables independent scaling at every layer.

The user experience tier scales on factors such user numbers – the storage will scale by data volumes, says Royles. The mid-tier captures the logging and telemetry – for example, monitoring workload behaviours over time. It is all about slicing and dicing the resources so that you can manage it whether it is poorly utilised or otherwise, for specific business use cases, in small bites that “smooth the curve”.

“That telemetry informs the resourcing and plan,” he says. “If you go back through everything into the storage, that can be scaled out on VMs, perhaps for 2,000 data scientists. That’s not unusual, and now that is containered, we can actually scale in smaller increments.

“The journey of how to right-size that compute infrastructure sounds counter-intuitive, but it is about using smaller machines, more often – because we need parallel throughput to storage.”

James Sturrock, systems engineering director for Western Europe and sub-Saharan Africa at converged infrastructure supplier Nutanix, agrees that best-practice resourcing in private cloud must start with visibility. Discover what you have got, the resources it is consuming, and where it is assigned – can you can retire it because you have a new system that takes care of this function or capability, or lift it and shift it? Can it be replatformed or refactored?

“Am I going to move away from Oracle, for example, because it’s fairly expensive and move to MySQL, because it can do what I need?” says Sturrock. “Should the big Exchange environment that I’ve got in my datacentre be repurchased as Office 365 or software-as-a-service? Work out what you actually need in the first place and what you’re going to change.”

Is private cloud the right choice?

Ed Hoppitt, EMEA director for modern apps and cloud-native platforms at virtualisation giant VMware, warns that if you don’t get private cloud right either commercially or capacity-wise, people will just go elsewhere for another or different offering. Also, organisations should avoid falling into the trap of assuming that it makes sense to build it themselves because “it’s just engineering time” for the human resource they already have.

“There is only so much governance and corporate pain you can wrap around a line of business,” says Hoppitt. “So first understand why it’s private cloud. If it’s regulatory or security issues, the focus then becomes very much on building the right security model and policies, making sure they can still operate in a way that reflects the kind of agility someone would expect from public cloud.”

To make private cloud concepts work well, what you actually have to do is drive good user behaviour – end-user customers need to understand that it has value and cost, and that they can give back resources as well as take them, he says. It’s about change management and management of the future pipeline.

Paul Stapley, hybrid cloud practice director at services provider Logicalis, says that for most organisations, running a hybrid setup is the way to go, with control once again being about defining the operating model, governance, security, data handling and storage, and compliance.

“Then it’s about continuously monitoring and managing what’s going on to make sure you make the best of that initial decision of where to put services,” he says.

Private cloud most often becomes “what’s left over” after a public cloud migration, rather than a pure play, says Stapley. Beyond that, looking at systems from the likes of Dell, HP and others that have come out with “halfway house”-type solutions that enable different consumption models and more elasticity.

“If you’ve got really spiky elastic workloads, then you can’t be thinking about private cloud, because you are in danger of having to build for the top of that spike, and wasting money,” he says.

“It doesn’t matter how great you are in terms of managing going forward, you have always got that huge headroom that you rarely use. That is why it is so critical to review the nature of the services that the customer has and really have that honest discussion about which environment is best for them.”

Source is ComputerWeekly.com

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