Traditionally, we’ve seen various companies falter without being able to streamline their business operations or properly handle their workloads. With the growth of cloud technology, some tremendously powerful solutions have surfaced. On top of that, grid computing offers an extra element of elasticity that comes with the underlying technology resources. We have already covered some of the basics in our previous blog post, Infinitely Scalable Clusters, Grid Computing 101. As we explore this topic further, we unveil the benefits of grid computing, cloud tech, and serverless tech.
Businesses, but more crucially financial services, are constantly challenged with managing ever growing data sets. Additionally, they are facing massive overheads and processes that are generally time-consuming. As a result, most of these companies are now relying on some form of HPC (high performance computing) grids for valuing portfolios, calculating risk, etc.
There are some key underlying common factors to consider when moving grid computing to the cloud:
In practice, what all of this applies to is kind of irrelevant – so, it doesn’t matter if it’s trading, portfolio analysis, finance, or backend accounting. We’ve even seen it in use cases such as sales and marketing. Ultimately, cloud grid computing is a powerful weapon only when it improves the business and adds value. Naturally, it all falls into place when you are solving business problems, better, quicker, and at a lower cost. As it’s known from the project management triangle (link) ticking all three boxes is impossible, however this doesn’t seem to be a limitation with cloud grid computing and we’ve seen scenarios where all three have been achieved – better results, at a cheaper rate reducing the time from days to hours.
From our experience, even though the cloud significantly lowers the barriers to entry into grid computing, the cloud adoption process can be a challenge. We have seen some recurring themes to the choices firms face: what cloud provider to opt for, what data storage to use, what types of compute, how to transition from legacy languages to more modern, data gravity and governance?
There is no single solution for all cases, but we have to focus on the nature of the business, its data and the output it requires out of that data. Then it is a balancing act between the many variables how to achieve this. The more challenging scenarios are migrating existing legacy workloads from on-premise into a hybrid solution between on-premise and cloud. This often requires compromises around data management and compute resources.
Here are some of the approaches we use at Hentsu to solve these challenges:
Discover more about the serverless approach and refactoring legacy applications in the cloud.
More often the migrations are completely away from on-premise, skipping even the hybrid model, simply because of the added complexity dealing with on-premise equipment. There are some approaches to the hybrid model using solutions such as AWS Outposts, Azure Stack and Google Anthos, as well as solutions such as OpenStack.
Various organizations are utilizing different analytic tools on separate clusters, and this can cause a so-called “cluster sprawl.” Cloud computing is something of a turn-key solution in that regard, thanks to various cloud-based PaaS offerings.
“In some ways, the cluster sprawl has been enabled through the ease with which end users can spin up resources and access different cloud platforms. We’ve seen this across clients, with the democratization of technology and empowerment of teams and users. We work to mitigate this cluster sprawl through templating, reusable patterns, and tight ‘business guardrails’ around what users can do. The other key approach we take is having tight configuration management. This can mean anything from basic having awareness of where things are running, to moving the entire platform into code in Git, and we extensively use Terraform to keep on top of that. That helps keep in check of what the infrastructure is and how it is spun up, deployed and used across different cloud providers and teams. At the end of the day, as tech we need balance empower of the users with also getting the right business value as quickly and efficiently as possible” Hentsu CEO, Marko Djukic.
There is a fine line between too much locking down and too much freedom. The cloud tech is always innovating and evolving, which is one of the key attractions of cloud platforms. What used to be great a year ago, is suddenly replaced with something better and evolved, and tech needs to enable getting that into the end user’s as quickly as possible.
So, let's examine certain essentials when it comes to cloud grid computing:
As cloud technology grows and evolves, our knowledge expands, and Hentsu can help with challenges you may be facing as you form your own business strategy around the public cloud space.
To learn even more about the advantages Grid Computing, check out full interviews with Marko Djukic and our other Hentsu cloud experts.
