We’re happy to announce that ParkMyCloud now supports Alibaba Cloud!
Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) users have saved millions of dollars on their cloud bills using ParkMyCloud’s automated cloud cost optimization platform. Customers like McDonald’s, Sysco, and Unilever use ParkMyCloud to automatically turn off idle cloud resources as part of their DevOps process.
Now, Alibaba Cloud customers can do the same.
Alibaba Cloud is experiencing rapid customer adoption and growth – in the 4th quarter of last year, they saw over 100% growth, with more than 300 products and features launched. The company is clearly expanding their horizons beyond retail and putting a focus on innovation and development in the cloud space – both in China where their core customer base is located, and throughout the world as companies globally choose Alibaba as their primary cloud provider or as part of a multi-cloud strategy.
But the real reason we’re here is to help cloud users solve the enormous problem of cloud waste.
We estimate that Alibaba users will waste $552 million on idle cloud resources this year – that’s $1.5 million per day that could easily be saved with automated cost optimization in place. There’s no time to lose in getting cost control measures in place.
Hitachi ID Systems recently reached their first ParkMyCloud birthday – to celebrate, we chatted with Patrick McMaster about how they optimize training infrastructure and why he and his team said “We honestly couldn’t be happier with ParkMyCloud.”
Can you start by telling me about Hitachi ID Systems and what you and your team do within the company?
Hitachi ID Systems makes identity and access management (IAM) software. I am the training coordinator, so I handle getting clients and potential partners up to speed with how our software works, how to install it, how to administrate it, etc. For those who are more interested in learning about software, we set them up with a virtual environment and course materials or an instructor to get them up to speed with how the software works.
Can you describe how you’re using public cloud?
We use AWS exclusively. When we advertise that we’re running a course a few months ahead of time, our infrastructure starts seeing the registrations and will start creating VMs, applying patches, getting the latest version of the appropriate software installers on the desktop and getting everything ready for the students, who will be accessing geographically-local AWS infrastructure.
In the past, everything for this online training was very manual. We on the training team would spin up the VMs manually, do the updates manually, and send the information to the potential students., Then when the course was over we would go through and do the reverse – shutting the elements down and turning off the virtual machine on AWS.
What does the supporting training infrastructure in AWS look like?
We have a number of VMs running per student or team that only need to be active during the team’s local business hours, plus some additional supporting infrastructure which is required 24/7. We started to realize as we got more students and began offering self-paced training that our AWS fees were increasing from the 24/7 access we were providing, but also just the management of keeping track of which students are where, when they should be brought into the system, when they should be shut down, etc. We needed to find a solution pretty quickly as we experienced that period of rapid growth.
How did that lead you to finding ParkMyCloud?
We knew we needed to automate the manual processes for this. Of course, lots of organizations tend to come up with solutions internally first. We’re a software company, so we had the talent for that, but we never have enough time. I’ve come to terms more and more every year with the benefits of delegating to the other sources. I realized that we are probably not the first organization to have this problem, so I Googled and found ParkMyCloud.
It became quickly evident that the features that you offered were exactly what we were looking for.
Can you describe your experience as a ParkMyCloud user so far?
Sure! So just before our demo of ParkMyCloud, we were fighting with this issue of trying to figure out how we can manage multiple time zones and multiple geographic locations, and not pay for that time that VMs are just spun up.
Then we went through the ParkMyCloud demo process and started our trial. We connected to our system and looked at ways to set up different schedules and pull information from AWS. There was definitely a moment where everyone in the room looked each other and said, “we must be missing something” – there had to be some additional steps we hadn’t thought out because it seemed too easy to work. But it really was that easy.
It just took a week of monitoring to make sure everything was turning off when it was supposed to – the bulk of our effort was really in that first week, and the time we need to spend in the interface is so small. We can go into ParkMyCloud’s dashboard and make exceptions to the schedule when needed, but the time that we actually spend thinking about these things is now about 2 hours a week, whereas before it was something that members of our staff might struggle with for 1-2 days. It’s been a huge improvement.
We did some calculations just in terms of uptime versus what we were doing before, and having the different schedules at our disposal and being able to spend that one week coming up with every scenario we could come up with was time well-spent. Now there are very few exceptions. I don’t think we’ve had to create a new schedule in a long time. Everything is organized logically, it’s very easy for us to find everything we need.
