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首页利用Azure优化数据设计与管理:Microsoft Azure数据解决方案实战
利用Azure优化数据设计与管理:Microsoft Azure数据解决方案实战
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更新于2024-07-18
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"《云数据设计、编排与管理:利用微软Azure打造解决方案》是一本专为软件开发人员和具备良好数据设计背景以及基本开发技能的专业人士撰写的指南。本书旨在帮助读者掌握如何在Azure平台上优化数据解决方案,以节省时间和成本。作者弗朗西斯科·迪亚兹和罗伯托·弗雷托深入浅出地介绍了如何利用Azure数据平台进行设计、分析、集成、监控和衍生服务。 书中详细讲解了Azure的各种服务,使读者能够识别哪些服务最适合特定需求,从而实现高效的数据设计。读者将学会如何将关系型数据库无缝融入到整体架构中,同时也能了解如何利用Azure的混合云和公共云特性处理各种类型的数据。非关系型数据库的选择和应用也被讨论,以便应对复杂的数据需求。 此外,本书还重点介绍了如何通过Azure服务进行数据的编排和迁移,确保数据在生命周期中的有效管理和操作。章节设计上,五分之六的内容聚焦于PaaS服务,而另一章则专门探讨SQL Server在云环境和混合云IaaS功能中的特性。 《云数据设计、编排与管理:利用微软Azure》不仅提供了一套实践性的方法论,而且具有实际操作的案例和策略,适合希望在Azure平台上建立强大数据解决方案的专业人员参考。版权信息表明,此书享有所有权利,包括翻译、再版、图像使用等,提醒读者未经许可不得擅自复制或传播。" 通过阅读这本书,读者可以全面提升在云计算环境下设计、管理数据的能力,从而在IT行业中取得竞争优势,并确保数据解决方案的高效和可靠性。
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In Chapter 3 (Working with NoSQL alternatives) we want to turn tables on the typical
discussion around NoSQL.We choose to not include Cosmos DB in the chapter, either to
postpone the topic to a dedicated book, either to highlight how many NoSQL alternatives
we have in Azure outside the classics. We center the discussion around Blobs, that are
often under-evaluated, around Tables and Redis to finally approach on Azure Search,
one of the most promising managed search services in the cloud ecosystem.
In Chapter 4 (Orchestrate data with Azure Data Factory) we discover orchestration
of data. We want to emphasize the importance of data activities, in terms of movements,
transformation and the modern addressing to the concepts we known as ETL for many
years. With Data Factory, you will discover an emerging (and growing up) service to deal
with pipelines of data and even complex orchestration scenarios.
In Chapter 5 (Working with Azure Data Lake Store and Azure Data Lake Analytics)
we start to build foundations for the big data needs. We discover how Data Lake can help
with storing, managing and analyzing unstructured data, stored in their native format
while they are generated. We will learn this important lesson around big data: since we
are generating and storing today the data we are using and analyzing tomorrow, we need
a platform service to build intelligence on it with minimal effort.
Finally, Chapter 6 (Working with In-Transit Data and Analytics) closes the book
with a little introduction about messaging and, generally, the in-transit data, to learn
how we can take advantage of ingestion to build run-time logics in addition to the most
consolidated ones. Messaging is extremely important for several scenarios: almost every
distributed system may use messaging to decouple components and micro-services.
Once messaging is understood, we can apply the event-based reasoning to move some
parts of the business rules before the data is written to the final, persistent data store.
Eventually, we learn how to implement in-transit analytics.
We hope this can be a good cue to address how to approach data service in this
promising momentum of cloud and Platform-as-a-Service. We know this book cannot
be complete and exhaustive, but we tried to focus on some good points to discuss the
various areas of data management we can encounter on a daily basis.
inTRoduCTion
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© Francesco Diaz, Roberto Freato 2018
F. Diaz and R. Freato, Cloud Data Design, Orchestration, and Management Using Microsoft Azure,
https://doi.org/10.1007/978-1-4842-3615-4_1
CHAPTER 1
Working withAzure
Database Services
Platform
To get the most out of the power of cloud services we need to introduce how to deal with
relational data using a fully managed RDBMS service, which is, in Microsoft Azure, SQL
Database.
SQL Database is the managed representation of Microsoft SQL Server in the cloud.
Can be instantiated in seconds/minutes and it runs even large applications without
minimal administrative effort.
