Among several exciting announcements we heard at AWS re:Invent 2018 was one that hit close to our Loudoun County home – the new AWS GovCloud (US-East) Region. Joining GovCloud (US-West), the first of its kind, the East region is the second for AWS GovCloud and the 19th AWS region in the world. This announcement is significant, particularly to the Washington DC area of the east coast, home to the ParkMyCloud headquarters and a significant number of U.S. government departments and agencies.
The US-East region adds three more Availability Zones to AWS GovCloud, doubling the three total that were previously included with the existing infrastructure. This is great news for U.S. customers in the public and commercial sector in highly regulated industries that must meet stringent compliance requirements, including those for disaster recovery and continuity of operations. The new region is compatible with EC2, S3, and RDS instance types, among more.
Why does AWS GovCloud matter?
The advantages of scalability, security, and agility in the cloud are alluring. But for customers with sensitive data and strict compliance and security requirements, like government agencies, using the cloud is a tricky process with a huge checklist to follow. To provide the same benefits of cloud services while meeting even the most stringent U.S. government requirements, Amazon designed an isolated cloud region only for those users – AWS GovCloud.
What’s Different in AWS GovCloud?
Think of AWS GovCloud as Amazon’s “gated community.” GovCloud vets all of its government customers and their partners to create secure cloud solutions, meeting compliance requirements for FedRAMP, the DOJ’s Criminal Justice Information Systems (CJIS), U.S. International Traffic in Arms Regulations (ITAR), Export Administration Regulations (EAR), Department of Defense (DoD) Cloud Computing Security Requirements Guide (SRG), FIPS 140-2, IRS-1075, and more. This specialized region allows for customers to host sensitive Controlled Unclassified Information (CUI) that includes data in categories such as agriculture, patent, export, critical infrastructure, immigration, law enforcement, proprietary business info, statistical, tax, financial, and transportation, to name a few. GovCloud is ideal for government agencies at the federal, state, and local level, as well as organizations in regulated industries including financial, technology, energy, healthcare, law enforcement, defense, enterprise, and aerospace.
How do I qualify to be a GovCloud customer?
GovCloud is only available to vetted U.S. entities and root account holders with U.S. citizenship. AWS ensures address compliance in the cloud with network, data, and virtual machines that are isolated from all other AWS cloud regions. GovCloud features a separate identity and access management stack with unique credentials that work only within the AWS GovCloud region. In addition, the region is managed solely by AWS personnel of U.S. citizenship, on U.S. soil, and users get their own separate management console. The region also has endpoints specific to its region, including the option to use designated endpoints, meeting FIPS 100-2 compliance requirements.
Why go GovCloud?
Whether it’s Personally Identifiable Information (PII), patient medical records, financial data, law enforcement data, or other forms of CUI, AWS GovCloud allows users to meet compliance requirements on their cloud journey. Government agencies have an opportunity with Amazon to support mission critical workloads for enterprise applications, high performance computing, big data, storage & disaster recovery. For a U.S. cloud with vetted access, that meets compliance, guards data, improves identity management, protects workloads, and enhances cloud visibility, AWS GovCloud is the way to go.
Although Amazon dominates the market share of cloud services, there’s been a trend among retailers to choose AWS alternatives. Big-name retailers, in verticals from clothing to electronics, are moving away from maintaining their own data centers in favor of the public cloud’s agility and better access to customers worldwide. To highlight a few:
Gap Inc. signed a five-year contract with Microsoft, choosing Azure as their primary cloud provider. Employees will also be using Microsoft 365 tools and the Enterprise Mobility and Security suite. They chose Azure to support their e-commerce operations, inventory, and workforce systems.
Gap chose Azure among AWS alternatives because they wanted “a partner that is not going to be a competitor […] in any other parts of their businesses,” as told by Shelley Bransten, corporate VP for global retail and consumer goods at Microsoft.
Furthermore, in a move directly targeting Amazon, Walmart has asked their tech vendors to choose AWS alternatives. Wal-Mart spokesman Dan Toporek told CNBC: “Our vendors have the choice of using any cloud provider that meets their needs and their customers’ needs. It shouldn’t be a big surprise that there are cases in which we’d prefer our most sensitive data isn’t sitting on a competitor’s platform.”