Who is responsible for tracking your AWS spending in the organization? Have they had any feedback?
Our finance department. Since we started using ParkMyCloud, it’s been very very quiet. No news is good news from finance. We are saving about 40% of our bill.
Do you have any other cloud cost savings measures in place?
Not for this training infrastructure. We have a pretty unique use case here. Our next steps are going to be more towards automatic termination, automatic spinning things up, more time-saving measures rather than cost.
This summer ParkMyCloud is working on instance rightsizing, if that’s something that would be helpful for you.
That’s definitely something that we could use. We are always trying to find better ways of doing things.
We have been talking about idle cloud resources for several years now. Typically, we’re talking about instances purchased On Demand that you’re using for non-production purposes like development, testing, QA, staging, etc. These resources can be “parked” when they’re not being used, such as on nights and weekend, saving 65% or more per resource each month. What we haven’t talked much about is how the problem of idle cloud resources extends beyond just your typical virtual machine.
Why Idle Cloud Resources are a Problem
If you think about it, the problem is pretty straightforward: if a resource is idle, you’re paying your cloud provider for something you’re not actually using. This adds up.
Most non-production resources can be parked about 65% of the time, that is, parked 12 hours per day and all day on weekends (this is confirmed by looking at the resources parked in ParkMyCloud – they’re scheduled to be off just under 65% of the time.) We see that our customers are paying their cloud providers an average list price of $220 per month for their instances. If you’re currently paying $220 per month for an instance and leaving it running all the time, that means you’re wasting $143 per instance per month.
Maybe that doesn’t sound like much. But if that’s the case for 10 instances, you’re wasting $1,430 per month. One hundred instances? You’re up to a bill of $14,300 for time you’re not using. And that’s just a simple micro example. At a macro level that’s literally billions of dollars in wasted cloud spend.
4 Types of Idle Cloud Resources
So what kinds of resources are typically left idle, consuming your budget? Let’s dig into that, looking at the big three cloud providers — Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
On Demand Instances/VMs – this is the core of the conversation, and what we’ve addressed above. On demand resources – and their associated scale groups – are frequently left running when they’re not being used, especially those used for non-production purposes.
Relational Databases – there’s no doubt that databases are frequently left running when not needed as well, in similar circumstances to the On Demand resources. The problem is whether you can park them to cut back on wasted spend. AWS allows you to park certain types of its RDS service, however, you can not park like idle database services in Azure (SQL Database) or GCP (SQL). In this case, you should review your database infrastructure regularly and terminate anything unnecessary – or change to a smaller size if possible.
Load Balancers – AWS Elastic Load Balancers (ELB) cannot be stopped (or parked), so to avoid getting billed for the time you need to remove it. The same can be said for Azure Load Balancer and GCP Load Balancers. Alerts can be set up in Cloudwatch/Azure Metrics/Google Stackdriver when you have a load balancer with no instances, so be sure to make use of those alerts.
Containers – optimizing container use is a project of its own, but there’s no doubt that container services can be a source of waste. In fact, we are evaluating the ability for ParkMyCloud to park container services including ECS and EKS from AWS, ACS and AKS from Azure, and GKE from GCP, and the ability to prune and park the underlying hosts. In the meantime, you’ll want to regularly review the usage of your containers and the utilization of the infrastructure, especially in non-production environments.
Cloud waste is a billion-dollar problem facing businesses today. Make sure you’re turning off idle cloud resources in your environment, by parking those that can be stopped and eliminating those that can’t, to do your part in optimizing cloud spend.
We recently discussed how orphaned volumes and snapshots contribute to cloud waste and what you can do about it, but those are just two examples of orphaned cloud resources that result in unnecessary charges. The public cloud is a pay-as-you-go utility, requiring full visibility of specific infrastructure – you don’t want to be charged for resources you aren’t using. Here are other types of orphaned cloud resources that contribute to cloud waste (and cost you money):
Unassociated Elastic IPs
Elastic IPs are reserved public IP addresses designed for dynamic cloud computing in AWS. As a static IPv4 address associated with your AWS account, Elastic IPs can continue running an EC2 instance, even if it is stopped and restarted, by quickly remapping the address to another one of your instances. You can allocate an Elastic IP address to any EC2 instance in a given region, until you decide to release it.
