Enterprises Can Reduce Spend by 75% with Data-Driven Optimization
May 30, 2019 (Dulles, VA) – ParkMyCloud, provider of the leading enterprise platform for continuous cost control in public cloud, has announced that its platform now recommends resource “RightSizing” changes for cost optimization on Amazon Web Services (AWS) and Google Cloud Platform (GCP). These changes can save up to 75% on oversized instances and databases.
The problem posed by oversized resources is significant. ParkMyCloud data shows that 95% of resources under the platform’s management are operating at less than 50% average CPU, showing patterns of significant underutilization and overprovisioning. Moving a virtual machine size down one tier will save 50%. Many instances are so overprovisioned that changes by two or more tiers make more sense, allowing for 75% or higher savings. Users can also save money by modernizing instances. The cloud providers incentivize instance modernization by pricing the newest generations the lowest.
RightSizing joins ParkMyCloud’s “parking” functionality, which automatically schedules non-production cloud resources, such as those used for development, testing, staging, and QA, to turn off when they’re not needed. With a typical schedule that parks a resource for 12 hours each night and on weekends, users can save 65% of the cost of their resources. Combined with rightsizing, this means that an average cloud user is poised to reduce overall costs in their cloud environment from 50-80% or more.
“Not only can rightsizing provide significant savings, but it takes the burden of tedious and murky decisions off the shoulders of users,” said ParkMyCloud Founder Jay Chapel. “The real advantage for enterprise cloud users is automation.”
To get started, public cloud users should visit www.parkmycloud.com/free-trial to start a free 14-day trial of the product and to receive their own RightSizing recommendations.
ParkMyCloud provides an easy-to-use platform that helps enterprises automatically identify and eliminate wasted cloud spend. More than 1,000 enterprises around the world – including Unilever, Sysco, Hitachi ID Systems, Sage Software, and National Geographic – trust ParkMyCloud to cut their cloud spend by millions of dollars annually. ParkMyCloud’s SaaS offering allows enterprises to easily manage, govern, and optimize their spend across multiple public clouds. For more information, visit www.parkmycloud.com.
Katy Stalcup, ParkMyCloud
Today, we’re happy to share the latest in cost optimization: ParkMyCloud now makes RightSizing recommendations for your resources in AWS and Google Cloud.
Optimize Your Cloud Infrastructure with Automated RightSizing
Choosing the right instance type for cloud resources is difficult. The major providers offer a huge range of options, each optimized for different capabilities, and a variety of sizes within each instance family. It can be hard to predict in advance what you’ll need. And indeed, our data shows that 95% of instances are operating at less than 50% average CPU – that is to say, most of them are oversized.
Why does it matter? Oversizing is a huge waste of money. Downsizing by one instance size saves 50% of the cost – and two sizes down saves 75%. You can also save money by modernizing instances. The cloud providers incentivize instance modernization by pricing the newest generations the lowest.
ParkMyCloud will not only recommend but also help you take action to resize your instances, move families, and/or modernize as needed so that you can optimize performance with the lowest cost.
What Else is New?
We’re always enhancing and improving ParkMyCloud to make it work best for you. Here’s what else is new:
What’s up next? Azure RightSizing, scheduled resizing and optimization for container services.
How to Get Started
If you’re new to ParkMyCloud, you’ll want to start with a 14-day free trial. Once you connect to your cloud provider, you’ll be able to start managing your instances. You’ll have access to the full set of Enterprise Tier features for the length of the trial, and after 14 days you can choose the free tier or a more advanced tier.
To enable RightSizing, both new and current users should contact us as this feature is currently in beta. Once that’s active, go to the Recommendations screen and select the RightSizing tab to see all sizing recommendations, which you can then click to apply. The resource will be resized the next time it’s restarted. It’s that easy!
Today’s entry into our exploration of public cloud prices focuses on AWS Lambda pricing.
Low costs are often cited as a benefit of using serverless. A recent survey showed that companies saved an average of 4 developer workdays per month by adopting serverless, and 21% of companies reported cost reduction as a main benefit. But why aren’t 100% of companies reporting cost savings?
In this article, we’ll take a look at the Lambda pricing model, and some things you need to keep in mind when estimating costs for serverless infrastructure.
How AWS Lambda Pricing Works
AWS Lambda pricing is based on what you use. There are two major factors that contribute to the calculation of “what you use”:
- Requests — Lambda counts a request each time it starts executing in response to an event notification or invoke call. Each request costs $0.0000002.
- Duration — Duration is calculated from the time your code begins executing until it returns or otherwise terminates, rounded up to the nearest 100ms. But, the price is not charged per second. Rather, it is charged per GB-second, which is the duration in seconds multiplied by the maximum memory size in GB. Every GB-second costs $0.0000166667.
There is a free tier available to all Lambda users — and note that this is unrelated to your regular AWS free tier usage. Every user gets 1 million requests per month and 400,000 GB-Seconds per month, for free.
In addition to requests and duration, you will also be charged for additional AWS services used or data transfers – regardless of whether you’re using Lambda’s free tier. For many applications, API requests and data transfers will cost significantly more than the AWS Lambda core pricing.
Why AWS Lambda Pricing is So Confusing
Ultimately, Lambda pricing is confusing and hard to predict. Here’s why:
- Granularity — the fact that cost is per each function execution makes it difficult to estimate compared to server-based pricing models. Thinking in terms of iterations of a microservices script requires some mental gymnastics.
- Multiplicative costs — the fact that the duration charges are based on a calculation makes it harder to conceptualize and more variable than other pricing models – and if both duration and memory change, the costs increase quickly.
- Additional charges — at a cost of $3.50 per million calls, AWS API Gateway charges often make up a significant portion of the cost to run serverless – plus data transfers and other “on top” costs.
