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Cloud Compliance Regulations and Best Practices

Cloud Compliance Regulations and Best Practices

~5 minutes read

Cloud compliance refers to the need for organizations and cloud computing providers to comply with a set of standards and regulations established by industry guidelines, as well as local, national, and international laws. According to the compliance principle, a company can operate safely and efficiently only when it follows all the laws and requirements set out by the federal, state, and local governments.

Compliance has always been important as the consequences of compliance failures lead to regulatory fines, lawsuits, and reputational damage. Despite the relevance of this topic, there is still little understanding among companies of the existing compliance regulations, consequences of non-compliance, as well as what best practices are worth taking into account when choosing services offered by different cloud providers.

List of compliance regulations

Businesses should be compliant with many global regulations, such as HIPPA, PCI DSS, GDPR, ISO/IEC 27001, NIST, NERC, and so on. Typically, the regulations that apply to the on-premise software are also applied to the cloud-based infrastructures. However, some of the regulations relate specifically to the cloud.

The top cloud vendors earned certifications that meet global compliance requirements, including ISO 27001, PCI DSS, HIPAA, FedRAMP, etc. Note that cloud compliance isn’t only the cloud service provider’s responsibility: according to a shared responsibility model (we’ve talked about in our previous article), cloud vendors and companies work together to ensure compliance over their entire hybrid and multi-cloud network.

In order to understand, what your company dealing with, there’s a list of some general compliance requirements:

Health Insurance Portability and Accountability Act (HIPAA) is a US federal law that protects sensitive patient health information from being revealed without the patient’s permission. The healthcare industry can benefit from the HIPAA-compliant cloud tools, as they offer cost savings and remote file sharing.
Payment Card Industry Data Security Standard (PCI DSS) is an information security standard designed to increase the control of cardholder data to reduce credit card fraud. PCI DSS is relevant to the companies dealing with branded credit cards. Although the PCI Standard is mandated by the card brands, they are administered by the Payment Card Industry Security Standards Council (PCI SSC).
General Data Protection Regulation (GDPR) is a regulation applied to the organizations that provide customers with goods or services in the European Union (EU). Also, GDPR rules are related to the companies that collect and analyze data tied to EU residents.
National Institute of Standards and Technology Cybersecurity Framework (NIST CSF) is a voluntary framework that consists of best practices, standards, and guidelines helping to manage cybersecurity-related risks.
Sarbanes–Oxley (SOX) Act of 2002 is a United States federal law that establishes certain practices for auditing, reporting, and keeping financial records for public companies and corporations.
The North American Electric Reliability Corporation Critical Infrastructure Protection (NERC CIP) plan is a set of standards applied to regulate, monitor, and manage the cybersecurity of the Bulk Electric System (BES) in North America specifically.
Federal Risk and Authorization Management Program (FedRAMP) provides a standardized approach to security assessment, authorizations, and monitoring for cloud service offerings. FedRAMP empowers companies to use cloud technologies, considering the security and protection of federal information, and contributes to adopting only secure cloud solutions.
ISO/IEC 27001 is a requirement for how to establish, implement and manage information security. ISO stands for The International Organization for Standardization which is an independent, non-governmental international organization with an international membership of 163 national standard bodies.

Consequences of non-compliance

Failed audits

Let’s make it clear, failing a compliance audit itself isn’t that bad, and here’s why – audit emphasizes the weak spots. The most difficult part comes right after the audit when an organization has to correct the mistakes that caused the failure. It may take days, weeks, or even months to identify aspects that need improvements.

Financial costs

Non-compliance penalties can be harsh. Let’s take willful violations of HIPAA requirements as an example. In this case, fines can vary from $1,000 per violation and reach $50,000 per not corrected violation.

In the case of reckless violation of the Sarbanes-Oxley requirements, a CEO or CFO can be personally fined up to $1,000,000. If the violation is proven to be a willful one, the fine can go up to $5,000,000.

Don’t forget about the potential money loss due to the reputational damage, as clients and partners will hardly want to collaborate with the company breaking laws and neglecting the compliance requirements.

Legal consequences

The most concerning issues connected to compliance ignorance are criminal sentences, not to mention potential legal consequences from the parties affected by the organization’s failure to comply.

For instance, a business executive who violates Sarbanes-Oxley (SOX) certification requirements may not only pay up to a $5,000,000 fine but also be sentenced to 20 years in prison. The thing is, it’s not the end: if your company fails in handling the customer’s sensitive data and it results in serious damage, the customer can sue the company for that.

Compliance best practices

To mitigate challenges and risks like potential compliance violations, security threats, loss of visibility, and data breaches, IT governance and compliance professionals should take into account the following steps:

Choose only trustworthy cloud providers

Top cloud vendors like Amazon Web Services, Microsoft Azure, and Google Cloud are proven to be secure and compliant, as well as experienced to keep your cloud environment safe. They may help you meet global compliance requirements such as GDPR, PCI DSS, HIPAA, and others we’ve mentioned above.

Specify the responsibilities of the company and cloud provider

According to a shared responsibility model, security and compliance responsibilities are shared between the cloud service provider (it’s responsible for the security of the cloud, and the user or a company (it bears the responsibility for the security in the cloud).

It’s essential to learn who is responsible for what exactly and articulate it while signing the contract with the cloud provider. It will help to avoid the unpleasant situations of misunderstanding and ignorance of responsibilities by both sides of the agreement.

Speaking of which, we advise you to carefully read the terms and conditions of the contracts, as 62.7% of cloud providers don’t specify that customer data is owned by the customer itself, according to Kinsta. This creates a legal gray area where a provider could claim ownership of all your uploaded data.

Assemble the right team and educate your staff

Having a solid cloud provider isn’t enough to ensure your company is compliant. It’s also important to have the right people in place. Team members that have knowledge about cybersecurity offer valuable suggestions and provide relevant insights.

Additionally, it’s recommended to organize team meetings to explain the basics of security and compliance that should be implemented in the organization. You’ll never regret spending time on that once your workers are professionals in the field of cybersecurity, and make no crucial mistakes.

Implement regular compliance and security checks

It’s better to identify the problem while it’s not too late. So, to be aware of the current security state of the cloud environment, it’s recommended to conduct compliance and security checks on a regular basis. One more suggestion is to have two teams: one is responsible for the continuous checks, and another for urgent remediating issues.

Compliance tools

There are plenty of native tools that can facilitate your compliance teams’ work. Let’s have a look at the tools offered by each cloud provider individually, as well as take into account third-party tools.

Amazon Web Services (AWS)

AWS Lake Formation provides a data catalog that automatically discovers and tags data across the AWS cloud environment. It helps to define and manage security and auditing policies in a more organized way.
Amazon CloudFront is a content distribution service that offers a geo-restriction option, so users can access your content only if they’re in the whitelisted country. It’s used to avoid crossing geographical boundaries and violating compliance regulations.
AWS Config was created to monitor the security and compliance of your AWS environment. It allows to handle the resources inventory, as well as view the configuration history, and get notifications on all the configuration-related changes.

Microsoft Azure

Azure Security and Compliance Blueprints allows Microsoft Azure services customers to create, deploy, and manage compliant environments, including for certifications like ISO:27001, PCI DSS, and others.
Azure Security Center is used to handle security management and enable advanced threat protection across hybrid cloud workloads.
Azure Policy was created to define and enforce policies for keeping your cloud environment compliant with internal policies and external (regional and global) regulations.

Google Cloud Platform (GCP)

Google has a Cloud Compliance Resource Center that provides the compliance documentation, security certification list, and required information to help you support your compliance.

Third-party tools

There are lots of third-party tools in the market that help with monitoring the multi-cloud and hybrid cloud environments. Platforms like Binadox allow companies to connect various cloud accounts and manage them in one place, without switching between multiple dashboards and trying to interpret the data that is represented differently by each cloud vendor.