The advantage of having an Elastic IP (EIP) is the ability to mask the failure of an EC2 instance, but if you do not associate the address to your account – you’re still getting charged. To avoid incurring a needless hourly charge from AWS, remember to release any unassociated IPs you no longer need.
Elastic Load Balancers (with no instances)
Cloud load balancing allows users to distribute workloads and traffic with the benefit of the cloud’s scalability. All major cloud providers offer some type of load balancing – AWS users can balance workloads and distribute traffic among EC2 instances with its Elastic Load Balancer, Google Cloud can distribute traffic between VM instances with Google Cloud Load Balancing, and Azure’s Load Balancer distributes traffic across multiple data centers.
An AWS Elastic Load Balancer (ELB) will incur charges to your bill as long as it’s configured with your account. Like with Elastic IPs, whether you’re using it or not – you’re paying. If you have no instances associated with your ELB, delete to avoid paying needless charges on your monthly bill.
Unused Machine Images (AMIs)
A Machine Image provides the information required to launch an instance, which is a virtual server in the cloud. In AWS they’re called AMIs, in Azure they’re Managed Images, and in Google Cloud Platform they’re Custom Images.
As part of your measures to reduce unnecessary costs from orphaned volumes, delete unused machine images when you no longer need them. Unless deleted, the snapshot that was created when the image was first created will continue to incur storage costs.
One of the growing pains that organizations face is the management of isolated pools of data in their cloud environment. Fragmented storage can result from data coming from a number of sources used by applications and business processes. Object Storage was designed to break down silos into scalable, cost-effective storage to store data in its native format. AWS offers object storage solutions like Amazon S3 and Amazon Glacier, Google has Google Cloud Storage, and Azure calls its solution Azure Blob Storage. All options help you manage your storage in one place, keeping your data organized and your business more cost effective.
Although object storage in and of itself is a cost effective solution, there are still ways to optimize and reduce costs within this solution. Delete files you no longer need so that you’re not paying for them. Delete unused files which can be recreated. In S3, use the “lifecycle” feature to delete or overwrite older versions of data. Clean up incomplete uploads that were interrupted, resulting in partial objects that are taking up needless space. And compress your data before storing to give you better performance and reduce your storage requirements.
How to Avoid Wasted Spend on Orphaned Cloud Resources
Don’t let forgotten resources waste money on your cloud bill. Put a stop to cloud waste by eliminating orphaned cloud resources and inactive storage, saving space, time, and money in the process. Remember to:
Release unassociated IPs you no longer need.
Remove Elastic Load Balancers with no instances attached.
Delete unused machine images when you no longer need them.
Keep object storage minimal – optimize by “cleaning up” regularly, removing files you don’t need.
The premise of the cloud and the resources available to you were meant to be cost effective, but it’s up to you keep costs in check. Optimize your cloud spend with visibility, management, and cost automation tools like ParkMyCloud to get the most out of your cloud environment.
You’ve gone full-blown DevOps, drank the Agile Kool-Aid, cloudified everything, and turned your monolith to microservices — so why have all of your old monolith costs turned into even bigger microservices costs? There are a few common reasons this happens, and some straightforward first steps to get microservices cost control in place.
Why Monolith to Microservices Drives Costs Up
As companies and departments adapt to modern software development processes and utilize the latest technologies, they assume they’re saving money – or forget to think about it altogether. Smaller applications and services should come with more savings opportunities, but complexity and rapidly-evolving environments can actually make the costs skyrocket. Sometimes, it’s happening right under your nose, but the costs are so hard to compile that you don’t even know it’s happening until it’s too late.
The same thing that makes microservices attractive — smaller pieces of infrastructure that can work independently from each other — can also be the main reason that costs spiral out of control. Isolated systems, with their own costs, maintenance, upgrades, and underlying architecture, can each look cheaper than the monolithic system you were running before, but can skyrocket in cost when aggregated.
How to Control Microservices Costs
If your microservices costs are already out of control, there are a few easy first steps to reining them in.
Keep It Simple
As with many new trends, there is a tendency to jump right in and switch everything to the new hotness. Having a drastic cutover, while scrapping all of your old code, can be refreshing and damaging all at the same time. It makes it hard to keep track of everything, so costs can run rampant while you and your team are struggling just to comprehend what pieces are where. By keeping some of what you already have, but slowly creating new functionality in a microservices model, you can maintain a baseline while focusing on costs and infrastructure of your new code.
