We chatted with Greg Cockburn, Principle Practice Lead for Australia-based managed services provider AC3, about how they selected ParkMyCloud as part of their MSP software portfolio.
Great to speak with you, Greg! Can you start out by telling us about AC3 and what you all do?
Sure. So our go-to-market strategy is about cloud, infrastructure, data, software integration, and cybersecurity management. We can help you on your journey from a consulting phase about a new project, or during a migration into the cloud, all the way through to managing that on an ongoing basis. We provide managed services, cybersecurity expertise, day-to-day operations, cloud infrastructure builds, software development, and everything in between.
It requires us to really understand the client’s business. For us, it’s really all about enabling technology to solve business problems.
What’s your role at AC3?
My role is Principle Practice Lead, I look after all of the practices which include AWS, Azure, systems integration and management, and two up and coming practices: software and data, and cybersecurity.
How many customers do you all have?
About a thousand. That’s about a 50/50 split of customers using AWS or Azure, and customers in private cloud. And that’s across both government and private organizations and all sizes.
Are most of your customers in your general geographical area?
Yes. Most of our customers are Australian or New Zealand based.
So of your customers that are using AWS or Azure, how far are they into their cloud journey?
It’s a very varied mix. We have everything from mid-sized agencies that have been running WordPress environments and need help with customizations, all the way through to large enterprises and governments. Where they are in their cloud journeys can vary greatly.
For some, we’re starting with a lift-and-shift and then kind of unraveling some of their workloads to see if we can start making use of native services. For others, there are workloads that we’re looking after or were built that are completely serverless. For example last year we built a completely serverless data lake for New South Wales Spatial Services.
How did you start using ParkMyCloud?
I personally had a particular need to solve a resource scheduling problem, so I checked out some MSP software options for scheduling and then jumped in and used it. ParkMyCloud had a simpler interface compared to some of the other products out there, and got the job done. It was an easy model to understand and consume, and it wasn’t going to cost an arm or leg. I liked that the pricing wasn’t based on percentages or anything complicated.
And then it kind of just started to snowball from there. We’ve got more and more customers using ParkMyCloud, and we’ve started to integrate it into our monitoring.
What was the specific use case that got you looking for a solution?
The customer wanted to be able to manage on and off schedules themselves. We have our own internal process that does some of that, but it wasn’t available to customers – there was no interface they could use to create, apply, or override their own schedules.
One customer was saying to us, look, we need to be able to turn it off potentially days at a time as opposed to just a regular schedule. And then sometimes we might want to be able to have it running all week if we’re doing load testing or vulnerability testing or something like that.
So we jumped on board with ParkMyCloud and signed this customer as a bit of a proof of concept. They were really happy with everything. They were able to schedule everything, group things together, and it made perfect sense for them from there.
Now we have many more customers using ParkMyCloud, and have hooks inside our internal monitoring system for ParkMyCloud so we can keep an eye on everything.
Has it saved you or your team any time to hand off the scheduling to the end-users?
Definitely. By being able to give end users control, they’re able to drive how and when they have things and can turn them on and off on an as-needed basis.
Before, one of our engineers would have to understand the problem, talk to the customer, grab those requirements, put it into a ticket, go in and put the scheduling into our system, test it to make sure that it worked, and close that ticket. Now it’s a completely different team that can take care of that – a team that is more customer aligned rather than the support team. They can just spin up a new account for ParkMyCloud. The automation takes care of hooking it into the AWS account with the right roles, etc., and the customer gets an email to get started with and they’re off and away.
Do you have any other feedback about your and your customers’ experience using ParkMyCloud?
The ParkMyCloud team has been really responsive which helped me integrate the product with Google’s suite for SSO. When we’ve raised suggestions, the team has been responsive supporting those initiatives and we’ve seen some of them come to fruition.
We also appreciate that the interface is easy to use and the pricing model is simple. It’s just really easy. That was the big key thing for us. There are other solutions and MSP software offerings out there that can do some sort of scheduling. But what tends to happen with these tools is that they end up doing many things and they don’t do them well. Software providers do better when they remember their original core focus and stick to that.
Exciting news: RightSizing is now generally available in ParkMyCloud! You can now use this method for automated cost optimization alongside scheduling to achieve an optimized cloud bill in AWS, Azure, and Google Cloud.
How it Works
When you RightSize an instance, you find the optimal virtual machine size and type for its workload.
Why is this necessary? Cloud providers offer a myriad of instancetypeoptions, which can make it difficult to select the right option for the needs of each and every one of your instances. Additionally, users often select the largest size and compute power available, whether it’s because they don’t know their workload needs in advance, don’t see cost as their problem, or “just in case”.
