Azure Dev/Test pricing is an option that Azure offers to give developers access to the tools that are necessary to support ongoing development and testing in Microsoft Azure services. This, hopefully, should give the user more control of their applications and environments reducing waste.
Azure Dev/Test Pricing Options
With Azure Dev/Test pricing, three different options are available to users – Individual, Teams (Enterprise Agreement Customers), and another Teams option for those customers that don’t fall under the enterprise agreement. These pricing options are offered solely to active Visual Studio subscribers. We’ll dig in a little deeper to the pricing options and the benefits associated with each one.
Option 1: Individuals
The individual option is meant to let users explore and get familiar with Azure’s services. As you can imagine, pricing for individuals is a little different than team pricing. Individuals are given the pricing option of monthly Azure credits for those who are subscribed to Visual Studio. If this pricing option is chosen, the individual is given a separate Azure subscription with a monthly credit balance ranging from $50-150.
You get to decide how you use your monthly credit. There are several Azure services that you can put the credit towards. The software included in your Visual Studio subscription can be used on Azure VMs for no additional charges, you pay a reduced rate for the VMs that you run.
These monthly credits are ideal for personal workloads, but other options are more optimal for team workloads.
Option 2: Teams – Enterprise Agreement Customers
Teams that have an Enterprise Agreement in place have access to low Dev/Test rates for multiple subscriptions. The funds that are on the customer’s Enterprise Agreement will be used – there is no separate payment. A discount is given to customers at this level – all Windows and Windows Server, Virtual Machines, Cloud Services, and more are discounted off normal Enterprise Agreement rates.
Unlike the option for Individuals, the team’s option for enterprise agreement customers allow end-users to access the application to provide feedback and to run tests – only Visual Studio subscribers can actually use the Azure resources running in this subscription.
Option 3: Teams – All Other Customers
If a user isn’t an enterprise agreement customer but wants to use Azure for their teams, they would fall under this category. This rate offers a pay-as-you-go Dev/Test pricing option. This pricing option is very appealing because it allows users to quickly get their teams up and running with dev/test environments. Users are only allowed to use these environments for development and testing.
This is a more flexible and inclusive option, it allows for multiple team members to interact with the resources, it’s not limited to just the account owners.
Can Azure Dev/Test Save You Money?
All three options allow users to use the software that is included in their Visual Studio subscription for dev/testing. For VMs being run in environments in all three of these options, users are given a discounted price that is based on a Linux VM rate.
Microsoft Azure users that are looking to save money on their cloud costs may want to use one of these options. These pricing options come with the benefit of no additional Microsoft software charges on Azure Virtual Machines and exclusive dev/test rates on other Azure services.
Users looking to save money on public cloud may be in the market for a start/stop VM solution. While it sounds simple, there is huge savings potential available simply by stopping VMs, typically on a schedule. The basic idea is that non-production instances don’t need to run 24×7, so by turning VMs off when they’re not needed, you can save money.
If you use Microsoft Azure, perhaps you’ve seen the Start/Stop VM solution in the Azure Marketplace. You may want this tool if you want to configure Azure to start/stop VMs for the weekend or on weekday nights. It may also serve as a way to avoid creating a stop VM powershell.
Users of Azure have taken advantage of this option to start/stop VMs during off-hours, but have found that it is lacking some key functionality that they require for their business. Let’s take a look at what this Start/Stop tool offers and what it lacks, then compare it to ParkMyCloud’s comprehensive offering.
Azure Start/Stop VM Solution
Let’s take a look at Azure’s start/stop VM solution. The crux of this solution is the use of a few Azure services, specifically Automation and Log Analytics to schedule the VMs and Azure Monitor emails to let you know when a system was shut down or started. Both scheduling and keeping track of said schedules are important.
As far as the backbone of Azure services, the use of native tools within Azure can be useful if you’re already baked into the Azure ecosystem, but can be prohibitive to exploring other cloud options. You may only use Azure at the moment, but having the flexibility to use other public clouds in the future is a strong reason to use cloud-agnostic tools today.
Next, this solution costs money, but it’s not very easy to estimate the cost (but does that surprise you?). The total cost is based on the underlying services (Automation, Log Analytics, and Azure Monitor), which means it could be very cheap or very expensive depending on what else you use and how often you’re scheduling resources.
The schedules themselves can be based on time, but only for a single start and stop time – which is not practical for typical applications. The page claims it can be based on utilization, but in the initial setup there is no place to configure that. It also needs to be set up for 4 hours before it can show you any log or monitoring information.
The interface for setting up schedules and automation is not very user-friendly. It requires creating automation scripts that are either for stopping or starting only, and only have one time attached. This is tedious, and the single-time configuration makes it difficult to maximize off time and therefore savings.
