Edison  Stark

Edison Stark

1596765780

Google Cloud Spanner : A Revolutionary Relational Database

Cloud Spanner is a Relational Database but its different than traditional database such as MySQL , Amazon RDS or PostgreSQL. In this blog we will see why its different and why i think it is revolutionary .


Image for post

Table of Contents

  • Introduction to cloud spanner
  • Cloud Spanner is revolutionary
  • Configuring Cloud Spanner Instances Options
  • How Schema & Data Model Looks Like ?
  • How Replication Works In Cloud Spanner?
  • Follow Some Best Practices

Introduction to cloud spanner

  • Google Cloud Spanner is relational database management system like Cloud SQL on GCP. But it is different than traditional relational databases

What makes it different than Cloud SQL on GCP or Azure SQL or Amazon RDS ?

  • It is globally distributed, whereas Cloud SQL is regional.
  • It can scale horizontally , that means it can add more nodes to the cluster as data grows. Hence it can support any data size, while Cloud SQL has limitation of 10 TB.
  • It offers strong consistency despite of being distributed globally, this is cutting edge built on googles proprietary technologies.
  • Its is much expensive than Cloud SQL , hence should be used when data size requirement is more than 10 TB.

Cloud Spanner is revolutionary

  • Generally strong consistency can be achieved in vertically scalable databases ( ex Oracle, MySql, PostgreSql) but Horizontally scalable databases(Hbase, Cassandra etc.) are eventually consistent. Hence if we need strong ACID support we will use database like Oracle, MySql & i.e OLTP use cases. But if strong ACID support not required then we will use analytical database such as BigQuery, Snowflake , Redshift, HBase etc i.e OLAP use cases.
  • In Short Strong ACID Support -> OLTP Databases
  • No Strong ACID Support -> OLAP Databases
  • But Cloud spanner provide strong ACID support and its also horizontally scalable , that is indeed differentiator from the product out there in the market.

Configuring Cloud Spanner Instances Options

Cloud Spanner instance can be of type regional or multi-regional.

Regional Instance

  • Availability of 99.99 (4 nines)
  • Lower Write Latency
  • Less Expensive

Multi-Regional Instance

  • Availability of 99.999(5 nines)
  • Lower Read Latency
  • More Expensive

_⭐ ️ _Each node in Cloud Spanner cluster provides 10k QPS of read and 2k QPS of. writes with 2 TiB of storage.

#horizontal-scaling #transactional-database #rdbms #google-cloud-spanner #database

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Google Cloud Spanner : A Revolutionary Relational Database
Adaline  Kulas

Adaline Kulas

1594162500

Multi-cloud Spending: 8 Tips To Lower Cost

A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.

Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.

By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.

However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.

  • Deactivate underused or unattached resources

Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.

Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.

  • Figure out idle instances

Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.

Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.

  • Deploy monitoring mechanisms

The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.

For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.

#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market

Rusty  Shanahan

Rusty Shanahan

1597833840

Overview of Google Cloud Essentials Quest

If you looking to learn about Google Cloud in depth or in general with or without any prior knowledge in cloud computing, then you should definitely check this quest out, Link.

Google Could Essentials is an introductory level Quest which is useful to learn about the basic fundamentals of Google Cloud. From writing Cloud Shell commands and deploying my first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

Let’s see what was the Quest Outline:

  1. A Tour of Qwiklabs and Google Cloud
  2. Creating a Virtual Machine
  3. Getting Started with Cloud Shell & gcloud
  4. Kubernetes Engine: Qwik Start
  5. Set Up Network and HTTP Load Balancers

A Tour of Qwiklabs and Google Cloud was the first hands-on lab which basically gives an overview about Google Cloud. There were few questions to answers that will check your understanding about the topic and the rest was about accessing Google cloud console, projects in cloud console, roles and permissions, Cloud Shell and so on.

**Creating a Virtual Machine **was the second lab to create virtual machine and also connect NGINX web server to it. Compute Engine lets one create virtual machine whose resources live in certain regions or zones. NGINX web server is used as load balancer. The job of a load balancer is to distribute workloads across multiple computing resources. Creating these two along with a question would mark the end of the second lab.