Supermarket and retail giant Kroger took a multi-cloud approach, first with Pivotal and Microsoft, and later adding on Google Cloud in 2017. In a CNBC interview, Chris Hjelm, Kroger’s chief information officer, explains why the retailer spends millions of dollars on Microsoft and Google in order to avoid AWS: “For obvious reasons competitively, it doesn’t make sense for us to do a ton to help grow that business for them.”
Target, another retail competitor of Amazon, decided to stop financing its rival in mid-2017 and began dropping down their use of AWS. Microsoft, Google, and Oracle all pushed for their business as discussions were kept quiet, with a Target spokesperson only admitting that they use multiple clouds. Earlier this year, Google CEO Sundar Pichai confirmed Target as a big cloud customer.
And the list goes on…
In addition to the rest, Spotify, eBay, Best Buy, and LL.Bean all turned to Google to meet their cloud needs. One by one, big retailers with recognized names are choosing Microsoft and Google in favor of Amazon.
Why Retailers Choose AWS Alternatives
Cloud migration requires a massive haul of data, costs, and time from a business. Not only is there a lot to consider in terms of pricing, services, and overall offerings, but there are also certain needs unique to a specific industry. Big retailers turning away from AWS and onto other cloud providers highlights an issue for Amazon as a competitor in the retail industry, providing opportunities for other providers like Microsoft and Google to secure enterprise deals.
Meanwhile, not everyone has chosen AWS alternatives. Amazon still holds the market lead and continues to retain a footprint in the retail industry with customers including Nordstrom, Nike, Under Armour, and Lululemon. So while sources suggest that more retailers are looking for other options outside of AWS, time will tell if Amazon can hold its spot among retailers.
Alibaba Cloud offers a number of ECS instance types optimized to meet various needs at the enterprise level. Instance types are specialized for different purposes, and vary by virtual CPU (vCPU), disk capability, memory size, and other features, offering a number of options to match any workload.
ECS instance types at the enterprise level are available for computing on the x86-architecture or for heterogenous computing, with generous options among both. But with so much to choose from, how does one find the right ECS instance type to meet their individual needs? We drew up a comparison for a quick guide on the different options and what they offer. The chart below and written descriptions are a brief and easy reference, but remember that finding the right instance type for your workload will always depend on your needs.
All general purpose ECS instance types are I/O optimized, offer a CPU to memory ratio of 1:4 and come with support for SSD and Ultra Cloud Disks.
The g5 instance type is backed by a 2.5 GHz Intel Xeon Platinum 8163 processor. With an ultra high packet forwarding rate, higher computing specs and higher network performance, this type ideal for scenarios involving transfer of a large volume of packets, running enterprise-level apps, small to medium database systems, data analysis, and computing clusters and data processing that rely on memory.
Similar to the g5, the sn2e instance is ideal for the same scenarios and has higher computing specifications and enhanced network performance. Backed by a 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) or Platinum 8163 (Skylake) processors.
hfg5 (high clock speed)
The hfg5 is centered upon stable performance. Having many features in common with the g5 and sn2e options, this type family also offers a 56 vCPU instance type for boosted performance. With a 3.1 GHz Intel Xeon Gold 6149 (Skylake) processor, this instance type is better suited for high-performance front end servers, science and engineering apps, and Massively Multiplayer Online (MMO) games and video coding.
Compute optimized ECS instance types are all I/O optimized with support for SSD Cloud Disks and Ultra Cloud Disks, but vary in their vCPU to memory ratios and ideal scenario uses. Read on to learn the nuances.
Se1ne (enhanced network performance)
The se1ne comes with higher computing specs for enhanced network performance, a vCPU ratio of 1:8, ultra high packet transfer rate for receiving or transmitting, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) or Platinum 8163 (Skylake) processors. This type is ideal for large pack transfers, high-performance and large memory databases, data analysis, mining, distributed memory cache, and enterprise-level apps with large memory requirements (Hadoop, Spark).
hfc5 (high clock speed)
Optimized for stable performances, the hfc5 type boasts 3.1 GHz Intel Xeon Gold 6149 (Skylake) processors, vCPU to memory ratio of 1:2, higher computing specs and performance, and ideal for high-performance Web front-end servers, science and engineering applications, and MMO gaming and video coding.
gn6v, gn5, gn5i, gn4, ga1 (with GPU)
The g-series ECS instance type families come are all optimized for GPU compute workloads, with varying GPU processors and compute to memory options. All are ideal for deep learning, scientific computing, high-performance computing, rendering, multi-media coding, decoding, and other GPU compute workloads.