To create new schedules, you have to create new scripts, which makes the interface confusing for those who aren’t used to the Azure portal. At the end of the setup, you’ll have at least a dozen new objects in your Azure subscription, which only grows if you have any significant number of VMs.
Users have noted numerous complaints in the solution’s reviews:
“Great idea – painful to use – I don’t know why it couldn’t work like the auto shutdown built into the VM config with maybe a few more options (on/off weekdays vs. weekends). Feels like a painful set of scripts with no config options once it’s deployed (or I don’t understand how to use it).”
“Tried to boil the ocean– This solution is complex and bloated. It still supports classic VMs. The autostop solution only supports stop not start. Why bother using this?”
“Start/Stop VMAzure – Difficult to do and harder to modify/change components. I’ll have difficulty to repeat to create another schedule for different VM.”
Luckily, there’s an easier option.
How it stacks up to ParkMyCloud
So if the Start/Stop VM Solution from Microsoft can start and stop Azure VMs, what more do you need? Well, we at ParkMyCloud have heard from customers (ranging from day-1 startups to Fortune 100 companies) that there are features necessary for a cloud cost optimization tool if it is going to get widespread adoption.
That’s why we created ParkMyCloud: to provide simple, straightforward cost optimization that provides rapid ROI while being easy to use. You can use ParkMyCloud to save money through Azure start/stop VM schedules for non-production resources that are not needed evenings and weekends, as well as RightSizing overprovisioned resources.
Here are some of the features ParkMyCloud has that are missing from the Microsoft tool:
Single Pane of Glass – ParkMyCloud can work with multiple clouds, multiple accounts within each cloud, and multiple regions within each account, all in one easy-to-use interface.
Easy to change or override schedules – Users can change schedules or temporarily override them through the UI, our API, our Slackbot, or through our iOS app.
Schedule recommendations – the Azure tool requires users to determine their own schedules. ParkMyClouds recommends on/off schedules based on keywords found in tags and names, and based on resource utilization history.
Policy engine – ParkMyCloud can assign schedules automatically based on rules you create based on teams, names, or other criteria.
RightSizing – in addition to on/off schedules, you can also save money with RightSizing. Our data shows that more than 95% of VMs are operating at less than 50% average CPU, which means they are oversized and wasting money. Changing the VM size or family, or modernizing instance types, saves 50-75% of the cost of the instance.
User Management – Admins can delegate access to users and assign Team Leads to manage sub-groups within the organization, providing user governance over schedules and VMs. Admin, Team Lead, and Team Member roles are able to be modified to fit your organization’s needs.
No Azure-specific knowledge needed – Users don’t need to know details about setting up Automation Scripts or Log Analytics to get their servers up and running. Many ParkMyCloud administrators provide access to users throughout their organizations via the ParkMyCloud RBAC. This is useful for users who may need to, say, start and stop a demo environment on demand, but who do not have the knowledge necessary to do this through the Azure console.
Enterprise features – Single sign-on, savings reports, notifications straight to your email or chat group, and full support access helps your large organization save money quickly.
Integrations – use ParkMyCloud with your favorite SSO tools such as Ping and Okta. Get notifications and send commands back to ParkMyCloud through tools like Slack and Microsoft Teams.
Straightforward setup – it usually takes new users 15 minutes or less to set up a ParkMyCloud account, connect to Azure, and get started saving money.
Reporting – with ParkMyCloud, users can view, download, and email savings reports covering costs, actions, and savings by team, credential, provider, resource, and more.
Notifications – users can get configurable notifications of ParkMyCloud updates & activities via email, webhook or ChatOps.
Huge cost savings and ROI – here are just a few examples from some of our customers.
A global fast food chain is managing 3,500+ resources in ParkMyCloud and saving more than $200,000 per month on their cloud spend
A global registry software company has saved more than $2.2 million on their cloud spend since signing up for ParkMyCloud – an ROI of 6173%
A global consumer goods company with 200+ ParkMyCloud users saves more than $100,000 per month on their cloud spend.
As you can tell, the Start/Stop VM solution from Microsoft can be useful for very specific cases, but most customers will find it lacking the features they really need to make cloud cost savings a priority. ParkMyCloud offers these features at a low cost, so try out the free trial now to see how quickly you can cut your Azure cloud bill.
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:
Have you been hearing a lot about Azure Databricks lately? We have. One of the nice things about talking with ParkMyCloud users is that we get to see trends often before they are more widely recognized within the industry. Whether it is adoption of new instances or databases, or usage of new tools and services it’s always interesting to see change occur.
What is Databricks?
One such change over the last year or so has been an enormous increase in the use of very short-lived instances, typically less than 60 minutes, which get spun up as part of clusters. These are in fact Databricks being used to undertake data analytics workloads. I had come across Databricks in relation to their unicorn status in the startup world – as of six months ago were valued at close to $4B – so I guess it was only a matter of time before we began to see the fruits of their labor become popular.