- Wait time — if a function makes an outgoing call and sits idle waiting for the result, you’ll be charged for the wait time. Be sure to set a maximum function execution time to prevent this from driving up costs (as well as a maximum memory size).
- Code maintenance — it’s a murkier area when it comes to costs, but with more functions come more lines of code to maintain.
Of course, there are several AWS Lambda pricing calculators out there to help estimate costs — ranging from the simpler that include only the number of executions, memory allocation, and average duration (examples from Dashbird and A Cloud Guru) to those incorporating language, activity patterns, and EC2 comparisons from the cheekily named servers.lol.
AWS Lambda Costs Are Just One Factor
There are plenty of benefits to serverless, from low latency to scalability to simple deployment. However, alongside vendor lock-in, applications with long or variable execution times, and control over application performance, cost is another reason why serverless may not replace traditional servers for all situations.
Among the many ways to purchase and consume Azure resources are Azure low priority VMs. These virtual machines are compute instances allocated from spare capacity, offered at a highly discounted rate compared to “on demand” VMs. This means they can be a great option for cost savings – for the right workloads. And we love cost savings! Here’s what you need to know about this purchasing option.
How Azure Low Priority VMs Work
The great part about these virtual machines is the price: it’s quite attractive with a fixed discount of 60-80% compared to on-demand. The “low priority” part means that these VMs can be “evicted” for higher priority jobs, which makes them suitable for fault-tolerant applications such as batch processing, rendering, testing, some dev/test workloads, containerized applications, etc.
Low priority VMs are available through Azure Batch and VM scale sets. Through Azure Batch, you can run jobs and tasks across compute pools called “batch pools”. Since batch jobs consist of discrete tasks run using multiple VMs, they are a good fit to take advantage of low priority VMs.
On the other hand, VM scale sets scale up to meet demand, and when used with low priority VMs, will only allocate when capacity is available. To deploy low priority VMs on scale sets, you can use the Azure portal, Azure CLI, Azure PowerShell, or Azure Resource Manager templates.
When it comes to eviction, you have two policy options to choose between:
- Stop/Deallocate (default) – when evicted, the VM is deallocated, but you keep (and pay for) underlying disks. This is ideal for cases where the state is stored on disks.
- Delete – when evicted, the VM and underlying disks are deleted. This is the recommended option for auto scaling because deallocated instances are counted against your capacity count on the scale set.
Azure Low Priority VMs vs. AWS Spot Instances
So are low priority VMs the same as AWS Spot Instances? In some ways, yes: both options allow you to purchase excess capacity at a discounted rate.
However, there are a few key differences between these options:
- Fixed vs. variable pricing – AWS spot instances have variable pricing while Azure low priority VMs have a fixed price as listed on the website
- Integration & flexibility – AWS’s offering is better integrated into their general environment, while Azure offers limited options for low priority VMs (for example, you can’t launch a single instance) with limited integration to other Azure services.
- Visibility – AWS has broad availability of spot instances as well as a Spot Instance Advisor to help users predict availability and interruptibility. On the other hand, Azure has lower visibility into the available capacity, so it’s hard to predict if/when your workloads will run.
Should You Use Azure Low Priority VMs?
If you have fault-tolerant batch processing jobs, then yes, low priority VMs are worth a try to see if they work well for you. If you’ve used these VMs, we’re curious to hear your feedback. Have you had issues with availability? Does the lack of integrations cause any problems for you? Are you happy with the cost savings you’re getting? Let us know in the comments below.
March 28, 2019 (Dulles, VA) – ParkMyCloud, provider of the leading enterprise platform for continuous cost optimization in the cloud, announced today that it has achieved Amazon Web Services (AWS) Cloud Management Tools Competency status. This designation recognizes that ParkMyCloud assists AWS customers in provisioning and managing AWS workloads through specialized solutions for administering & provisioning, managing, and optimizing AWS resources.
Achieving the AWS Cloud Management Tools Competency differentiates ParkMyCloud as an AWS Partner Network (APN) member that provides specialized demonstrated technical proficiency and proven customer success with specific focus on workloads based on Resource & Cost Optimization. To receive the designation, APN Partners must possess deep AWS expertise and deliver solutions seamlessly on AWS.
“We live and breathe cloud cost optimization,” said Jay Chapel, ParkMyCloud CEO. “Achieving AWS Cloud Management Tools Competency status validates the purpose we have served since day one: helping companies automate cost control while leveraging the agility and breadth of services that AWS provides.”
AWS is enabling scalable, flexible, and cost-effective solutions from startups to global enterprises. To support the seamless integration and deployment of these solutions, AWS established the AWS Competency Program to help customers identify Consulting and Technology APN Partners with deep industry experience and expertise.
ParkMyCloud helps enterprises automatically identify and eliminate wasted cloud spend through resource rightsizing and automated scheduling based on usage. This automation saves cloud customers time and money.
“We’ve been using ParkMyCloud for three years to automate cost optimization in our AWS environments,” said Melanie Metcalfe, Director of Project Support, Foster Moore. “We’ve now saved more than $2 million using the platform, and look forward to that number continuing to grow.”
ParkMyCloud provides an easy-to-use platform that helps enterprises automatically identify and eliminate wasted cloud spend. More than 900 enterprises around the world – including Sysco, Workfront, Hitachi ID Systems, Sage Software, and National Geographic – trust ParkMyCloud to cut their cloud spend by millions of dollars annually. ParkMyCloud’s SaaS offering allows enterprises to easily manage, govern, and optimize their spend across multiple public clouds. For more information, visit www.parkmycloud.com.
Katy Stalcup, ParkMyCloud