Moreover, Binadox can be configured to send security notifications to the team channels so that your team stayed aware of every single security threat and misconfiguration.

You can book a demo to find out more about the Binadox solution or try it for free and test all its features right away.

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Top 5 Cloud Computing Trends for 2022

Top 5 Cloud Computing Trends for 2022

~5 minutes read

Cloud adoption has been on an upward trajectory for over a decade now. In 2020 and 2021, cloud computing technology usage soared due to the global COVID-19 pandemic. Despite the fact that the epidemiological situation seems to have gone back to normal, the interest in the cloud didn’t decrease. Moreover, public cloud services are expected to grow by over 22% ($482 billion US dollars) in 2022, according to a Statista report.

As the cloud has become an integral part of the organizing life and work processes, it’s better to keep up with its latest updates not to miss anything important, and be ahead of competitors. In this article, we described 5 cloud trends for 2022.

Trend 1: Cloud delivery models shape the tech landscape

Hybrid cloud

The keynote of the year 2022 and beyond are customizable, flexible solutions that facilitate businesses’ agility and provide a competitive advantage to stay at the top of the market.

Back in the day, organizations had to choose between private and public solutions: the public cloud offered more accessible, pay-as-you-go services, while the private cloud systems provided companies with more control over the security of their sensitive data (due to location).

Hybrid cloud implementation gave companies the chance to get the best of both worlds: private and public solutions. According to Equinix, 93% of companies either expressed interest or already adopted a hybrid cloud. It allows low latency due to the ability of private cloud platforms to be cut down to handle specific tasks; and enforced security, provided by more reliable encryption methods used within the private cloud architecture.

Talking about cloud service providers, Microsoft Azure is an example of a public cloud vendor that allows businesses to keep commonly accessed data on public servers and store sensitive data on private servers to ensure better control.

Multi-cloud

Beyond hybrid models, many companies want to commit to multi-cloud solutions as well. TechJury predicts that by the end of 2022, 90% of businesses will have a multi-cloud architecture.

Multi-cloud means the deployment of two or more cloud platforms. This approach helps companies avoid vendor lock-in, as well as offers a better user experience by using fast, low-latency connections to significantly improve application response time. Also, with the use of several public clouds, organizations get the opportunity to scale easier and move data across platforms faster.

Still, this type of cloud model has its peculiarities: the management and monitoring of multiple cloud resources and their costs is a more complex task, so close attention to details and reliable tracking tools are required.

Serverless

On top of the two cloud-delivery models we’ve covered before, serverless cloud computing is also pivotal to the future IT landscape change. Mordor Intelligence claims that the popularity of serverless cloud computing is expected to grow by 22.6% in 2026.

Serverless cloud computing is a cloud model where infrastructure is orchestrated by cloud service providers, so businesses free themselves from managing and maintaining servers. That’s why this model is especially popular with developers – it allows them to focus only on building and running the applications. Additionally, serverless cloud platforms are scalable and can easily be adapted to changing needs or demands of the customers.

Trend 2: AI and ML implementation for business intelligence

The market value of artificial intelligence will reach $850.61 billion by 2028, according to Verified Market Research.

Machine learning and artificial intelligence offer marvelous potential benefits for companies: they both allow the processing of large amounts of data and do it faster, easier, and more effectively, without human involvement. The opportunity to automate various operations saves a lot of time and allows team members to concentrate on more complex tasks.

Also, ML and AI provide businesses with insights into industry trends, customer preferences, and behavior. This feature helps organizations understand their target audience more clearly and satisfy their needs.

Trend 3: Focus on security and compliance solutions

Today businesses are concerned about the security of their cloud resources and the compliance of their data as never before. It’s explained by the number of cyber-attacks that doubled up during the last two years.

According to Accenture’s Cost of Cybercrime Study, 43% of cyber attacks are aimed at small businesses, but only 14% of the companies are prepared to defend themselves.

Cloud providers respond to the remaining and growing interest in security by offering improved security features and compliance certifications. There are some examples of such solutions:

Cloud disaster recovery (CDR) refers to the strategies and cloud-based services that enterprises use to back up data and restore it to resume normal operations after a disaster. Also, CDR is used to balance workload and replicate cloud services and products across several cloud vendors.
Secure Access Service Edge (SASE) is a cloud security architecture used for access management and connectivity control between devices, cloud applications, on-premises infrastructures, and so on. It serves as an SSO service that provides companies with facilitated access to their multiple cloud apps alongside the highest levels of security and compliance. Gartner’s study shows that at least 40% of companies will create firm commitments to incorporate SASE in their toolkit.

Trend 4: Sustainability is a top priority

Companies started to pay closer attention to environmental issues, as nowadays customers want to see a sustainable approach in all aspects of their life, including work.

Cloud computing deployment is more sustainable than local computing – the usage of cloud platforms and services reduces an individual company’s carbon footprint and physical waste. According to Northwestern, companies can potentially reduce energy consumption by 87% if they move their applications to the cloud.

Even though cloud computing helps companies to run businesses according to sustainability concepts, the cloud still impacts the environment. Computing currently contributes 1.4% towards the global greenhouse gas footprint, and it’s forecasted to reach 14% by 2040.

According to these statistics, it’s clear that cloud providers need to adapt their services to protect our planet. They’ve already started solving this issue in some different ways. For instance, Google is the largest corporate buyer of renewable energy in the world. Additionally, this company uses machine learning trained on historical weather data to adapt its data centers’ cooling systems proactively.

In turn, Microsoft is experimenting with aquatic data centers to reduce the power used by artificial cooling systems. Amazon Web Services want to reach 100% renewable energy use by 2025, by creating solar and wind power projects.

Trend 5: Taking cloud cost optimization seriously

A lot of companies migrated to the cloud as it allowed them to quickly respond to demand fluctuation – scale up or down resources based on a workload. The opportunity to scale easier was game-changing as the whole process of “purchasing additional resources” took less time and was almost effortless.

Sooner companies realized that they purchase far more resources than needed. First of all, because it was easy and required no manual installment. Secondly, companies couldn’t get a full consumption picture as used multiple cloud vendors’ products. That is why sooner they started to pay extra attention to the cost-saving practices offered by cloud providers (native tools) and third-party solutions. Without careful cloud assets management and its continuous optimization, there are more chances to go over the budget.

With the advent of multi-cloud, a new generation of cloud management platforms emerged to help businesses understand, optimize and predict their monthly cloud costs. One example of a cloud management solution is Binadox. It provides users with a clear picture of their expenditures across multiple cloud platforms.

Additionally, it has numerous features like tagging, rightsizing, and automation rules that help companies not only reduce cloud bills but also facilitate the decision-making process. With the help of such tools as Binadox cost optimization becomes achievable and realistic in 2022.

Want to try Binadox? Sign up for a free account.

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Google Cloud Platform Integration

Google Cloud Platform Integration

~5 minutes read

This guide provides information on how to integrate a GCP account with the cloud management and cost optimization platform Binadox to take control of your cloud assets and reduce expenses.

To integrate Binadox with the Google Cloud Platform, you need to follow 4 steps:

1. Set up Cloud Billing data export to BigQuery;

2. Run the Script from the Cloud Shell;

3. Create a JSON file for the service account;

4. Integrate GCP with Binadox using the JSON file.

Further, these steps are described in detail. To enlarge images in the instructions, click on them.

1. Set up Cloud Billing data export to BigQuery

Cloud Billing export to BigQuery implies the export of Google cloud billing data (such as usage, cost, and pricing) to a specified BigQuery dataset throughout the day at regular intervals.

1. Sign in to the Google Cloud console.

2. Click on the menu button at the top left corner to open a portal menu. In the navigation pane on the left, click Cloud overview > Dashboard.

