AWS VS Azure VS GCP VS IBMCloud Basic Details(Multi Cloud)

Cloud Computing is the delivery of on-demand computing resources (computer power, database storage, applications as well as other IT resources) over the internet. This is achieved by using a network of remote servers hosted on the internet rather than a local server/personal computer. A cloud service is any service made available to users on demand via the Internet from a cloud computing provider’s server as opposed to being provided from a company’s own on-premises servers. Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) are the three categories of cloud services. Cloud service platforms provide the above-mentioned services.

Major cloud service platforms:

Amazon Web Services (AWS) – It’s a comprehensive, evolving cloud computing platform provided by Amazon. AWS delivers a mix of IaaS, PaaS, and SaaS.

Microsoft Azure (formerly known as Windows Azure) – It is Microsoft’s public cloud computing platform. It provides a range of cloud services through a global network of Microsoft managed data centers.

Google Cloud – Google Cloud Platform is the suite of public cloud computing services by Google. It runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. This includes a range of hosted services to compute, storage and application development that run on Google hardware. Google Cloud Platform services can be accessed by software developers, cloud administrators and other enterprise-IT professionals over the public internet or through a dedicated network connection.

IBM Cloud (formerly known as IBM Blemix and  IBM Softlayer) –  Cloud computing services from IBM which offers PaaS, SaaS, and IaaS. With IBM Cloud IaaS, organizations can deploy and access virtualized IT resources such as compute power, storage and networking over the internet. For compute, organizations can choose between bare-metal or virtual servers.

Alibaba Cloud – Subsidiary of Alibaba group which provide a suite of cloud computing services that covers elastic computing, 

object storage, relational database, big data analysis, and artificial intelligence in fifteen geographical regions around the globe.

Oracle Cloud – Cloud service offering from Oracle Corporation. This provides servers, storage, network, applications and services through a global network of Oracle’s managed data centers. Here, services are provided over the internet, on demand.

Here, we can see the comparison between each of the above cloud platforms in general :Public Cloud:

Along with the above features, there is a need to consider these important factors while purchasing a cloud service:

• Historical usage (by region, instance family, etc.).
• Steady-state usage vs. part-time usage.
• Future plans for: Growth or Decline in usage, Changing cloud provider, Changing instance, families, Moving regions, Shifting to another computer-model (like containers, serverless architecture, etc.).
• The balance between savings over time and cash payments up front.
• Level of flexibility required.

Reference:

http://www.nodericks.com/aws-vs-azure-vs-google-vs-ibm-cloud-best/

https://www.tomsguide.com/features/aws-vs-azure-vs-google-cloud-vs-ibm-cloud-whats-the-best-cloud-environment

https://www.parkmycloud.com/blog/aws-vs-azure-vs-google-cloud-market-share/

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Google Cloud questions and explanation

 Question: What is GAE and GCE in GCP?

Solution : Google App Engine (GAE) and Google Compute Engine (GCE) are both used for deploying applications and are equally popular with small and large businesses. Google App Engine is a Platform as a Service (PaaS) solution that makes deployment easier.The Google Compute Engine on the other hand is an Infrastructure as a Service (IaaS) tool.

Question: PaaS vs IaaS: What’s the Difference?

Solution : PaaS refers to cloud-based platform services that provide developers with a framework to build custom applications. Therefore, PaaS isn’t delivering software over the internet but provides a platform that’s accessible to different developers to create software that’s delivered over the internet.

IaaS cloud-based infrastructure resources are delivered to organizations with virtualization technology that helps them build and manage their servers, network, data storage and operating systems. IaaS customers can control their own data infrastructure without having to physically manage it on-site.

Reference: https://www.parallels.com/blogs/ras/app-engine-vs-compute-engine/

Question: What are the cloud databases in GCP?

Solution:

Relational

  Bare Metal Solution for Oracle(Lift and shift Oracle workloads to Google Cloud),

  Cloud SQL(Managed MySQL, PostgreSQL, and SQL Server),  

Cloud Spanner(Cloud-native with unlimited scale, consistency, and 99.999% availability)

Key value

Cloud Bigtable(Cloud-native NoSQL wide-column store for large scale, low-latency workloads)

Document

  Firestore(Cloud-native NoSQL to easily develop rich mobile, web, and IoT applications)

Firebase Realtime Database(Store and sync data in real time)

In-memory

Memorystore(Fully managed Redis and Memcached for sub-millisecond data access)

Additional NoSQL

MongoDB Atlas(Global cloud database service for modern applications)

Google Cloud Partner Services(Managed offerings from our open source partner network, including MongoDB, Datastax, Redis Labs, and Neo4j)

Reference: https://cloud.google.com/products/databases

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How to specify ignore rules and exceptions from these rules for files and folder, that won’t be included in the build context in Docker(.dockerignore)

The .dockerignore file is the tool. It can help you to define the Docker build context you really need. Using this file, you can specify ignore rules and exceptions from these rules for files and folder, that won’t be included in the build context and thus won’t be packed into an archive and uploaded to the Docker server.

The .dockerignore file is similar to gitignore file. It is used by  the git tool. similarly to .gitignore file, it allows you to specify a pattern for files and folders that should be ignored by the Docker client when generating a build context. While .dockerignore file syntax used to describe ignore patterns is similar to .gitignore it’s not the same.

The .dockerignore pattern matching syntax is based on Go filepath.Match() function and includes some additions.

Here is he complete syntax for the .dockerignore:

Pattern:

{ term }
term:
'*' matches any sequence of non-Separator characters
'?' matches any single non-Separator character
'[' [ '^' ] { character-range } ']'
character class (must be non-empty)
c matches character c (c != '*', '?', '\\', '[')
'\\' c matches character c

character-range:
c matches character c (c != '\\', '-', ']')
'\\' c matches character c
lo '-' hi matches character c for lo <= c <= hi

additions:
'**' matches any number of directories (including zero)
'!' lines starting with ! (exclamation mark) can be used to make exceptions to exclusions
'#' lines starting with this character are ignored: use it for comments
________

Note: Using the ! character is pretty tricky. The combination of it and patterns before and after line with the ! character can be used to create more advanced rules.

Examples:

# ignore .git and .cache folders

.git

.cache

# ignore all *.class files in all folders, including build root

**/*.class

# ignore all markdown files (md) beside all README*.md other than README-secret.md

*.md

!README*.md

README-secret.md

Reference:

https://codefresh.io/docker-tutorial/not-ignore-dockerignore/

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