In fact, our analysis of instances being managed in ParkMyCloud showed that 95% of instances were operating at less than 50% average CPU, which means they are oversized and wasting money.
Now with ParkMyCloud’s RightSizing capability, you can quickly and easily – even automatically – resolve these sizing discrepancies to save money. ParkMyCloud uses your actual usage data to make these recommendations, and provides three recommendation options, which can include size changes, family/type changes, and modernization changes. Users can choose to accept these recommendations manually or schedule the changes to occur at a later date.
How Much You Can Save
A single instance change can save 50% or more of the cost. In the example shown here, ParkMyCloud recommends three possible changes for this instance, which would save 40-68% of the cost.
At scale, the savings potential can be dramatic. For example, one enterprise customer who beta-tested RightSizing found that their RightSizing recommendations added up to $82,775.60 in savings – an average of more than $90 per month/ more than $1,000 per year for every instance in their environment.
How to Get Started
Are you already using ParkMyCloud? If not, go ahead and register for a free trial. You’ll have full access for 14 days to try out ParkMyCloud in your own environment – including RightSizing.
If you already use ParkMyCloud, you’ll need to make sure you’re subscribed to the Pro or Enterprise tier to have access to this advanced feature.
Now it’s time to RightSize! Watch this video to see how you can get started in just 90 seconds:
ParkMyCloud now supports all three major cloud providers for resource RightSizing with the latest release of automated Azure Rightsizing!
How to Use ParkMyCloud’s Azure RightSizing to Automatically Optimize Costs
RightSizing is the process of matching a workload to the best supporting virtual machine to optimize costs. Why does it matter? Many virtual machines in the cloud are sized much larger than necessary for the workloads running on them. A recent analysis of the resources managed in the ParkMyCloud platform showed that the Average CPU across resources was merely 4.9%. Additionally, more than 95% of the resources sampled were operating at less than 50% average CPU. This means that they are provisioned for far more CPU than they actually need.
VM sizing and type selection has a drastic effect on cost –– one size down within the same VM family can reduce the cost by 50%, andwith changes between families or across more than one size, savings can be even greater. In the example shown here, ParkMyCloud has three RightSizing options, which could save the user 40-68% of the cost.
ParkMyCloud recommends VMs eligible for RightSizing; can take automated action to RightSize VMs, and can change VM families and modernize types.
Other New Features in ParkMyCloud
We’re constantly updating and improving the ParkMyCloud platform to bring you the best user experience and the most savings on your cloud environment. Here are some of the latest notable feature and support additions:
First, you’ll need to be an active ParkMyCloud customer or trial user. To set up an account, start a free trial and connect to your Azure account. You will have full access to the Enterprise Tier level features for 14 days.
Then, for customer and trial users alike, please contact us to enable the RightSizing beta, which supports Azure RightSizing as well as AWS and Google Cloud. In a few weeks, RightSizing will be made generally available for users on the new Pro tier as well as the Enterprise tier. Take advantage of this time to check it out!
On our first day as Turbonomic employees, our team had some great discussions with CTO Charles Crouchman about Turbonomic, ParkMyCloud, and the market for infrastructure automation tools. Charles explained his vision of the future of infrastructure automation, which parallels the automation trajectory that cars and other vehicles have been following for decades. It’s a comparison that’s useful in order to understand the goals of fully-automated cloud infrastructure – and the mindset of cloud users adopting this paradigm. (And of course, given our name, we’re all in on driving analogies!)
The Five Levels of Vehicle Autonomy
The idea of the five levels of vehicle autonomy – or six, if you include level 0 – is an idea that comes from the Society of Automotive Engineers.
The levels are as follows:
Level 0 – No Automation. The driver performs all driving tasks with no tools or assistance.
Level 1 – Driver Assistance.The vehicle is controlled by the driver, but the vehicle may have driver-assist features such as cruise control or an automated emergency brake.
Level 2 – Partial Automation or Occasional Self-Driving. The driver must remain in control and engaged in driving and monitoring, but the vehicle has combined automated functions such as acceleration and steering/lane position.
Level 3 – Conditional Automation or Limited Self-Driving. The driver is a necessity, but not required to monitor the environment. The vehicle monitors the road and traffic, and informs the driver when he or she must take control.
Level 4 – High Automation or Full Self-Driving Under Certain Conditions. The vehicle is capable of driving under certain conditions, such as urban ride-sharing, and the driver may have the option to control the vehicle. This is where airplanes are today – for the most part, they can fly themselves, but there’s always a human pilot present.
Level 5 – Full Automation or Full Self-Driving Under All Conditions. The vehicle can drive without a human driver or occupants under all conditions. This is an ideal, but right now, neither the technology nor the people are ready for this level of automation.