3. In a Dashboard either select an existing project or create a new project to store Cloud Billing data there.

To create a new project, enter the Project name, Organization, and Location. Click the Create button.

4. Create a BigQuery dataset in which the data will be stored. To do that, you need to complete the following steps:

Go to Dashboard > Resources > BigQuery, or use the search bar at the top.

On the BigQuery page, in the navigation pane on the left, click BigQuery Studio. On the left side of the workspace page, you will see an ID of the created project. Click the three dots menu on the right and select Create dataset;

In the popped-out Create dataset window on the right, enter the dataset ID, select the location and select when the default table expires (or leave this field empty). Once this step is completed, click Create Dataset button.

5. Enable the BigQuery Data Transfer Service API. To complete this step, go to APIs and services > Library. In Category, select Big Data. Find BigQuery Data Transfer API. Click Enable button.

6. After API is enabled, you will see a modal window with the suggestion to create a transfer. Leave this step incomplete, as the transfer will be created automatically by the script.

7. Enable billing on the project. To do that, in the navigation pane on the left, click Billing. If the project has no billing account, link a billing account. Enter the name of the account and click the Set Account button.

Troubleshooting:

If you reached the limit of projects on which you can enable billing, you can request an increase of your billing quota, or click Manage Billing Account and delete the accounts that are linked to the deleted projects. Then try to link the billing account to the newly created project again.

8. Enable Cloud Billing export of cost data and pricing data to be written into the dataset:

In the navigation pane on the left, click Billing export;
On the Billing Export page, in the BigQuery export tab (selected by default) edit the settings of the Standard usage cost and Detailed usage cost;

Click the Edit Settings button, select a created dataset and click the Save button. This action needs to be done for all two parameters – Standard usage cost and Detailed usage cost.

2. Run the Script from the Cloud Shell (within the cloud console)

Binadox script creates a Role with Permissions, Data Transfer, and Service Account, as well as enables APIs required for getting access to the Billing information. To have the script running you need to follow the steps below:

1. Click on the Activate Cloud Shell icon on the header. Wait for the cloud console to open.

2. Copy and paste the command into the opened cloud console. You will need to authorize Google to run the script. In a popped-out Authorize Cloud Shell modal window, click the Authorize button.

curl -o- https://gist.githubusercontent.com/binadox-public/7fcc24a9ad25f4564cdb23fb7ec39087/raw/a12600c02399daa188269e9a16763803e1b17972/setup-binadox-billing.sh | bash

Troubleshooting:

Error text:
FAILED_PRECONDITION: You can’t create a role with role_id [name] where there is an existing role with that role_id in a deleted state.
Solution: Undelete the existing role with role_id [name], from your billing project, and run the script again.

Error text:
Resource in a project is the subject of a conflict.
Solution: No additional actions are required.

3. Once the script is successful, you can close the Cloud Shell console and proceed to the next step.

3. Create a JSON file for the required service account

1. A service account is created automatically by the script (view Clause 2).

2. To create a JSON file for the service account, click APIs&Services.

3. Once you’re on the API&Services page, proceed to the Credentials section.

4. Click on the email of the Service Account called “Binadox Configurer”.

5. You will be redirected to the Service account details page. Proceed to the Keys tab located at the top of the page.

6. On the Keys page, click on the Add Key button and then select Create new key from the drop-down list.

7. In a popped-out modal window, download a file that contains the private key. Choose JSON key type. Click the Create button.

7. Save the JSON file to your computer.

4. Integrate your GCP with Binadox using the downloaded JSON file

1. Log into your Binadox accont.

2. There are two main flows to connect a cloud account:

In case when you have no cloud accounts connected yet, click Home in the navigation pane on the left. Choose a cloud account you want to connect to and click the Connect button.
In case you have connected cloud accounts, click Home in the navigation pane on the left. Select the Cloud providers card and click the Manage button. In the Cloud Utilization Dashboard, click the Add Account button in the Cloud Accounts tab. Click on the Google Cloud Platform icon.

3. You will be redirected to the Connection page.

4. Copy the data from the downloaded JSON file and paste it to the Connection parameters field. Click the Connect button.

5. Google Cloud connection with Binadox is established.

Note:

You will be able to view GCP cost data in Binadox a day after integration.

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Microsoft Azure Integration

Microsoft Azure Integration

~5 minutes read

This guide illustrates how to integrate Microsoft Azure with the cloud cost optimization platform Binadox to plan, analyze and reduce infrastructure costs.

To successfully integrate Binadox with Microsoft Azure, you need to follow 8 steps:

1. Create an Application in Azure Active Directory (AD);

2. Get Secret Value in Certificates & secrets;

3. Assign Roles;

4. Create Storage Accounts;

5. Get Access Keys;

6. Create Containers;

7. Export Billing Information in Cost Management + Billing;

8. Create New Connection for Microsoft Azure in Binadox.

Further, you can find each step described in detail. To enlarge images in instruction – click on it.

1. Create an Application in Azure Active Directory (AD)

1. Sign in to the Microsoft Azure portal.

2. Proceed to Azure Active Directory. To find it you need to click on the menu button at the top left corner to open a portal menu. In the navigation pane on the left, click All services.

3. Select Azure Directory from the list of services or select Identity or Security > Azure Active Directory.

4. In the navigation pane on the left, click App registration. Then proceed to the New Registration at the top left corner of the App registration page. To register an application:

Enter application name;
Select account type – Accounts in this organizational directory only;
In a drop-down list, select a platform – Web;
Enter redirect URI – https://app.binadox.com/api/1/aplications/authorize/try;
Click the Register button.

5. Once the application is created, you’ll be redirected to the newly created application page. Here you can copy the Application (client) ID and Directory (tenant) ID to enter them on the Binadox connection page.

2. Get Secret Value in Certificates & secrets

1. On the newly created application page, in the navigation pane on left, click Certificates & secrets tab.

2. Proceed to the Client secrets tab on the Certificates & secrets page; click New client secret.

3. In the popped-out Add a client secret window on the right, enter the description, and select when the secret expires. Once this step is completed, click Add button.

4. When Secret Value is created, copy it to the clipboard. You will need this credential when integrating Microsoft Azure with Binadox.

3. Assign Roles

You need to Assign roles to receive saving and security recommendations and automate your cloud using Binadox rules.

In the navigation pane on the left, click All services. Proceed to Subscriptions service.

Select the “Pay-as-you-go” subscription name.

Once you’re at the “Pay-as-you-go” page, in the navigation pane on the left proceed to the Access control (IAM) section. Click the Add button. In the drop-down list, select Add role assignment.

On the Add role assignment page, select the Contributor line. Proceed to the Members tab. Click the Select members button.

In the popped-out Select members window on the right, enter the name of the created application (view Clause 1) in the search string. Select the app from the list and click the Select button. Once this step is done, click Review + assign button. You’ll see the success message once the role is assigned.

4. Create Storage Accounts

1. Proceed to Storage accounts. To find it, click on the menu button at the top left corner to open a portal menu. In the navigation pane on the left, click All services.

2. In the navigation pane on the left, select Storage. On the Storage page, select Storage accounts.

3. Click the Create button on the top left corner of the Storage accounts page.

4. Create a storage account. To do that follow the steps below:

4.1 First of all, set the parameters in the Basics tab:

Select Pay-as-you-go subscription;
Select resource group – BinadoxApp, or create a new one. Enter its name and save it;
Enter Storage account name;
Select a region;
Choose Standard performance;
Leave default Redundancy data unchanged.

4.2 Then, turn to the Advanced tab:

Leave all the data unchanged, except one – Minimum TLS version. Select Version 1.0.