#google-cloud-essentials #google #google-cloud #google-cloud-platform #cloud-computing #cloud

Ruth  Nabimanya

Ruth Nabimanya

1623224760

Backup database to Google Cloud Storage

A process to set up periodic database backup to Google Cloud Storage

I have a few small websites hosted on the Digital Ocean server. Each of them has a MySQL database and I wanted to regularly set uploading full database export to some independent location outside of Digital Ocean to sleep more calmly. Since my life revolves around Google Cloud, my preference for storage was clear. The goal is to use crontab to periodically run a bash script to execute MySQL database export and gsutil  command to copy a file to the Cloud Storage bucket. To configure the whole process there are several steps involved, which I will describe in this article. I interactions with the Google Cloud project, I am using web UI, although all steps could be done via the command-line interface.

1. Create a Cloud Storage bucket for backups

2. Create a Service Account

#database #mysql #google-cloud-platform #google-cloud-storage #backup database to google cloud storage #backups

Edison  Stark

Edison Stark

1596765780

Google Cloud Spanner : A Revolutionary Relational Database

Cloud Spanner is a Relational Database but its different than traditional database such as MySQL , Amazon RDS or PostgreSQL. In this blog we will see why its different and why i think it is revolutionary .


Image for post

Table of Contents

  • Introduction to cloud spanner
  • Cloud Spanner is revolutionary
  • Configuring Cloud Spanner Instances Options
  • How Schema & Data Model Looks Like ?
  • How Replication Works In Cloud Spanner?
  • Follow Some Best Practices

Introduction to cloud spanner

  • Google Cloud Spanner is relational database management system like Cloud SQL on GCP. But it is different than traditional relational databases

What makes it different than Cloud SQL on GCP or Azure SQL or Amazon RDS ?

  • It is globally distributed, whereas Cloud SQL is regional.
  • It can scale horizontally , that means it can add more nodes to the cluster as data grows. Hence it can support any data size, while Cloud SQL has limitation of 10 TB.
  • It offers strong consistency despite of being distributed globally, this is cutting edge built on googles proprietary technologies.
  • Its is much expensive than Cloud SQL , hence should be used when data size requirement is more than 10 TB.

Cloud Spanner is revolutionary

  • Generally strong consistency can be achieved in vertically scalable databases ( ex Oracle, MySql, PostgreSql) but Horizontally scalable databases(Hbase, Cassandra etc.) are eventually consistent. Hence if we need strong ACID support we will use database like Oracle, MySql & i.e OLTP use cases. But if strong ACID support not required then we will use analytical database such as BigQuery, Snowflake , Redshift, HBase etc i.e OLAP use cases.
  • In Short Strong ACID Support -> OLTP Databases
  • No Strong ACID Support -> OLAP Databases
  • But Cloud spanner provide strong ACID support and its also horizontally scalable , that is indeed differentiator from the product out there in the market.

Configuring Cloud Spanner Instances Options

Cloud Spanner instance can be of type regional or multi-regional.

Regional Instance

  • Availability of 99.99 (4 nines)
  • Lower Write Latency
  • Less Expensive

Multi-Regional Instance

  • Availability of 99.999(5 nines)
  • Lower Read Latency
  • More Expensive

_⭐ ️ _Each node in Cloud Spanner cluster provides 10k QPS of read and 2k QPS of. writes with 2 TiB of storage.

#horizontal-scaling #transactional-database #rdbms #google-cloud-spanner #database

Google Cloud: Caching Cloud Storage content with Cloud CDN

In this Lab, we will configure Cloud Content Delivery Network (Cloud CDN) for a Cloud Storage bucket and verify caching of an image. Cloud CDN uses Google’s globally distributed edge points of presence to cache HTTP(S) load-balanced content close to our users. Caching content at the edges of Google’s network provides faster delivery of content to our users while reducing serving costs.

For an up-to-date list of Google’s Cloud CDN cache sites, see https://cloud.google.com/cdn/docs/locations.

Task 1. Create and populate a Cloud Storage bucket

Cloud CDN content can originate from different types of backends:

  • Compute Engine virtual machine (VM) instance groups
  • Zonal network endpoint groups (NEGs)
  • Internet network endpoint groups (NEGs), for endpoints that are outside of Google Cloud (also known as custom origins)
  • Google Cloud Storage buckets

In this lab, we will configure a Cloud Storage bucket as the backend.

#google-cloud #google-cloud-platform #cloud #cloud storage #cloud cdn