How These Levels Apply to Infrastructure Automation Tools
Now let’s take a look at how these levels apply to infrastructure automation tools and infrastructure:
Level 0 – No Automation. No tools in place.
Level 1 – Driver Assistance.Some level of script-based automation with limited applications, such as scripting the installation of an application so it’s just one user command, instead of hand-installing it.
Level 2 – Partial Automation or Occasional Self-Driving. In cloud infrastructure, this translates to having a monitoring system in place that can alert you to potential issues, but cannot take action to resolve those issues.
Level 3 – Conditional Automation or Limited Self-Driving. Think of this as traditional incident resolution or traditional orchestration. You can build specific automations to handle specific use cases, such as opening a ticket in a service desk, but you have to know what the event trigger is in order to automate a response.
Level 4 – High Automation or Full Self-Driving Under Certain Conditions.This is the step where analytics are integrated. A level-4 automated infrastructure system uses analytics to decide what to do. A human can monitor this, but is not needed to take action.
Level 5 – Full Automation or Full Self-Driving Under All Conditions. Full automation. Like in the case of vehicles, both the technology and the people are a long way from this nirvana.
So where are most cloud users in the process right now? There are cloud users and organizations all over this spectrum, which makes sense when you think about vehicle automation: there are early adopters who are perfectly willing to buy a Tesla, turn on auto-pilot, and let the car drive them to their destination. But, there are also plenty of laggards who are not ready to take their hands off the wheel, or even turn on cruise control.
Most public cloud users have at least elements of levels 1 and 2 via scripts and monitoring solutions. Many are at level 3, and with the most advanced platforms, organizations reach level 4. However, there is a barrier between levels 4 and 5: you will need an integrated hardware/software solution. The companies that are closest to full automation are the hyperscale cloud companies like Netflix, Facebook, and Google who have basically built their own proprietary stack including the hardware. This is where Kubernetes comes from and things like Netflix Scryer.
In our conversation, Charles said: “The thing getting in the way is heterogeneity, which is to say, most customers buy their hardware from one vendor, application software from another company, storage from another, cloud capacity from another, layer third-party software applications in there, use different development tools –– and none of these things were effectively built to be automated. So right now, automation needs to happen from outside the system, with adaptors into the systems. To get to level 5, the automation needs to be baked in from the system software through the application all the way up the stack.”
What Defines Early Adopters of Infrastructure Automation Tools
While there’s a wide scale of adoption in the market right now, there are a few indicators that can predict whether an organization or an individual will be open to infrastructure automation tools.
The first is a DevOps approach. If an organization using DevOps, they have already agreed to let software automate deployments, which means they’re accepting of automation in general – and likely to be open to more.
Another is whether resource management is centralized within the organization or not. If it is centralized, the team or department doing the management tends to be more open to automation and software solutions. If ownership is distributed throughout the organization, it’s naturally more difficult to make unified change.
Ultimately, the goal we should all be striving for is to use infrastructure automation tools to step up the levels of automated resource configuration and cost control. Through automation, we can reduce management time and room for human error to achieve optimized environments.
We recently held our first AWS webinar, featuring speakers from AWS, Sysco, and our CTO Bill Supernor. If you missed “How to Turn AWS Utilization Data into Automated Cost Control,” not to worry! You can watch a replay here.
Here are 9 takeaways from this AWS webinar – and more resources to learn about them:
Cost Optimization is one of five key pillars in the AWS Well-Architected Framework, and we’re glad to see AWS prioritizing controlled costs so highly. If you’re not already familiar with the Well-Architected Framework, learn more on the AWS site. The other pillars, by the way, include operational excellence, security, reliability, and performance efficiency.
Choose the right pricing modelfor your workload needs. Make sure to evaluate whether Reserved Instances are a good choice before committing, and don’t forget about Spot Instances either.
Tagging resources according to cost allocation was emphasized by AWS as important for decision making – and of course it is! You have to be able to categorize your resources to make decisions about them. Here’s more on how to improve cloud automation through tagging.
Use AWS CloudWatch – similarly, use your CloudWatch data to optimize your environment. AWS is collecting data about your usage whether you’re looking at it or not – so put it to work!
Bagels work– Sysco Foods’ Kurt Brochu shared that he could motivate his team to show up for cost optimization trainings by providing bagels. Sometimes it takes a bit of prodding to get team members not directly responsible for budget to care about cost, so don’t be afraid to get creative.
Use Gamification as a motivator – similarly, by turning cost savings into a race or other competition, you can awake interest that might otherwise be hard to find.
There are plenty more AWS webinars – AWS partners frequently hold webinars in conjunction with the cloud provider. One of the best places to learn about them is the @AWS_Partners Twitter channel.
Watch the replay of our AWS webinar for the full story – and let us know in the comments below what else you’d like to learn about in future webinars!