4.3 Next, leave the data unchanged in the Networking tab, Data protection tab, and Tags tab.

4.4 Scroll down the information in the Review + create tab, review the data, scroll down the page and click Create.

4.5 Once the creation of the Storage account is completed, click the Go to resource button.

5. Get Access Keys

1. In the navigation pane on the left, select the Access keys section.

2. Click the Show keys button on the top left corner of the Access keys page.

3. Copy the Connection string of the Key 1 to the clipboard.

6. Create Containers

1. In the navigation pane on the left, click Containers.

2. Click the Container button on the top left corner of the Containers page.

3. In the popped-out New Container window on the right, enter the name of the container, and select Public access level – Private (no anonymous access). Once this step is completed, click the Create button.

4. Copy the name of the created container to use it for integration with Binadox.

7. Export Billing Information in Cost Management + Billing

1. Click on the menu button at the top left corner to open a portal menu. In the navigation pane on the left, click All services.

2. In the navigation pane on the left, select the All section.

3. Proceed to the Cost Management + Billing page.

4. In the navigation pane on the left, click Exports (in the Settings section).

5. Click Add on the top left corner of the Exports page.

6. On the New Export page:

Enter the name of the export in Export details.
Select Actual cost (Usage and Purchases) in Metric.
Export type – Daily export of month-to-date costs.
Select the date of the NEXT day.
Select Use existing storage.

Select your subscription.
Select the storage account you’ve created (view Clause 3).
Paste the name of the newly created container (view Clause 5).
Create Directory path name.
Click the Create button.

7. After the export is created, select it and click Run now at the top of the page. After a few seconds, the data will be pulled up.

8. Create New Connection for Microsoft Azure in Binadox

1. Log into your Binadox account.

2. There are two main flows to connect a cloud account:

In case you have no cloud accounts connected yet, click Home in the navigation pane on the left. Choose a cloud account you want to connect to and click the Connect button.
In case you have connected cloud accounts, click Home in the navigation pane on the left. Select the Cloud providers card and click the Manage button. In the Cloud Utilization Dashboard, click the Add Account button in the Cloud Accounts tab. Click on the Microsoft Azure icon.

3. After taking the previous step, you will be redirected to the Connection page. On the connection page, enter the Application (client) ID, Client Secret Value, Directory (tenant) ID, Connection string, and Container Name into the corresponding fields (see Clauses 1, 2, 4, and 5 ). Click Connect.

4. Microsoft Azure connection with Binadox is established.

Note:

You will be able to view Microsoft Azure cost data for the past 30 days in Binadox immediately after integration.

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FinOps vs DevOps Approach to Optimizing Costs

FinOps vs DevOps Approach to Optimizing Costs

~5 minutes read

The finance teams and the engineering teams should work together to optimize cloud costs, as huge cloud expenses affect the business negatively. Financial experts should consider the best practices of the tech world to work effectively. Developers, in their turn, should think about the financial consequences of their technical decisions.

However, many companies face the situation when the finance team offers cost reduction solutions that contradict the engineering team’s perspective. It makes the conversation between two departments adversarial, as both teams take into account only their departments’ efficiency metrics.

In this article, we’re going to explain why the IT department should take part in the cloud cost optimization process, too. Also, we’ll make the arguments proving that cloud costs aren’t only the finance team’s responsibility.

Below we listed 4 reasons why cloud cost optimization isn’t only the FinOps team’s responsibility.

Reason 1: DevOps team CAN and SHOULD control cloud costs

Developers usually choose cloud services based on their own judgments. It has a positive side, as they can pick the products that are more convenient in terms of usage, increase productivity, and fulfill their tech needs. However, it is pretty common when the IT team doesn’t consider how much these services would cost to a company.

So, it is better to create an environment where tech specialists taking part in decision-making are informed of cloud services costs as well. In fact, cloud services cost should become one of the top priorities of developers in addition to cloud architecture governance and maintenance.

The perfect scenario for two departments’ collaboration should be the following:

The DevOps team forms the extensive list of required operation services and then presents reasons for choosing a particular service together with its cost to the FinOps team. That would bring more clarity to the FinOps team when forming and allocating cloud budget, as well as when looking for possible ways to cut expenses.

FinOps marks which services are strategically important and business-critical so can not be replaced by cheaper ones or simply eliminated. What is more important, Finances at this stage can also present reports on the most cost-driving services or resources. That would let tech departments re-analyze current architecture and think about in which ways they can make cloud usage more cost-efficient.

Reason 2: Teamwork encourages profitability

Even though it’s faster to make decisions on your own, there are good chances that the financial department condemns itself to select an inefficient solution.

Finance and tech should work like left and right brains: while one is busy with finding a creative solution, the other estimates whether this solution is practical or not. All the defined ideas can be discussed with the leadership team or a business owner, which is the third – and final – party taking part in the decision-making process.

Teamwork eliminates energy-consuming disputes between IT and financial departments.

Reason 3: Cloud cost data interpretation

Too much information (TMI) is a significant problem for the financial department, especially concerning cloud cost optimization. Typically, information in cloud bills is overloaded and confusing, some of the data isn’t necessarily relevant to the specialist trying to examine and understand it. As a result, it becomes harder to explain to the business owners what exactly went wrong in any given month.

The possible solution for different decision-makers here is to learn and interpret cost data that are relevant to their expertise. Let’s clarify the roles in the shared responsibility model applied for the cloud cost optimization process. It will help you to see what different departments should focus on.

The finance team’s main task is to have a global awareness of the real cost of the cloud architecture: instances, services, storage, and other resources. This information allows businesses to understand the most and least profitable and efficient applications and features.

The financial department also manages cloud budgets and makes sure the budget is spent wisely. What’s more important, the FinOps team creates reports which can be used for forming cost optimization recommendations.

It’s vital to consider that the role of finance is not to learn cloud computing and discover the details of instances deployment and data migration. If a financial expert in your company has this knowledge, it’s an added advantage, however, usually, the tech team takes that role.

The developers have more knowledge of what happens in the cloud. They can assist the finance department in avoiding cloud cost optimization mistakes. In fact, tech guys are more qualified to optimize cloud costs than financial specialists.

Due to technical know-how, devs can allocate computing resources, choose the right size of instance and type of storage, and so on – all of this influences cloud costs. Developers can also use external tools, identify hidden costs, and assume where exactly huge cloud expenditures come from.

Reason 4: Avoiding development slowdowns

There’s a common misperception among tech guys that thinking about the cost while developing will slow them down. In reality, it’s quite the opposite – having access to real-time cost data can actually increase the pace of development. Organizations that are willing to take cost as an operational metric can build more solid systems and speed up their modernization.

As the cloud can be scaled infinitely, developers can build their applications using maximum resources. However, we recommend learning to use just the capacity they really need instead. It will cut down on unnecessary waste.

Cloud cost optimization for DevOps and beyond

The responsibility for the cloud cost optimization process should be evenly distributed between the finance department and cloud architects or developers. Confronting conversations can be easily mitigated when both parties have sufficient information on costs. For this purpose, all of them need the right tool.

Binadox has features allowing financial and tech teams to have a deeper look into cloud costs and the consumption rates of the company’s cloud resources and services.

Book a demo to learn about Binadox cloud cost optimization solutions and opportunities. Start a free 14-day trial to establish a proper cost management process.

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Basic Cloud Computing Terminology

Basic Cloud Computing Terminology

~5 minutes read

Those who deploy multi-cloud architecture may have some issues with the cloud computing terminology, as well-known cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) have peculiar names for their services and products.

As the naming difference may be misleading for the majority of users and business executives, in this paper, we’d like to discuss how cloud services are called across AWS, GCP, and Azure. Also, we’re going to explain basic cloud terminology.

Computing

Instances and Virtual Machines (VMs)

Instances and virtual machines provide your business with cloud computing power, delivering memory, CPU, networking capacity, and storage. Each instance operates on a digital version of a physical machine – a virtual one. VMs can store data, run programs, and operating systems, as well as execute other computing functions.