gnv6: V100 GPU processors, vCPU to memory ratio of 1:4, 2.5 GHz Intel Xeon Platinum 8163 (Skylake) processors.
gn5: NVIDIA P100 GPU processors, no fixed ratio of vCPU to memory, high-performance local NVMe SSD disks, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors.
gn51: NVIDIA P4 GPU processors, vCPU to memory ratio of 1:4, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors.
gn4: NVIDIA M40 GPU processors, no fixed CPU to memory, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
ga1: AMD S7150 GPU processors, vCPU to memory ratio of 1:2.5, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors, and high-performance local NVMe SSD disks. Also ideal for other server-end business scenarios that require powerful concurrent floating-point compute capabilities
f1, f2, f3 (with FPGA)
The f-series ECS instance type families are ideal for deep learning, genomics research, financial analysis, picture, transcoding, and computational workloads, including real-time video processing and security.
f1: Intel ARRIA 10 GX 1150 FPGA, vCPU to memory ratio of 1:7.5, 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
f2: Xilinx Kintex UltraScale XCKU115, vCPU to memory ratio of 1:7.5, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
F3: Xilinx 16nm Virtex UltraScale + VU9P, vCPU to memory ratio = 1:4, and 2.5 GHz Intel Xeon Platinum 8163 (Skylake) processors
Memory optimized ECS instance types are optimized to meet for needs for high-performance and high memory databases and come I/O optimized with support for SSD and Ultra Cloud disks.
The re4 is ideal for memory-intensive applications and Big Data processing engines (Apache spark or Presto), with 2.2 GHz Intel Xeon E7 8880 v4 (Broadwell) processors, up to 2.4 GHz Turbo Boot, vCPU to memory ratio of 1:12, up to 1920.0 GiB memory, and ecs.re4.20xlarge and ecs.re4.40xlarge have been certified by SAP HANA.
The s-series instance types are good for transfers of large volumes of packets, data analysis and mining, distributed memory cache, and Hadoop, Spark, and other enterprise-level applications with large memory requirements.
se1ne: vCPU to memory ratio of 1:8, high packet transfer rate, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) or Platinum 8163 (Skylake) processors.
se1: vCPU to memory ratio of 1:8, 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
The d-series ECS instance types are I/O optimized with support for SSD and Ultra Cloud disks come with high computing specs and network performance. They’re best use for Hadoop MapReduce, HDFS, Hive, HBase, etc, Spark in-memory computing, big data computing and storage analysis (i.e. internet and finance industries), Elasticsearch, logs, and so on.
d1ne: High-volume local SATA HDD disks with high I/O throughput and up to 35 Gbit/s of bandwidth for a single instance, vCPU to memory ratio of 1:4, 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
D1: High-volume local SATA HDD disks with high I/O throughput and up to 17 Gbit/s of bandwidth for a single instance, vCPU to memory ratio of 1:4, and 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
The ic5 instance types stands on it own with a vCPU to memory ratio of 1:1. I/O optimized with support for SSD Cloud Disks and Ultra Cloud Disks, a high packet transfer rate, and 2.5 GHz Intel Xeon Platinum 8163 (Skylake) processors. Ideal for web front-end servers, data analysis, batch compute, and MMO game front-ends.
With Local SSD
i2, i2g, i1
The i-series type family all come with high-performance local SSD disks with high IOPs, high I/O throughput, and low latency. They’re ideal for OLTP and high-performance relational databases, NoSQL databases (Cassandra and MongoDB), and search applications, such as Elasticsearch
i2: vCPU to memory ratio of 1:8, designed for high-performance databases, 2.5 GHz Intel Xeon Platinum 8163 (Skylake) processors
i2g: vCPU to memory ratio of 1:4, designed for high-performance databases, 2.5 GHz Intel Xeon Platinum 8163 (Skylake) processors
i1: vCPU to memory ratio of 1:4, designed for big data scenarios, 2.5 GHz Intel Xeon E5-2682 v4 (Broadwell) processors
What Alibaba ECS instance types are right for your workloads?
With a wide range of ECS instance types belonging to multiple families, how do you determine the ECS type is a good match for your workload? With plenty to choose from, it’s highly probable that one of them will meet your needs effectively, but first you need to know what those needs are. Once you have a clear and ongoing vision of your workload, usage trends, and business needs, use the guide to start looking for the ECS type that’s right for you.