Tell us about the technology challenges that you face – we would love to hear from you: firstname.lastname@example.org[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built="1" _builder_version="4.1"][et_pb_row _builder_version="4.1"][et_pb_column type="4_4" _builder_version="4.1"][et_pb_video src="https://www.youtube.com/watch?v=9eHStLqY4go&feature=youtu.be" _builder_version="4.1"][/et_pb_video][et_pb_text _builder_version="4.1" header_font="|||||||#000000|" hover_enabled="0" locked="off"]
We are currently seeing a major change in the IT industry, and the cloud environment has turned into a safe haven. With a variety of major businesses switching to the public cloud, we have also seen a huge drive towards scaling, and automation. Generally, both the technology and financial sectors are facing a huge shift from having complex computing tasks done manually towards more streamlined and automated processes. That's where grid computing comes in.
When going for cloud adoption, “businesses are pushing PaaS first and that has a lot of positive effects. To begin with, things are made easier right off the bat, because essentially all the building blocks are there, so any initial business can run workloads and get going within a day or two, rather than wasting too much time to set up the foundation,” stated Hentsu CEO, Marko Djukic.
An increasing amount of businesses are implementing grid computing clusters to handle massive workloads.
Grid Computing refers to making use of the shared power of a cluster of computers to process computationally intensive tasks that would otherwise bog down a single workstation. To put it simply, jobs can be submitted from one computer to the grid, which then processes the data and returns the output to the user. Importantly, multiple people can simultaneously make use of the same grid by intelligently managing how the computers in the grid allocate resources. This allows for significantly improved workflow for companies whose work is optimized for grid computing.
Opening with a much needed refresher on public and private cloud, as well as defining key terminology, the talk flowed into an investigation of the challenges companies face when working with different data sets and a look at solutions currently available to companies.
To recap, grid computing denotes one main computer that distributes information and tasks across multiple networked computers – all of that usually towards one objective. Let us simplify a bit and illustrate how things operate. Grid computing network frequently has three types of machines:
One of the key aspects of grid computing is flexibility, and more importantly, computing power. In other words, it boils down to having a single computer grid for large amounts of data rather than placing the demand on a single supercomputer. You can also find out how Grid Computing yields faster results for your business.
But for now, let's focus on the most frequently asked questions related to grid computing.
Why grid is computing important?
What are the real benefits and biggest advantages of grid computing?
Well, the reasons why so many businesses rely on this particular method of completing joint tasks because it denotes following key advantages:
It has to be highlighted that ephemeral computing has also been a huge part of the innovation process in modern-day tech. It carries tremendous advantages, albeit we have to ask the simple and most obvious question here: what does that mean for businesses and the SaaS industry in particular?
When you describe a process as “ephemeral” it denotes something temporary and brief. Essentially, the notion of dealing with a surplus of servers or indeed a shortage of servers is something that’s not an issue with ephemeral computing. To put it into perspective, ephemeral computing services are agile and will adjust according to the problems and needs at hand.
Utilizing ephemeral clusters that scale up and down as needed is quite a boost to handling workloads in general. In short, it means you limit or eliminate convoluted pre-planning and relying on heavy server power.
“It’s basically all about serverless. Code that is distributed across ephemeral compute that handles the analysis and then churns out the answers without having to deal with what’s actually the underlying compute,” says Marko Djukic.
He added: “Compute is just a utility you consume as needed, nothing exists permanently."
To summarize, in PaaS and SaaS scenarios, giving your business operations and workloads the power to shrink automatically, can completely remove any scalability issues you may be experiencing with traditional server-heavy computing methodology.
There is a breadth of choices for grid computing and how to migrate workloads into cloud environments. We covered some of those, looking at traditional MATLAB setups to more extreme Platform as a Service (PaaS) environments from Google using their Bigquery and Datalab, and ran some live demos ripping though 2TB of full depth market data.
We've built up a wealth of in-house expertise running grid computing workloads across all three major public clouds - Amazon AWS, Microsoft Azure and Google Compute Engine. We can get you up and running quickly with pre-tested designs and architectures, greatly eroding the overall traditional pains and TCO for running grid computing.[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version="4.1"][et_pb_column type="4_4" _builder_version="4.1"][et_pb_text _builder_version="4.1"]
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