Back to Azure – let’s take a look at the new functionality.
How You Can Park Azure Scale Sets
In ParkMyCloud, you can now manage and park Azure scale sets, both with and without autoscaling, to turn them off or to a “low” state when not needed to save money. When you set a parking schedule on a scale set, you have the option to set a straightforward “on/off” schedule — when parked, the maximum number of resources is 0 and therefore the group is fully parked. Or if you prefer, set your own preferred number of resources for a “low” rather than “off” state.
While we’re talking to our Microsoft fans — don’t miss the Microsoft Teams bot we made so you can control ParkMyCloud right from your chat window! ChatOps is fun, and this bot can streamline your workday by saving you a trip to the ParkMyCloud console.
ParkMyCloud Users: Enable Scale Sets and Get Parking
Once you’ve done that, you can start parking scale sets. You can filter your dashboard to show only scale groups – on the left menu under “Resources” click “Auto Scaling Groups” to filter to just that type of resource. You can select a group and put a parking schedule on it, just like an individual instance.
As mentioned above, you can customize the amount of resources in the group in the high/low states. For the selected group, click the arrow on the far right to open the resource detail screen. You will be able to set a “desired” value of resources for the group at start and at stop.
Note that if your scale sets have multiple scaling profiles, they won’t be parkable and will be denoted with the “unparkable” icon. The number of “Autoscale Profiles” assigned to an Azure scale set is listed on the resource details screen.
New Users: Get Started
If you don’t use ParkMyCloud yet, it’s easy to get started and start saving 65% or more on your cloud costs. We recently upgraded our 14-day free trial to provide Enterprise tier access, so you’ll get to try out everything from user import/export feature to database parking to SmartParking, with unlimited users, teams, and cloud credentials. Get started now.
Leading Cloud Cost Optimization Platform Expands Savings on Public Cloud Resources
May 31, 2018 (Dulles, VA) – ParkMyCloud, the leading enterprise platform for continuous cost control in public cloud, announced today that it has released cost optimization support for Microsoft Azure virtual machine scale sets and Google Cloud Platform managed instance groups.
The ParkMyCloud platform helps Amazon Web Services (AWS), Microsoft Azure (Azure), and Google Cloud Platform (GCP) customers save money on cloud resources by automatically integrating cost control into their DevOps processes. ParkMyCloud saves money by scheduling cloud resources to turn off when they are not needed – which they call “parking”.
Azure scale sets and GCP managed instance groups are groups of cloud resources that are frequently used for redundancy and scaling purposes. For testing and development, common practice is to set up a non-production network architecture that mirrors production. All too often, the non-production environment is left running, wasting money on resources that aren’t being used. With ParkMyCloud cost control in place, users can automate “off” or “scaled down” schedules for these resources, ensuring that they only pay for services they are actually using.
“Customers using scale groups in public cloud are typically savvy users who are increasingly cost conscious,” said Bill Supernor, ParkMyCloud CTO. “With each release, we are expanding ParkMyCloud’s automation engine to support the cloud resources our customers are using. This allows them to easily incorporate cost optimization with their DevOps process.”
Earlier this year, ParkMyCloud released automated usage-based cost optimization called “SmartParking” for AWS, Azure and GCP. In the coming months, ParkMyCloud plans to release support for Alibaba Cloud as well as additional resource types in AWS, Azure, and GCP.
ParkMyCloud is a SaaS platform that automatically identifies and eliminates public cloud resource waste, reducing spending by 65% or more — think “Nest for the cloud.” AWS, Azure and Google users such as McDonald’s, Sysco Foods, Unilever, Avid, and Sage Software have used ParkMyCloud to cut their cloud spending by millions of dollars. ParkMyCloud helps companies like these optimize and govern cloud usage by integrating cost control into their DevOps processes. For more information, visit https://www.parkmycloud.com.
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.
The time is ripe to take a fresh look at the advantages of multi-cloud. In the past 12 months, we’ve seen a huge increase in the number of our customers who use multiple public clouds – now more than 20% of our customers use multiple public clouds. With this trend in mind, we wanted to take a look at the positives of a multi-cloud strategy as well as the risks – because of course there’s no “easy button.”
What is Multi-Cloud?
First off, let’s define multi-cloud. Clearly, we’re talking about using one or more clouds, but clouds come in different flavors. For example, multi-cloud incorporates the idea of hybrid cloud – a mix of public and private Clouds. But multi-cloud can also mean two or more public clouds or two or more private clouds.
According to the RightScale 2018 State of the Cloud Report, 81% of Enterprises have a multi-cloud strategy:
What are the advantages of multi-cloud?
