Revision as of 15:53, 5 April 2017

Minha tabela de mapeamento entre on-promises para Cloud<ref>teste</ref>

Tecnologia	On-premises	Amazon Web Services (AWS)	IBM Bluemix	Microsoft Azure	Google Cloud
Acesso	-	https://aws.amazon.com	https://console.ng.bluemix.net	https://azure.microsoft.com	https://cloud.google.com
Computação	Hardware, Virtualization Docker	EC2 EC2 Container Service (ECS) LightSail Lambda Batch	Bare Metal Server Virtual Server (Hourly) Virtual Server (Monthly) VMWare Solutions	Example	Google App Engine Compute Engine Container Engine
Storage	DAS,SAN,NAS,SSD	S3 EFS Glacier Storage Gateway	Block Storage (iSCSI/NAS) Cloud Object Storage (S3 API and Swift API) Content Delivery Network (CDN) File Storage (NFS)	Example	Example
Banco de Dados	MS SQL Server, MySQL, Oracle, DB2, PostgresSQL, MongoDB	RDS (Gestão de DBs na nuvem -> MySql/Oracle/SQL Server), DynamoDB (NoSQL), ElastiCache Redshift (Data Warehouse),	DB2, Informix, MySQL (Compose for MySQL and ClearDB MySQL) ElephantSQL(PostgresSQL as a Service) Cloudant NoSQL	Example	Google Cloud SQL (MySQL e PostgreSQL)
Rede	VPN MPLS	Virtual Private Cloud (VPC), Direct Connect	IBM	MS	Google
Content Delivery	CDN de terceiros	CloudFront	SoftLayer CDN \|\| MS \|\| Google
Load Balance	Hardware and Software load balance (Cisco ACE, F5, ...)	Elastic Load Balancing, software load balancers	IBM	MS	Google
Escalabilidade e Cluster	Hardware and software clustering tools	Auto Scaling, software clustering solutions	IBM	MS	Google
Serviços de DNS	Bind, Windows Server	Route 53	IBM	MS	Google
Cache (Offload de DB)	Memcached, Redis	Amazon ElastiCache	Example	Example	Example

Infrastructure as a Service
(IaaS)
Platform as a Service (PaaS)
Software as a service (SaaS)

Big Data

Eco Sistema Big Data	On-premises	Amazon Web Services (AWS)	IBM Softlayer	Microsoft Azure
Coleta de Dados		Amazon S3, Amazon Kinesis, Amazon DinamoDB, Amazon RDS (Aurora)
Processamento de Eventos		AWS Lambda, KCL Apps
Processamento de Dados		Amazon EMR
Análise de Dados		Amazon Redshift (DB de data warehouse) , Amazon Machine Learning

Anotações

Ver também

@@ Line 1: / Line 1: @@
-Minha tabela de mapeamento entre on-promises para Cloud
+Minha tabela de mapeamento entre on-promises para Cloud<ref>teste</ref>
 {| class="wikitable sortable"
@@ Line 59: / Line 59: @@
 * Google Cloud SQL (MySQL e PostgreSQL)
 |-
-| Rede || VPN,MPLS || Amazon Virtual Private Cloud (VPC), AWS Direct Connect || Example || Example || Example
+| Rede
+||
+* VPN
+* MPLS
+||
+* Virtual Private Cloud (VPC),
+* Direct Connect
+|| IBM || MS || Google
 |-
-| Content Delivery || Thirdy-party CDN || Amazon CloudFront || IBM SoftLayer CDN || Example || Example
+| Content Delivery
+||
+* CDN de terceiros
+||
+* CloudFront
+||
+* SoftLayer CDN || MS || Google
 |-
-| Load Balance || Hardware and Software load balance (Cisco ACE, F5, ...) || Elastic Load Balancing, software load balancers || Example || Example || Example
+| Load Balance || Hardware and Software load balance (Cisco ACE, F5, ...) || Elastic Load Balancing, software load balancers || IBM || MS || Google
 |-
-| Escalabilidade e Cluster || Hardware and software clustering tools || Auto Scaling, software clustering solutions || Example || Example || Example
+| Escalabilidade e Cluster || Hardware and software clustering tools || Auto Scaling, software clustering solutions || IBM || MS || Google
 |-
 | Serviços de DNS
@@ Line 73: / Line 86: @@
 * Windows Server
 ||
-* Amazon Route 53
+* Route 53
-|| Example || Example || Example
+|| IBM || MS || Google
 |-
 | Cache (Offload de DB)
@@ Line 102: / Line 115: @@
 |}
+= Anotações =
+<reference>
 = Ver também =