Cloud providers refer to the VMs and instances differently: in Azure, it’s actually Virtual Machines (VMs), Amazon calls them Elastic Cloud Compute (EC2), and Google Cloud uses Compute Engine.

Platform-as-a-Service

Platform as a service (PaaS) is a cloud computing model where a third-party provider delivers hardware and software tools to users over the internet. Usually, these tools are needed for application development.

Azure and Google prefer straightforward product namings, which can be illustrated by their Platform-as-a-Service products — they offer Azure App Service, and App Engine Environment, respectively. Meanwhile, AWS likes a more creative naming approach, that’s why it has Elastic Beanstalk for deploying web applications and Amazon Lightsail for Virtual Private Servers (VPS).

Instances and Virtual Machines, and PaaS

Serverless Functions and FaaS

Both Function-as-a-Service (FaaS) and Serverless Functions refer to cloud computing services that free up developers from constant infrastructure management. When FaaS and Serverless technologies are used developers can focus primarily on building new features and improving the product.

A Serverless Function (Serverless) is a computing model where infrastructure orchestration is performed by cloud providers. Serverless seeks to exclude the management and configuration tasks giving users the opportunity to concentrate on building and running the applications.

FaaS allows developers to easily create software functions in a cloud – they still create the application logic, yet the code is executed in stateless compute instances that are orchestrated by the cloud service provider.

Talking about cross-vendors naming, Amazon’s pay-as-you-go service for executing code is called AWS Lambda, Microsoft uses Azure Functions, GCP – Google Cloud Functions for comparable serverless computing (view the table below).

Containers

Containers are packages of software that contain all of the vital elements to run in any environment: from a private data center to the public cloud. Cloud vendors also provide their users with open-source solutions like Kubernetes. They allow customers to deploy, automate, scale, as well as manage containerized applications.

Managed container services for Amazon is Elastic Kubernetes Service (EKS), Azure has Kubernetes Service, and Google Cloud Platform offers Google Kubernetes Engine. Amazon, Microsoft, and Google provide their users with the services for container management through AWS EC2 Container Service (ECS), Azure Container Service (AKS), and Google Cloud Run.

Containers services across AWS, Azure and GCP

Storage

Cloud computing provides its users with numerous storage types. The main three kinds are block storage, object storage, and file storage.

Object Storage

Object storage is typically used for read-only access, meaning that the file cannot be altered once it’s in the cloud, so the only option here is to reupload the files entirely. You can also retrieve the older variations of a file using the option called “versioning”.

So, standard object storage provided by Amazon is Simple Storage Service (S3), Azure has Azure Blob Storage, and Google offers Google Cloud Storage.

Block Storage

Block storage is an approach to data storage in which each storage volume acts as an individual hard drive that is configured by the storage administrator. This type of storage is designed for file systems, databases, and files where users require immediate read or write access. As a matter of fact, it may include regularly updated data.

The naming for this type of storage service is the following: Amazon has Elastic Block Store (EBS), Azure refers to its service as Azure Disk Storage, and Google calls this type of storage service Google Persistent Disk.

Hot and Cold Storage

What’s also worth considering is how frequently users plan to access their data. So, the standard storage type is usually called “hot”, as it’s deployed for ongoing use. “Cold” storage is long-term storage. Such services generally imply infrequent and archival access, which is reflected in their names.

Amazon offers S3 Infrequent Access, Glacier Instant Retrieval, Glacier Flexible Retrieval, and Glacier Deep Archive. Azure has Archive and Cool Blob Storage, and Google Cloud’s services include Nearline, Coldline, and Archive Storage.

File Systems

Naturally, users need and want to keep their files organized. Cloud file storage is exactly what they need in this case, as it’s a method for storing data in the cloud that provides servers and applications access to data through shared file systems.

Amazon calls its file storage Elastic File System (EFS), Azure refers to this kind of storage as Azure Files, and GCP offers Google Cloud Filestore. Each cloud provider also offers backup and disaster recovery capabilities in order to be fully prepared, just in case.

Database, Networking, and Security

Customers can ensure the security of their clouds using options offered by cloud providers. These options include security services, as well as networking and database services. Let’s consider them one by one.

Database

A cloud database is a database service built and accessed through a cloud platform. It serves almost the same functions as a traditional database and has cloud computing’s flexibility.

All three providers offer managed databases as a service: AWS calls it Amazon RDS, Azure refers to it as SQL Managed Instances, and Google has Cloud SQL. Also, there are services that have serverless options: AWS refers to its service as Amazon Aurora, Microsoft has Azure SQL Database, and Google calls the service Cloud Spanner.

Networking

One of the cloud’s benefits is reliable data access regardless of the data location. It’s provided by cloud networking, which offers connectivity to and between applications, and workloads across clouds and services.

There are also content delivery networks that serve as edge computing, meaning the data is stored closer to the user. Each cloud vendor has its own content delivery network. Microsoft and GCP refer to such networks as Azure Content Delivery Network (CDN) and Cloud CDN or CDN Interconnect, respectively. Amazon, in turn, calls it Amazon CloudFront.

Load balancing is also an essential part of handling network traffic. With load balancing, cloud users can distribute their workloads and traffic across multiple targets in multiple Availability Zones (AZs), and reduce costs at the same time. Each cloud provider offers its own load balancers to help achieve these tasks. AWS has Elastic Load Balancer (ELB), Microsoft offers Azure Load Balancer or Application Gateway, and GCP provides its users with the service called Cloud Load Balancer.

Customers that would like to provision their cloud assets, can also choose from the various private networks offered by the cloud vendors. A virtual private cloud (VPC) is an isolated private cloud that is securely hosted within a public cloud. VPC users can run host their websites or blogs, for instance, store their data, however, in this case, the private cloud is hosted remotely by a public cloud provider. Amazon’s private cloud is actually called Virtual Private Cloud (VPC), GCP uses a similar naming for this service – Google Virtual Private Cloud (VPC), and Microsoft has Virtual Network (VNet).

You can observe network service names across main cloud providers in the table below.

Networking services naming across AWS, Azure, and GCP

Security

Security is one of the most concerning matters that bother all cloud users. AWS provides a security solution called Identity and Access Management (IAM) to manage user access to the services and resources. Azure has Azure Active Directory. And Google has similar capabilities in Google Cloud Identity and Access Management (IAM).

AWS, Azure and GCP authentication and authorization services

Additionally, AWS, GCP, and Azure have Security Groups that contain a list of security rules that allow or deny network traffic to resources. The name of such groups differs across vendors, so, in Amazon, it is a Security Group, Azure offers a Network Security Group, and GCP refers to them as Compute Engine Firewall Rules.

It’s also worth mentioning that to ensure the security of your cloud environment, you should understand what the shared responsibility model is and what role you play in it. According to this model, the cloud vendor is responsible for the security of the cloud: physical hardware, software, and global infrastructure. You, as a customer, are responsible for the security in the cloud — data management, networking, and operating systems orchestration, as well as identity and access management, and so on.

Savings opportunities

Each cloud provider offers different discounts for long-term commitments. For instance, AWS has Reserved Instances (RIs) that allow users to achieve savings of up to 72%. Azure offers Reserved Virtual Machine (VM) Instances with a similar volume of discount.

These cloud vendors allow customers to pay for capacity for a one-year or three-year term. Additionally, Amazon offers Standard RIs. Users can sell them back to other AWS customers if they don’t need them anymore. Also, they can purchase Convertible RIs which can be exchanged for different configurations or sizes, however, there is no possibility to resell them. Azure can let you cancel an RI but with a prorated penalty.

Talking about Google, this cloud provider doesn’t offer Reserved Instances but gives its customers the opportunity to have a committed use discount for certain VMs and services instead. GCP claims that the savings, in this case, reach up to 70% in comparison with the on-demand pricing.There is one offering that sets AWS apart from other cloud providers – Savings Plans. This option is similar to Reserved Instances, but Savings Plans are less stable, as the provider can take them back any moment it needs them.