So why are businesses heading this direction with their infrastructure? Simple reasons include the following:
Optimization – place your workloads to optimize for cost and performance
Cloud providers’ unique capabilities – take advantage of offerings in AI, IOT, Machine Learning, and more
When I asked our CTO what he sees as the advantages of a multi-cloud strategy, he highlighted risk management. ParkMyCloud’s own platform was born in the cloud, we run on AWS, we have a multi-region architecture with redundancy (let’s call this multi-cloud ‘light’), and if we went multi-cloud we would leverage another public cloud for risk mitigation.
Specifically, risk management from the perspective of one vendor having an infrastructure meltdown or attack. AWS had an issue about 15 months ago when S3 was offline in US-East-1 region for 5+ hours affecting many companies, large and small, and software from web apps to smartphones apps were affected (including ours). There have also been issues of certain AWS regions getting a DDoS attack that have affected service availability.
Having a backup to another cloud service provider (CSP) or Private Cloud in these cases could have ensured 100% uptime. In the case of Alibaba and other cloud vendors, they may have a much stronger presence in certain geographic regions due to a long term presence. When any of the vendors just start getting a toe-hold in a region, their environment has minimal redundancy and safeguards in place that provide the desired high-availability, so another provider in the same region may be safer from that availability perspective.
Do the advantages of multi-cloud outweigh the challenges?
Now let’s say you want to go multi-cloud, what does this mean to you? From our own experience integrating with AWS, Azure, and Google Cloud, we’ve seen that each cloud has its own set of interfaces and own challenges. It is not a “write once, runs everywhere” situation between the vendors, and any cloud or network management utility system needs to do the work to provide deep integration with each CSP.
Further, the nuances of configuring and managing each CSP require both broad and deep knowledge, and it is rare to find employees with the essential expertise for multiple clouds – so more staff is needed to manage multi-cloud with confidence that it is being done in a way that is both secure and highly available. With everyone trying to play catch-up with AWS, and with AWS itself evolving at a breakneck pace, it is very difficult for an individual or organization to best utilize one CSP, let alone multiple clouds.
Things like a common container environment can help mitigate these issues somewhat by isolating engineers from the nuances of virtual machine management, but the issues of network, infrastructure, cost optimization, security, and availability remain very CSP-specific.
On paper there are advantages of having a multi-cloud strategy. In practice, like many things, it ain’t easy.
Given that spring is very much in the air – at least it is here in Northern Virginia – our attention has turned to tidying up the yard and getting things in good shape for summer. While things are not so seasonally-focused in the world of cloud, the metaphor of taking time out to clean things up applies to unused cloud resources as well. We have even seen some call this ‘cloud pruning’ (not to be confused with the Japanese gardening method).
Cloud pruning is important for improving both cost and performance of your infrastructure. So what are some of the ways you can go about cleaning up, optimizing, and ensuring that our cloud environments are in great shape?
Delete Old Snapshots
Let’s start with focusing on items that we no longer need. One of the most common types of unused cloud resources is old Snapshots. These are your old EBS volumes on AWS, your storage disks (blobs) on Azure, and persistent disks on GCP. If you have had some form of backup strategy then it’s likely that you will understand the need to manage the number of snapshots you keep for a particular volume, and the need to delete older, unneeded snapshots. Cleaning these up immediately helps save on your storage costs and there are a number of best practices documenting how to streamline this process as well as a number of free and paid-for tools to help support this process.
Delete Old Machine Images
A Machine Image provides the information required to launch an instance, which is a virtual server in the cloud. In AWS these are called AMIs, in Azure they’re called Managed Images, and in GCP Custom Images. When these images are no longer needed, it is possible to deregister them. However, depending on your configuration you are likely to continue to incur costs, as typically the snapshot that was created when the image was first created will continue to incur storage costs. Therefore, if you are finished with an AMI, be sure to ensure that you also delete its accompanying snapshot. Managing your old AMIs does require work, but there are a number of methods to streamline these processes made available both by the cloud providers as well as third-party vendors to manage this type of unused cloud resources.
With the widespread adoption of containers in the last few years and much of the focus on their specific benefits, few have paid attention to ensuring these containers are optimized for performance and cost. One of the most effective ways to maximize the benefits of containers is to host multiple containerized application workloads within a single larger instance (typically large or x-large VM) rather than on a number of smaller, separate VMs. In particular, this is something you could utilize in your dev and test environments rather than in production, where you may just have one machine available to deploy to. As containerization continues to evolve, services such as AWS’s Fargate are enabling much more control of the resources required to run your containers beyond what is available today using traditional VMs. In particular, the ability to specify the exact CPU and memory your code requires (and thus the amount you pay) scales exactly with how many containers you are running.
So alongside pruning your trees or sweeping your deck and taking care of your outside spaces this spring, remember to take a look around your cloud environment and look for opportunities to remove unused cloud resources to optimize not only for cost, but also performance.