Understanding theService
SQL Database can be viewed as a sort of Microsoft SQL Server as-a-Service, where those
frequently-addressed topics can be entirely skipped during the adoption phase:
• License management planning: SQL Database is a pay-per-use
service. There is no upfront fee and migrating between tiers of
different pricing is seamless
• Installation and management: SQL Database is ready-to-use. When
we create a DB, the hardware/software mix that runs it already exists
and we only get the portion of a shared infrastructure we need to
work. High-availability is guaranteed and managed by Microsoft and
geo-replication is at a couple of clicks away.
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• Maintenance: SQL Database is a PaaS, so everything is given to us
as-a-Service. Updates, patches, security and Disaster Recovery are
managed by the vendor. Also, databases are backup continuously to
provide end-users with point-in-time restore out-of-the-box.
From the consumer perspective, SQL Database has a minimal feature misalignment
with the plain SQL Server and, like every Platform-as-a-Service, those touch points can
be inferred by thinking about:
• Filesystem dependencies: we cannot use features that correlates
with customization of the underlying operating system, like file
placement, sizes and database files which are managed by the
platform.
• Domain dependencies: we cannot join a SQL Database “server”
to a domain, since there is no server from the user perspective. So,
we cannot authenticate with Windows authentication; instead, a
growing up support of Azure Active Directory is becoming a good
replacement of this missing feature.
• Server-wide commands: we cannot (we would say “fortunately”)
use commands like SHUTDOWN, since everything we make is
made against the logical representation of the Database, not to its
underlying physical topology.
In addition to the perceptible restrictions, we have some more differences related
to which is the direction of the service and the roadmap of advanced features. Since we
cannot know why some of the features below are not supported, we can imagine they are
related to offer a high-level service cutting down the surface area of potential issues of
advanced commands/features of the plain SQL Server.
For a complete comparison of supported features between SQL Database and SQL
Server, refer to this page: https://docs.microsoft.com/en-us/azure/
sql-database/sql-database-features
CHAPTER 1 WORKING WITHAZURE DATABASE SERVICES PLATFORM
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At least, there are service constraints which add the last set of differences, for
example:
• Database sizes: at the time of writing, SQL Database supports DB up
to 1TB of size (the counterpart is 64TB)
• Performance: despite there are several performance tiers of SQL
Database, with the appropriate VM set, SQL in a VM can exceed
largely the highest tier of it.
For a good introduction of how to understand the differences between the features
supported in both products, refer to this page: https://docs.microsoft.com/
en-us/azure/sql-database/sql-database-paas-vs-sql-server-iaas.
Connectivity Options
We cannot know the exact SQL Database actual implementation, outside of what
Microsoft discloses in public materials. However, when we create an instance, it has the
following properties:
• Public URL: in the form [myServer].database.windows.net.
Public- faced on the Internet and accessible from everywhere.
Yes, there are some security issues to address with this topology, since there is no
way to deploy a SQL Database in a private VNet.
• Connection modes:
• from outside Azure, by default, each session between us and SQL
Database passes through a Proxy, which connects to the actual
ring/pool of the desired instance
• from inside Azure, by default, clients are redirect by the proxy to
the actual ring/pool after the handshake, so overhead is reduced.
If we are using VMs, we must be sure the outbound port range
11000- 11999 is open.
CHAPTER 1 WORKING WITHAZURE DATABASE SERVICES PLATFORM
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We can change the default behavior of the Proxy by changing this property:
https://msdn.microsoft.com/library/azure/mt604439.aspx. Note that,
while connecting from outside Azure, this means multiple IPs can be configured to
outbound firewall rules.
• Authentication:
• Server login: by default, when we create a Database, we must
create a server before it. A server is just a logical representation of
a container of database, no dedicated physical server is mapped
to it. This server has an administrator credential, which have full
permission on every DB created in it.
• Database login: we can create additional credentials tied to
specific databases
• Azure AD login: we can bind Azure AD users/groups to the server
instance to provide an integrated authentication experience
• Active Directory Universal Authentication: only through a proper
version of SSMS, clients can connect to SQL Database using a
MFA
• Security:
• Firewall rules: to allow just some IPs to connect to SQL Database,
we can specify firewall rules. They are represented by IP ranges.
• Certificates: by default, an encrypted connection is established.
A valid certificate is provided, so it is recommended (to
avoid MITM attacks) to set to “false” the option “Trust Server
Certificate” while connecting to it.
Given this information above as the minimum set of knowledge to connect to a
SQLDB instance, we can connect to it using the same tooling we use for SQL Server.
SSMS is supported (few features won’t be enabled however), client connectivity through
the SQL Client driver is seamless (as it would be a SQL Server instance) and the majority
of tools/applications will continue to work by only changing the connection string.
CHAPTER 1 WORKING WITHAZURE DATABASE SERVICES PLATFORM
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