Get more from each cloud provider

The enlisted cloud terminology categories cover just a small part of the services cloud vendors can offer. To stay within the allocated budget these services should be properly managed.

A cloud management platform like Binadox can assist in this task. It provides total visibility of cloud resources used within a company. With Binadox it is easier to analyze consumption patterns, identify wasteful resources and manage them based on established policies.

What’s more, Binadox enables you to maintain security and compliance, automate numerous operations and be aware of all the ongoing processes.

Want to check the advantages of using a cloud management platform?

Sign up for a free trial period or book a demo.

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Introduction to Cloud Cost Intelligence

Introduction to Cloud Cost Intelligence

~5 minutes read

According to G2, 61% of organizations plan to optimize their cloud for cost savings, making it the top initiative. Trying to gain maximum profit, many businesses want to jump right to reducing cloud costs, but they forget that initially, they need to get the greater visibility of deployed resources.

Even when completing these tasks, there is still more they can do for saving their budget – they can learn to predict future cloud costs and solve the issues in their emerging state. That’s when cost intelligence comes into the picture, as it helps IT and FinOps teams make better decisions regarding cost allocation. Let’s understand what stands behind the term “cloud cost intelligence” first.

What is cloud cost intelligence?

When finding out about cloud cost intelligence for the first time, many wonder whether this term stands for cloud cost optimization or cost management. In fact, cloud cost management and optimization are more about actions taken, as they help companies control their cloud spendings and reduce them.

At the same time, cost intelligence is more about awareness, as it illustrates how cloud expenditures affect the bottom line of the business, as well as makes it easier to take smart cloud cost decisions.

Cloud cost intelligence allows business executives to answer such questions as:

What generates cloud costs?
How can costs be reduced?
Can future costs be predicted?

Getting deeper into the cloud cost intelligence metrics will help you answer these questions.

Cloud cost intelligence metrics

Let’s discover metrics that facilitate cloud cost intelligence implementation in a company. There are three types of them: cost transparency metrics, cloud cost optimization metrics, and cost forecasting ones.

Cost transparency metrics

Cost transparency, as its name indicates, allows companies to view where exactly and how money is spent within the organization. The cost transparency metrics usually depend on a company’s needs, so we’ll look at some of the most common ones.

Overall spend

First things first: understand your total cloud spend. It’s an easy task if you run single-cloud architecture, as you can see the overall spending at the top of your cloud bill. However, it’s more difficult to view all the costs across several cloud providers and different types of architectures.

For those who use a multi-cloud or hybrid cloud environment, it is more rational to adopt a third-party cloud management tool like Binadox. It allows a unified view of overall spending for multiple cloud accounts taken from different vendors.

Cost per service

Understanding which costs particular services generate is crucial for cloud inventory. It helps to identify the least used resources and realize which of them aren’t mission-critical and can be replaced by more profitable ones.

Utilized vs. unused resources spending

There’s a good chance that you have spare EC2 instances that are deployed for rapid demand spikes during seasonal occasions, for instance, Christmas or Black Friday. These instances are underutilized, or even worse, unused at all for the major part of the year.

According to the AWS insider report, 35% of cloud spending is wasted. It is good practice to identify wasted/unused resources that drive huge costs and start using them to the fullest extent, rightsize, or eliminate them.

In Binadox, you can get rightsizing recommendations based on your current workload. These recommendations include the percentage of instance utilization, its current cost, as well as the suggestion for a more profitable instance size paired with its cost.

Cost optimization metrics

Cost optimization stands for the practices that help businesses to organize their cloud spending in an optimal manner. Typically this phase requires companies to look for ways of cutting down their cloud costs.

Let’s take a closer look at the most common cloud cost optimization metrics.

Potential savings

The potential savings metric seeks to understand the maximum possible impact of optimizing the cloud infrastructure. If you’re deploying a cloud cost management tool, you might already receive optimization recommendations and get the idea of what stands behind it.

There are several kinds of recommendations: they may be for purchasing Reserved Instances, rightsizing existing instances, or eliminating idle instances and unused cloud services.

Realized savings

If potential savings mean the maximum possible savings, then realized savings illustrate how much was actually saved. It means that not all saving opportunities translate into real savings.

So, this metric gives the organizations’ executives the opportunity to see whether the business is able to implement suggested cost optimization practices or not, and take the necessary measures based on this information.

Cost forecasting metrics

The ability to predict cloud costs is the pillar upon which cloud economics rests. Imagine how the process of capacity and budget planning will change if we find a way to accurately forecast the expenditures.

This task can be accomplished by looking at historical usage data and consumption patterns. Machine learning can assist in this case, as it provides you with large amounts of contextual data. Pay attention to the following metrics when forecasting your future cloud costs.

Budgeted vs. actual spending

This metric seeks to realize the expected cloud spending and compare it to the real one, which, in turn, helps companies to understand how they can manage their financial assets more efficiently.

Once you’ve managed to map costs to budgets, it becomes easier to see if the organization has a catastrophic money waste, or it’s performing well. It also simplifies the recognition of whether you’re going over the budget, or you’re under-budgeted and need more money to accomplish your fundamental goals.

Additionally, with the awareness of the current situation and budgeting details, it is easier to plan the volume of capacity you may need in the future and make better decisions around upfront commitments like AWS Reserved Instances (RIs) or Savings Plans.

Forecasted spending

The forecasted spending metric seeks to identify the future impact of cloud spending on the business, as well as helps the companies avoid getting their budgets down the drain.

The budgeted vs. actual spending means the comparison between expectations and reality. Meanwhile, the ability to predict future spending gives FinOps teams the opportunity to set a budget based on their forecast, then track and compare it to the set budget. So, forecasting the upcoming cloud costs is all about learning to predict and be ready to address the cost-related issues before they turn into a huge problem.

In Binadox you can set the daily budget in the Cloud Utilization Dashboard and receive a notification when the set budget is exceeded. It helps minimize overspending immediately. Also, on the Cloud Utilization Dashboard, you can view the cloud resources consumption patterns and check whether the budget is allocated wisely or not.

Cloud cost intelligence with cloud providers

Previously we’ve discussed the possibility to use third-party tools to achieve cloud cost intelligence, and this approach is the most beneficial one in the case of multi-cloud or hybrid cloud architecture deployment.

Those who are devoted to a single cloud provider can use native cost monitoring tools.

AWS Cost Explorer

AWS Cost Explorer offers a detailed overview of your cloud costs in a dashboard. It provides AWS users with cloud cost information like overall costs, costs per service, and region. However, it doesn’t illustrate the costs of the underutilized and unused resources.

Potential savings are displayed via the recommendations for AWS RI and Savings Plans purchase – users can realize the volume of profit by looking at the percentage savings from implementing an RI purchase or committing via a Savings Plans.

On the other hand, AWS Cost Explorer allows its users to set budgets, as well as see the forecasted spending but keep in mind that this tool is only for AWS services and costs.

Azure Billing

Azure Billing presents cloud costs in a dashboard as AWS does. It also offers some intelligence into AWS cost via Cloudyn.

Azure Billing tool provides its users with recommendations for how they can save money based on their cloud assets usage. Also, with this solution, users can set the budgeting alerts and receive cost reports. What’s worth mentioning, the Azure Billing tool requires a good tagging strategy implementation in order to reach the granular cost visibility.

The difficulty of using the Azure solution lies in the impossibility to view idle resources costs, but the main hitch here is that it’s primarily for Azure services, though you may be able to see AWS services and costs, too.

GCP Billing

GCP Billing helps users to understand their cloud costs due to the spending analysis, regular reporting, and recommendations on how to prevent overspending.

This solution presents a good mix of basic features ideal for companies with simple cost structures. Additionally, GCP Billing has an API that allows users to access data via their analytics tool of choice.

