4. Other things I love
Automation - Do it once, it’s done forever.
Python - Simple and fun programming language
Meetups - There are tons of tech people in Frederick
VFW - Veterans of Foreign Wars in Frederick. If you are a Afghanistan or Iraq Vet let me know.
8. A cloud provider is a company that offers some component of cloud computing –
typically Infrastructure as a Service (IaaS), Software as a Service (SaaS) or
Platform as a Service (PaaS) – to other businesses or individuals. Cloud providers
are sometimes referred to as cloud service providers or CSPs.
- Google definition
11. What is AWS?
Amazon Web Services (AWS) is a secure cloud services platform, offering
compute power, database storage, content delivery and other functionality to help
businesses scale and grow.
13. What is Azure?
Microsoft Azure is a growing collection of integrated cloud services that
developers and IT professionals use to build, deploy, and manage applications
through our global network of datacenters.
15. What is Google Cloud Platform?
Google Cloud Platform is a suite of products & services that includes application
hosting, cloud computing, database services and more.
16. Three Use Cases
● Web Dev Demo
○ A web developer needs to show off their latest stuff to a customer ASAP
● Startup to scale any day
○ A startup has a product available online that could be the next big thing any day and needs to
go from two backend servers to 20 backend servers….right now.
● Enterprise with a data center lease expiring in 24 months
○ An enterprise has an existing data center and is preparing to move to the cloud because their
lease is expiring in 2 years.
○ Their infrastructure is not as agile as a Startup’s but uses cloud ready technologies like Active
Directory, OpenStack and/or VMware.
○ They also have a huge IT team of 100+ people to enable the move in 2 years.
17. Web Dev Demo
A web developer needs to show off their latest stuff to a customer ASAP
https://github.com/patrickpierson/cloud-compare/blob/master/README.md
18. Web Dev takeaways
● Azure from the start recommends a more complex setup.
● AWS and GCP recommend a quick and dirty but sellable way to go.
● Azure’s setup could be more costly.
19. Startup Use Case
A startup has a product available online that could be the next big thing any day and needs to go
from two backend servers to 20 backend servers…...right now.
21. AWS Cloudformation
JSON or YAML based. AWS managed service to deploy AWS resources.
https://s3-us-west-2.amazonaws.com/cloudformation-templates-us-west-2/AutoSc
alingMultiAZWithNotifications.template
22. Azure Resource Manager
JSON based. Azure managed service to deploy Azure resources.
https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/openv
pn-access-server-ubuntu/azuredeploy.json
23. Google Deployment Manager
Python/YAML based. Google managed service to deploy GCP resources.
https://github.com/GoogleCloudPlatform/deploymentmanager-samples/blob/maste
r/templates/autoscaled_group.py
https://github.com/GoogleCloudPlatform/deploymentmanager-samples/blob/maste
r/templates/autoscaled_group.py.schema
24. Startup takeaway
All three could work for a Startup.
Microsoft shops may want to start on Azure because of MSDN credits.
All three have free tiers.
Use what works best for you, try all three and see what happens.
25. Enterprise Use Case
An enterprise has an existing data center and is preparing to move to the cloud because their lease
is expiring in two years and the CTO has a cloud first initiative.
Their infrastructure is not as agile as a Startup but uses cloud ready technologies like Active
Directory, OpenStack and/or VMware.
They also have a huge IT team of 100+ people to enable the move in that two years.
26. Requirements
Requirement AWS Azure GCP
Fast connection to HQ
Dedicated Hardware
Active Directory
Integration
Note: For dedicated hardware on Azure and GCP the recommendation is to purchase a very large instance.
ish
27. Fast connection to HQ
Dedicated network connection with low latency from your Headquarters building to
the Cloud service provider via a NSP (Network Service Provider)
● AWS Direct Connect - 50+ NSPs
● Azure Express Route - 39 NSPs
● Google Cloud Interconnect - 23 NSPs
https://aws.amazon.com/directconnect/partners/#americas
https://azure.microsoft.com/en-us/services/expressroute/
https://cloud.google.com/interconnect/docs#cloud_interconnect_service_providers
28. Why dedicated hardware?
● Compliance/Security requirements - This is a big one for most enterprises.
White papers will scream that shared instances are secure but you can
understand why a CISO would want this just to feel better about the cloud.
● Expands existing infrastructure easily - VMware/Openstack deployment
pushed into the cloud environment.
● Additional visibility and control over instances - allows for manual placement
of instances if needed.
30. Instances
● Instance sizes vary so cost on a given size varies between all three
● Google compute charges by the minute
● Google compute offers custom machine sizes
● All three offer Low-Priority/Preemptible/Spot instances but offerings are
slightly different and do not fit every type of workload
● AWS is the only cloud provider offering dedicated hosts
31. Containers
● Google offers managed Kubernetes (public project based of of their Borg
system). Most mature service offering in this market.
● AWS offers Elastic Compute Service, two years old, new features added
regularly to (for the most part) clone Kubernetes without running Kubernetes
(my opinion)
● Azure Container Service is super new (few months old).
32. Managed Databases
● All three offer a lot of relational and non-relational database products.
● AWS
○ RDS - Relational Database service, MySQL, Postgres, MsSql, Oracle, and Aurora (MySQL
and Postgres compatible, marketed at Oracle customers)
○ DynamoDB - No-SQL Database Service, Cassandra partly based on this and Google’s
BigTable
○ Athena - Direct S3 SQL queries against CSV files
● Google
○ BigTable (First Cloud Database service)
○ Cloud SQL (Relational Database service)
○ Cloud Spanner (Horizontal scaling database service)
○ Cloud Datastore (No-SQL Database service with more features then BigTable)
33. Managed Databases cont
● Azure
○ Big push for SQLServer on VMs - Smart of them, maybe not the best choice given other
offerings (Expensive!)
○ SQL Database - Managed Database service built on SQL Server codebase
○ SQLServer Stretch Database - Dynamically stretch(?) SQL Server databases to Azure
○ Cosmos DB - Managed No-SQL Database service
○ Azure Database for MySQL and PostgreSQL (Preview)
34. Big Data
● AWS
○ Elastic Map Reduce - Managed Hadoop/Spark Clusters
○ Elasticsearch Service
○ Athena - S3 SQL queries
○ Kinesis - Stream terabytes of data
○ Redshift - Managed Data Warehousing
○ Snowmobile - 100PBs on an actual truck
● Azure
○ HDInsight - Managed Hadoop/Spark Clusters
○ Data Lake Analytics - Serverless big data analytics
35. Big Data
● GCP
○ Dataproc - Managed Hadoop/Spark Clusters
○ BigQuery - Managed data warehouse
○ Dataflow - Data process for streaming, ETL and batch computation
○ Datalab - Interactive notebook based on Jupyter for data work
36. Regions and Zones
AWS and GCP have different regions you can push apps to but also let you dive
deeper and use specific zones if needed. Azure does not do this.
Azure has its reasons and they might be a better fit for some users.
Specifically - No single AZ outages (happens on AWS and GCP from time to time)
AWS and GCP zones allow for much lower latency which may be important to
some users.
Most users of cloud will not actually care.