If you’re looking to break into the cloud computing space, there’s an abundance of resources out there, including free Google Cloud training. If you know where to look, open source learning is a great way to get familiar with different cloud service providers. Combined with our previous blog posts on free training resources for AWS and Azure, you’ll be well on your way to expanding your cloud expertise and finding your own niche. No matter where you are in the learning process, there’s a training resource for every experience level and learning type – get started now with our list of 5 free Google Cloud training resources:
1. Google Cloud Free Tier
For free, hands-on training there’s no better place to start than with Google Cloud Platform itself. GCP’s free tier option is a no-brainer thanks to its offerings:
Access to all GCP products. You’ll have everything you need to experiment with building and running apps, sites, and services. Firebase and the Google Maps API are included.
$300 credit is yours to spend for the next 12 months, an expansion from their previous 60-day period and a sizable offer in comparison to Azure’s $200 for 30 days, so take advantage.
No autocharges after the trial period ends – a rarity for most free trials, and a guarantee that this training resource is 100% free.
And for help with navigating the platform as you use it, check out GCP’s documentation for a full overview, comparisons, tutorials, and more.
On the Google Cloud training page, you’ll find plenty of classes to get technical skills and learn best practices for using the platform. Among those options, they have also teamed up with Coursera, an online learning platform founded by Stanford professors, to offer courses online so you can “skill up from anywhere.”
Coursera includes a number of free courses, and until 1/1/19, you can sign up and get your first month free on any select Google Cloud Specialization. Courses include topics in Machine Learning, Architecting, Data Engineering, Developing Applications, and the list goes on.
In conjunction with Coursera, Google Cloud offers hands-on training with specialized labs available via Qwiklabs, a learning lab environment for developers. Choose a “quest” from their catalog to get started with 50+ hands-on labs from beginner to expert level, where you’ll learn new skills in a GCP environment and earn cloud badges along the way. Get started with GCP Essentials and work your way into more advanced, niche topics like Managing Cloud Infrastructure with Terraform, Machine Learning APIs, IoT in Google Cloud, and so on.
You can’t go wrong with YouTube. An endless amount of free videos offers an abundance of Google Cloud training for those of you who prefer to watch the movie instead of reading the book (you know who you are). Some of the most popular YouTube channels for free Google Cloud training include:
Google Cloud Platform (243k subscribers) – “helping you build what’s next with secure infrastructure, developer tools, APIs, data analytics and machine learning.”
Edureka (537k subscribers) is a full-service, online learning platform with curated content in Big Data and Hadoop, DevOps, Blockchain, AI, Data Science, AWS, Google Cloud, and more. Their YouTube channel is a “gateway to high-quality videos, webinars, sample classes and lectures from industry practitioners and influencers.” If you’re jumping into GCP with no prior knowledge or experience, the What is Google Cloud Platform tutorial will get you started.
5. Blogs & Forums
While other resources keep you learning with hands-on training, tutorials, and certification prep, blogs keep your mind flowing with new insights, ideas, and the latest on all things cloud computing. Google Cloud and Qwiklab have blogs of their own, perfect for supplemented reading with their trainings. But for a more well-rounded blog with content on other service providers, check out Cloud Academy. We also cover Google Cloud on the ParkMyCloud blog – check out this guide to Google Cloud machine types, an explanation of sustained use discounts, and introduction to resource-based pricing. And be sure to subscribe to relevant discussion forums such as r/googlecloud on Reddit and the GCP Slack.
Take Advantage of These Free Google Cloud Training Resources
As it becomes clear that cloud computing is here to stay, free training resources only continue to emerge. We picked the 5 above for their reliability, variety, quality, and range of information. Whether you’re new to Google Cloud or consider yourself an expert, these resources will expand your knowledge and keep you up to date with what’s latest in the platform.
Microsoft Azure VM types come in a wide range optimized to meet various needs. Machine types are specialized, and vary by virtual CPU (vCPU), disk capability, and memory size, offering a number of options to match any workload.
With so many options available, finding the right machine type for your workload becomes confusing – which is why we’ve created this overview of Azure VM types (as we did before with EC2 instance types, and Google Cloud machine types). Note that while AWS EC2 instance types have names associated with their purpose, Azure instance type names are simply in a series from A to N.The chart below and written descriptions are a brief and easy reference, but remember that finding the right machine type for your workload will always depend on your needs.