The main inconvenience here lies in the difficulty to use the provided features due to the opposite needs of finance and engineering teams.

This tool can be used only for GCP services and their costs.

Improve Cloud Cost Intelligence with Binadox

Cloud management platform Binadox helps organizations that deploy multi-cloud or hybrid cloud architectures manage their cloud expenses in a structured way. Besides, Binadox simplifies achieving cloud cost transparency, implementing cost optimization strategies, and predicting future costs.

Try Binadox using a free 14-day trial period or book a demo to learn more about its features.

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7 SaaS Industry Trends for 2022

7 SaaS Industry Trends for 2022

~5 minutes read

The Software-as-a-Service (SaaS) model skyrocketed in popularity during the last few years, as it offered innovative solutions for a wide range of industries. Analysts claim that the SaaS market will grow at 12% each year, and by 2022, the volume of investments will reach approximately $141 billion. Therefore, as companies continue implementing SaaS into their operations and product distribution, it is better to be aware of and follow the latest trends in the SaaS industry.

In this article, we’ll take a closer look at the 7 SaaS trends for the year 2022 and will discover what the future holds for this type of service model.

Trend 1: Vertical SaaS

To start with, the main difference between horizontal and vertical SaaS lies in their focus: horizontal SaaS provides solutions to a great number of businesses, while vertical SaaS offers services that aim to attract a narrower audience, typically within a single niche.

Considering the benefits of vertical SaaS, it’s no wonder that the number of such products is rising. First of all, this type of SaaS model gives companies the opportunity to acquire the target audience using unique features created for a definite market segment. Secondly, the vertical SaaS provides solutions to the exact problems of a specific industry, without trying to solve the issues of numerous industries all at once. Additionally, vertical SaaS supports extensive customization, can quickly adapt to trends and serve the changing needs of the industry.

Trend 2: Micro SaaS

One of the possible ways to adapt to the competitive SaaS environment is to create a small and flexible tool that is planned to be run by a tiny team or even by a single person.

Micro-SaaS products often serve as an addition to the larger SaaS platforms. You can view similar products almost everywhere: on retail platforms (for example, Amazon Assistant for product comparison), SEO services (for instance, Yoast SEO plugins for WordPress). Some Micro-SaaS products like Grammarly are presented as browser extensions.

Micro-SaaS products creation and development typically require low costs and no outside funding. That is why a lot of start-ups develop exactly Micro-SaaS products. Besides, micro SaaS can operate remotely from almost any location and still generate high margins. All these benefits, combined with low overheads, have stimulated the massive interest in MicroSaaS solutions.

Trend 3: Artificial Intelligence (AI)

Artificial intelligence (AI) is considered to be one of the most remarkable game-changer technologies and SaaS trends for 2022. According to a Gartner survey, the expected increase of cloud AI in 2023 will be five times higher than in 2019. Companies like Salesforce and IBM have already set the AI-optimized SaaS solutions trend.

Artificial intelligence technology is widely used as it:

creates highly personalized apps and customizes them according to the users’ convenience and behavior;
provides an improved security system so that you can easily detect and prevent data leaks, cyberattacks, and other threats;
automates various processes that used to be performed manually;
enables companies to improve the decision-making processes, optimizes the length of research and development cycles, and creates sophisticated management strategies;
can predict which products will hit the market soon and become popular among different audiences.

Some of the brilliant examples of SaaS products using AI are Remove.bg, which automatically removes the background from images, as well as Flowrite, which creates copy for emails and collaboration tool messages.

Trend 4: Machine Learning (ML)

Machine Learning (ML) and AI are often considered to be synonyms but in fact, they are not all the same. To be more specific, machine learning is a subset of artificial intelligence that focuses on learning capabilities and data processing.

Machine learning technology allows for identifying patterns in customers’ preferences and habits. Using this information businesses can make calculated moves for improving products’ usability which brings higher engagement and retention rates.

MI also helps companies stay at the top of the competition by telling businesses how their offerings and market positioning should be optimized based on large amounts of contextual data processed.

There are numerous excellent examples of MI-based SaaS platforms. For instance, Zendesk is a sophisticated CRM system that helps sales teams to identify trends in clients’ behavior. Spotify also uses machine learning to create its personalized song suggestions.

Trend 5: Mobile-first approach

According to CNBC, 72.6% of people will use smartphones for communication, work, and surfing on the Internet by the end of the year 2022. Also, according to another study by eMarketer, the average person spends over 120 hours per month staring at their smartphones.

Many entrepreneurs run their businesses from their smartphones, not even mentioning that a huge number of employees use mobile phones to have their job done – it’s easier and faster that way. SaaS vendors took this paradigm shift into consideration and continue creating and improving mobile apps for their tools and services in the first place.

There also comes a wide array of challenges, especially from the design perspective – companies should decide how to create interfaces that will satisfy users’ needs, as well as facilitate app usage for people suffering from sight and hearing impairment.

Trend 6: Low–code

Low-code is a technology of developing an application with minimal coding. Many businesses are considering this approach, and the SaaS industry isn’t an exception. According to a Research and Markets report, the low-code industry could be worth $190 billion by 2030.

Low-code or even no-code platforms’ benefits include:

Increased accessibility to the average user

Those kinds of platforms allow non-tech startups to enter the market and diversify it.

Less time and money spent on development

Saved on development resources can be used on addressing the industry’s most concerning issues.

Some of the famous low-code app examples include Webflow and Typeform. Even if they’re not enough to create an entire application, you can use a low-code platform to build a lot of the key features that you want in your software product, and then manually code the rest.

Trend 7: Customer retention

Semruch study has shown that 44% of businesses focus on customer acquisition while only 18% focus on customer retention. However, just a 5% increase in customer retention can double organizational revenue. So, nowadays SaaS companies try to follow one of the SaaS trends for 2022 – pay closer attention to customer retention and churn reduction.

Companies can use the following practices to improve customer retention and reduce churn rate:

User onboarding emails;
24/7 support;
Video instructions and tutorials;
New feature notifications;
Improving the overall customer experience.

A greater focus on retention and churn goes beyond the basics of developing a product, it’s more about improving the life quality of your customers. If you’ll be able to accomplish this task and make a significant difference in your customers’ lives, the churn level will go down, and you can continue running, improving, and growing your company.

To sum up

The main reason for the growth of SaaS applications usage was the pandemic that facilitated remote work. However, it’s obvious that SaaS will continue to evolve even after workers return to the offices. Experts believe that 75% of companies will use all or almost all applications only in the form of SaaS by 2022, as business executives enjoy the benefits cloud applications are capable of offering for a fair price.

To continue getting the most out of your SaaS portfolio try out the Binadox platform. It provides both management and cost optimization features. SaaS Utilization Dashboard allows businesses to identify their tool consumption patterns and make more accurate decisions concerning future licenses purchase.

SaaS utilization dashboard, SaaS connections, invoices

Additionally, Binadox can help your organization avoid unnecessary SaaS expenditures by reminding you about your next renewal and sending you cost-saving recommendations.

It’s time to take control of your SaaS environment. Sign up for a 14-day free trial and make innovation, intelligence, and growth your priorities in 2022.

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AWS Storage Services: S3, EBS, EFS

AWS Storage Services: S3, EBS, EFS

~5 minutes read

Many companies face difficulty to choose the right storage services that would match their goals as the cloud market offers numerous solutions for any business needs. In this article, we’d like to focus on S3, EBS, and EFS, as they belong to the persistent data storage type, which means that data there is durable and sticks around after reboots, restarts, or power cycles.

AWS File, Block and Object Storage Services

Additionally, according to AllCode, an Amazon Web Services Consulting Partner, Amazon Elastic File System (EFS), Amazon Elastic Block Store (EBS), and Amazon Simple Storage Service (S3) are included in the list of the most popular AWS services.