The other way to keep it simple is to keep each microservice extremely limited in scope. If a microservice does just one thing, without a bunch of bells and whistles, it’s much easier to see if costs are rising and make the infrastructure match the use case. Additional opportunities for using PaaS or picking a cloud provider that fits your needs can really help maximize utilization.
Scalability and Bursting
Microservices architectures, by the very nature of their design, allow you to optimize individual pieces to minimize bottlenecks. This optimization can also include cost optimization of individual components, even to the point of having idle pieces turned completely off until they are needed. Other pieces might be on, but scaled down to the bare minimum, then rapidly scale out when demand runs high. A fluctuating architecture sounds complex, but can really help keep costs down when load is low.
Along with a microservices architecture, you may start having certain users and departments be responsible for just a piece of the system. With that in mind, cloud providers and platform tools can help you separate users to only access the systems and infrastructure they are working on so they can focus on the operation (and costs) of that piece. This allows you to give individual users the role that is necessary for minimal access controls, while still allowing them to get their jobs done.
Ordered Start/Stop and Automation with ParkMyCloud
ParkMyCloud is all about cost control, so we’ve started putting together a cost-savings plan for our customers who are moving from monolith to microservices.
First, they should use ParkMyCloud’s Logical Groups to put multiple instances and databases into a single entity with an ordered list. This way, your users do not have to remember multiple servers to start for their application – instead, they can start one group with a single click. This can help eliminate the support tickets that are due to parts of the system not running.
Additionally, use Logical Groups to set start delays and stop delays between nodes of the group. With delays, ParkMyCloud will know to start database A, then wait 10 minutes before starting instance B, to ensure the database is up and ready to accept connections. Similarly, you can make sure other microservices are shut down before finally shutting down the database.
Everything you can do in the ParkMyCloud user interface can also be done through the ParkMyCloud REST API. This means that you can temporarily override schedules, toggle instances to turn off or on, or change team memberships programmatically. In a microservices setup, you might have certain pieces that are idle for large portions of the day. With the ParkMyCloud API, you could have those nodes turned off on a schedule to save money, then have a separate microservice call the API to turn the node on when it’s needed.
The Goal: Continuous Cost Control
Moving from monolith to microservices can be a huge factor in a successful software development practice. Don’t let cost be a limiting factor – practice continuous cost control, no matter what architecture you choose. By putting a few costs control measures in place with ParkMyCloud, along with some automation and user management, you can make sure your new applications are not only modern, but also cost-effective.
Today we’d like to announce a new Microsoft Teams bot that allows you to fully interact with ParkMyCloud directly through your chat window, without having to access the web GUI. By combining this chatbot with a direct notifications feed of any ParkMyCloud activities through our webhook integration, you can manage your continuous cost control from the Microsoft Teams channels you live in every day — making it easy to save 65% or more on your instance costs.
Organizations who are utilizing DevOps principles are increasingly utilizing ChatOps to manipulate their environments and provide a self-service platform to access the servers and databases they require for their work. There are a few different chat systems and bot platforms available – we also have a chat bot for Slack – but one that is growing rapidly in popularity is Microsoft Teams.
By setting up the Microsoft Teams bot to interact with your ParkMyCloud account, you can allow users to:
Temporarily override schedules on parked instances
Toggle instances to turn off or on as needed
Combine this with notifications from ParkMyCloud, and you can have full visibility into your cost control initiatives right from your standard Microsoft Teams chat channels. Notifications allow you to have ParkMyCloud post messages for things like schedule changes or instances that are being turned off automatically.
Now, with the new ParkMyCloud Teams bot, you can reply back to those notifications to:
Snooze the schedule
Turn a system back on temporarily
Assign a new schedule.
The chatbot is open-source, so you can feel free to modify the bot as necessary to fit your environment or use cases. It’s written in NodeJS using the botbuilder library from Microsoft, but even if you’re not a NodeJS expert, we tried to make it easy to edit the commands and responses. We’d love to have you send your ideas and modifications back to us for rapid improvement.
If you haven’t already signed up for ParkMyCloud to help save you 65% on your cloud bills, then start a free trial and get the Microsoft Teams bot hooked up for easy ChatOps control. You’ll find that ParkMyCloud can make continuous cost control easy and help reduce your cloud spend, all while integrating with your favorite DevOps tools.