General purpose VMs are suitable for balanced CPU and memory, making them a great option for testing and development, smaller to medium databases, and web servers with lower traffic:
The latest family of virtual machines stand out for data protection and code confidentiality. SGX technology and a 3.7GHz Intel XEON E-2176G Processor back these machines, and in conjunction with Intel Turbo Boost Technology, they can go up to 4.7 GHz.
Dv2 VMs boast powerful CPUs – roughly 35% faster than D-series VMs – and optimized memory, great for production workloads. With the same memory and disk configurations as the D-series, based upon either a 2.4 GHz or 2.3 GHz processor and Intel Boost Technology, they can go to up to 3.1 GHz.
With expanded memory and adjustments for disk and network limits, the Dv3 series Azure VM type offers the most value to general purpose workloads. Best for enterprise applications, relational databases, in-memory caching, and analytics.
Similar to the AWS t-series machine type family, B-series VMs are burstable and ideal for workloads that do not rely on full and continuous CPU performance. Customers can purchase a VM size that builds up credits when underutilized, and the accumulated credits can be used as bursts – spikes in compute power that allow for higher CPU performance when needed. Use cases for B-series VM types include development and testing, low-traffic web servers, small databases, micro services, and more.
With a base core frequency of 2.7 GHz and a maximum single-core turbo frequency of 3.7 GHz, Fsv2 series VM types offer up to twice the performance boost for vector processing workloads. Not only do they offer great speed for any workload, the Fsv2 also offers the best value for its price based on the ratio of Azure Compute Unit (ACU) per vCPU.
F-series Azure VM types are great for workloads that require speed thanks to the 2.4 GHz Intel Xeon processor, reaching speeds up to 3.1 GHz with the Intel Turbo Boost Technology 2.0. The F-series is your best bet for fast CPUs but not so much when it comes to memory or temporary storage per vCPU. Analytics, gaming servers, web servers, and batch processing would work well with the F-series.
Memory optimized VM types are higher in memory as opposed to CPU, and best suited for relational database services, analytics, and larger caches.
For applications that require fast vCPUs, reliable temporary storage, and demand more memory, the Dv2, G, and DSv2/GS series all fit the bill for enterprise applications. The Dv2 series offers speed and power with a CPU about 34% faster than that of the D-series. Based on the 2.3 and 2.4 GHz Intel Xeon® processors and with Intel Turbo Boost Technology 2.0, they can reach up to 3.1 GHz. The Dv2-series also has the same memory and disk configurations as the D-series.
The Ev3 follows in the footsteps of the high memory VM sizes originating from the D/Dv2 families. This Azure VM types provides excellent value for general purpose workloads, boasting expanded memory (from 7 GiB/vCPU to 8 GiB/vCPU) with adjustments to disk and network limits per core basis in alignment with the move to hyperthreading.
For big data, SQL, and NoSQL databases, storage optimized VMs are the best type for their high disk throughput and IO.
VMs provide as much as 32 vCPUs with the Intel® Xeon® processor E5 v3 family. The Ls-series comes with the same CPU performance as the G/GS-Series and 8 GiB of memory per vCPU. This type works best applications requiring low latency, high throughput, and large local disk storage.
GPU VM types, specialized with single or multiple NVIDIA GPUs, work best for video editing and heavy graphics rendering – as in compute-intensive, graphics-intensive, and visualization workloads.
NC, NCv2, NCv3, and ND sizes are optimized for compute-intensive and network-intensive applications and algorithms.
NV and NVv2 sizes were made and optimized for remote visualization, streaming, gaming, encoding, and VDI scenarios.]
High Performance Compute
For the fastest and most powerful virtual machines, high performance compute is the best choice with optional high-throughput network interfaces (RDMA).
For the latest in high performance computing, the H-series Azure VM was built for handling batch workloads, analytics, molecular modeling, and fluid dynamics. These 8 and 16 vCPU VMs are built on the Intel Haswell E5-2667 V3 processor technology featuring DDR4 memory and SSD-based temporary storage.
And besides sizable CPU power, the H-series provides options for low latency RDMA networking with FDR InfiniBand and different memory configurations for supporting memory intensive compute requirements.
What Azure VM type is right for you?
With six virtual machine types belonging to multiple families and coming in a range of sizes, how do you determine the right Azure VM type for your workload? The good news is that with this many options, you’re bound to find the right type to meet your computing needs – as long as you know what those needs are. With good insight into your workload, usage trends, and business needs, you’ll be able to find the Azure VM type that’s right for you.