The Databricks story is an interesting one which begins at UC Berkeley with the development of a research project, Apache Spark in 2009. Apache Spark is described as a unified analytics engine for large-scale data processing. It provides an extremely rapid cluster computing technology, designed for fast computation. The team who developed Spark went on to found Databricks in 2013 since which time they have raised $500MM in funding.
The Databricks platform allows enterprises to build their data pipelines across data storage systems and prepare data sets for data scientists and engineers. To do this, Databricks offers a range of tools for building, managing and monitoring data pipelines. It enables the building of machine learning (ML) models, which have grown in parallel with the growth in big data within the enterprise.
The product also has an interesting approach to pricing with the introduction of their own usage-based billing methodology based on DBU’s. A DBU is a Databricks Unit (DBU) which is a unit of processing capability per hour, billed on per-second usage. This cost excludes the cost of the underlying instance (VM). The good thing is that the model is very transparent and provides a number of pricing options and tiers. Based on the tier and type of service required prices range from $0.07/DBU for their Standard product on the Data Engineering Light tier to $0.55 for the Premium product on the Data Analytics tier. Helpfully, they do offer online calculators for both Azure and AWS to help estimate cost including underlying infrastructure. The Azure Databricks pricing example can be seen here.
Databricks + Microsoft = Azure Databricks
A major breakthrough for the company was a unique partnership with Microsoft whereby their product is not just another item in the MS Azure Marketplace but rather is fully integrated into Azure with the ability to spin up Azure Databricks in the same way you would a virtual machine. Once running, the service can scale automatically as the users need change in the same way cloud is able to scale using autoscaling groups to match supply against demand.
Databricks are also available for other public cloud vendors, most notably AWS (available within the Marketplace). However, the level of integration is not the same as on Azure, and the service looks much more like a standard AWS marketplace offering.
Why More and More Companies are Using Azure Databricks
What is clear is that opportunities for use of ML and AI has progressed from experimentation to workloads, and these workloads are now at a massive scale. This has also been accompanied by the emergence of a new subset of DevOps called AIOps, which makes a lot of sense given the amount of infrastructure and services now needing to be configured and deployed to run such workloads.
In a forthcoming blog we will dig a little deeper in terms of the usage patterns for such workloads and the changes in terms of the way organizations running these workloads are now utilizing the public cloud for these non-production workloads.
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!
In today’s entry in our exploration of container services, we’ll look at Azure Kubernetes Service (AKS). Azure AKS manages your hosted Kubernetes environment, making it simple to deploy and manage containerized applications without container orchestration expertise, divesting much of that responsibility to Azure – much like EKS and GKE do for AWS and Google Cloud. Critical tasks like health monitoring of ongoing operations and maintenance by provisioning, upgrading, and scaling resources on demand are handled by Azure.
Azure AKS Overview
Azure AKS is, as of this writing, just over a year old, released for general availability in June 2018. With AKS, you can deploy, scale, and manage Docker containers and applications. Azure AKS gives developers greater flexibility, automation and reduced management overhead for administrators and developers. This is because it’s a managed service, which takes some of the management burden off the user.
As applications grow to span multiple containers deployed across multiple servers, operating them becomes more complex. To manage this complexity, Azure AKS provides an open source API to deploy, scale and manage Docker containers and container-based applications across a cluster of container hosts.
Use cases for AKS include:
Easily migrating existing applications to Kubernetes
Simplifying the deployment and management of microservices based applications
Easily integrated DevSecOps
IoT device deployment and management on demand
Machine Learning model training with AKS
If AKS is free, what do you pay for?
Yes, Azure AKS is a free service since there is no charge for managing Kubernetes clusters. However, you pay for the VM instances, storage and networking resources consumed by your Kubernetes cluster. These should be managed like any other cloud resources, with attention paid to potential areas of waste.
AKS vs. ACS
Microsoft’s experience with cluster orchestration began with Azure Container Service back in 2017, which supported Kubernetes, Docker Swarm and Mesosphere’s DC/OS. It was the simplest most open and flexible way to run container applications in the cloud then, and now followed by Azure Kubernetes Services (AKS), which was made generally available in 2018.
ACS users who run on Kubernetes can possibly migrate to AKS, but migration should be planned and reviewed for it to be successful as there are many key areas in which they are different. If considering migration, check out Azure’s guide to migrating from ACS to AKS here.
Should you use Azure AKS?
Chances are, you’re locked into a cloud provider – or have a preferred cloud provider – already, so you’re likely to use the container management service offered on your provider of choice. If you’re on Azure, AKS will be the natural choice as you increase use of microservices and app portability with containers.