So, let’s consider the advantageous features of all three storage services, as well as discover their use cases to know which solution can be helpful for your organization in particular.

Amazon S3

AWS Simple Storage Service (S3) is the most popular object storage among many organizations. Below you can discover the reasons for such popularity.

S3 benefits

Durability, scalability, and availability. Amazon S3 offers scaling of the storage resources for free. It protects your data from various threats, errors, and downtimes. This, in turn, makes your data accessible anytime you need it.
High level of data protection. S3 follows the security and compliance standards. It means you can store data and consider it protected from unauthorized access due to proper encryption and access management tools. S3 is the only object storage service that has a Block Public Access feature that gives you the opportunity to block public access to all of your objects at the bucket. Additionally, AWS supports various auditing capabilities that allow you to monitor access requests to S3 resources.
Cost-saving opportunities. There are several factors that influence S3 cost like the region where you store your data, the volume of stored data, the chosen S3 storage class, and so on. If you’re aware of them, you can optimize your S3 expenditures.

S3 use cases

Backup and restoration. S3 can be combined with the other types of AWS storage like EBS and EFS to achieve secure backups and restoration. These offerings can help you meet compliance, recovery time, and recovery point objectives.
Trustworthy disaster recovery. S3 storage provides the replication of sensitive data and mission-critical applications. It offers protection of resources by means of recovering data from different issues caused by a system failure or a natural disaster.
Possibility to archive data. S3 offers archiving capabilities such as S3 Glacier and S3 Glacier Deep Archive. These services give users the opportunity to archive the less used data and store it for extended periods of time at their lowest rates. The main advantage is that S3 Glacier allows restoring any archived object within several minutes.

Amazon Elastic Block Store (Amazon EBS)

Amazon EBS provides block storage volumes for use with EC2 instances. EBS volumes are attached to EC2s in the same way as the local disk drive is attached to the physical machine.

EBS benefits

High availability and security. EBS volumes offer automatic replication within the Availability Zones these volumes are located. Security is provided by access control and encryption policies.
Data backup and restoration. You can protect your data by backing up the EBS volumes to Amazon S3 with the help of taking real-time snapshots. They are incremental backups but cannot serve as a replacement for backup software. Here’s why: only the blocks on the device that have changed after your last snapshot are saved in the new snapshot. This minimizes the snapshots creation time and saves money by not duplicating data.
Geographic diversity. EBS volume snapshots can be duplicated and resources can be placed in different locations to facilitate disaster recovery and data center migration. It’s useful in the case when the company’s client base is spread all around the world.
Facilitated scalability. EBS volumes are scalable, so you can easily scale them both up and down. As it happens at a high speed, you get the required performance and needed capacity for changing computing needs.
Potential cost savings. EBS requires upfront disk pre-allocation, so if you’ve performed a sophisticated pre-analysis and identified how much space you need to reach your goals, you can save a lot of money. This analytical work needs to be done, as EBS costs about a third as much as EFS per GB.

EBS use cases

Testing and development. EBS perfectly suits development and testing aims, as this type of storage gives the opportunity to quickly and easily scale, duplicate, and archive the required environments.
Relational databases. As EBS scales to meet changing storage needs, it’s a great choice for deploying relational databases, including PostgreSQL, MySQL, Oracle, or Microsoft SQL Server. Depending on the amount of storage requested, Amazon RDS automatically stripes across multiple Amazon EBS volumes to enhance performance.
International market. You can copy EBS Snapshots and AMIs to run apps in various AWS regions. Not only does it minimize the data loss, but it also increases the speed of recovery time due to regular data backups.
Enterprise-wide applications. EBS is the powerful block storage that is enough to support essential applications (for instance, Microsoft SharePoint or Microsoft Exchange).

Amazon Elastic File System (Amazon EFS)

EFS is considered to be the best solution for the constantly fluctuating workloads, as it can scale automatically to meet the demand, no matter how rapidly it increases. What’s more important, EFS will automatically scale back down, when the demand spike decreases.

You can integrate EFS with different AWS services and access this type of AWS storage from all your instances. Let’s explore its advantages in detail.

EFS benefits

Scalable performance. EFS can support any workload, no matter how rapidly your file system grows. It’s all due to automatical up and downscaling capability. Additionally, with EFS you don’t need to provision the storage preliminarily before adding any files.
Constant accessibility. EFS ensures the possibility for EC2 instances and on-premises software to access the shared files anytime. Also, EC2 instances can access EFS file systems located in other AWS regions with the help of Amazon Virtual Private Cloud (VPC) peering.
Service management. EFS is a complete managed service. This means that the company’s executives or even IT department teams don’t need to maintain the file system themselves, which saves time and frees employees to perform other tasks.
Cost savings. EFS the most outstanding advantage is that you pay only for the storage you’re actually using. However, its cost is significant, especially when compared with the EBS cost.
Reliable security and compliance. You can control access to your EFS file systems with the use of AWS Identity and Access Management (IAM) or Amazon VPC permissions. EFS encrypts the data, even the one that is in transit, that provides trustworthy security and facilitates regulatory compliance.

EFS use cases

Big data analytics. EFS is suitable for running applications with big data, that require low-latency file access, as well as demands significant throughput.
Content management system and web server support. EFS is a solid file system that enables content management systems and supports web serving applications, such as websites and archives.
Development of apps and testing. EFS is the only type of storage that delivers a shared file system that is necessary for sharing code and files across numerous computing resources.

AWS Storage Services S3, EBS, EFS overview

Manage your storage

When deciding what type of Amazon storage to use (EBS, EFS, or S3), it’s better to consider all the details: advantages, the situation when you may need particular storage, as well as possible issues that may occur, like overspending or various security threats. Also, you may use all the above-mentioned storage types in order to meet all your business needs, instead of choosing one and only.

No matter what type of storage you’re deploying, keep in mind that cloud resources and costs should be properly managed. With Binadox you can view the utilization and cost rates for all S3, EFS, and EBS. Based on these rates the system forms recommendations that you can consider for optimizing AWS storage services.

Binadox Tools for Cloud Cost Optimization

To find out more about Binadox cost-saving practices sign up for a free 14-day trial period.

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AWS Data Transfer Pricing

AWS Data Transfer Pricing

~5 minutes read

The cost that the Data Transfer process generates might be confusing to understand as rates vary depending on multiple factors. So in this article, we look closer at AWS Data transfer costs and present cost-saving practices for moving your data in a more convenient and profitable way. But first of all, let’s understand why do you need to transfer your data at all.

Why transfer data?

If data transfer costs are higher than the cost of hosting your applications in the same regions and Availability Zones, what is the reason so many companies choose this geographic diversification?

Imagine, your application that is used worldwide started to be more popular in Asia, for example. In order to keep this growth going up and ensure the best user experience, it’s more reasonable to host your application closer to the user base, for instance, in the AWS Beijing Region (cn-north-1). This practice helps companies to avoid the latency occurring due to the data traveling between Asia and the US.

It would make sense to host an instance of your application in a different AWS region in order to lower the round-trip latency from different parts of the world. — Data Transfer

One more reason to use a specific region may be the cases when you want to conquer an outside market, for instance, a European one. Organizations there have to store their sensitive data in local data centers, according to the law. In this case, you need to comply with the local regulations, so hosting an instance of your service in the region located in Europe, for instance, Frankfurt (eu-central-1) is a possible way out.

Having several instances located around the world is also beneficial in the case of natural disasters, armed conflicts, or sanctions.

AWS Data Transfers pricing explained

AWS Data Transfer is a practice of moving the data from AWS to the Internet or shifting it from one AWS instance to another across the Regions or Availability Zones where the data is stored. Inbound transfers are free while the inter-Region and inter-Availablity Zone data transfers include additional costs (users are charged per GB).

Data transfer cost depends on how exactly data is transferred:

Into or out of AWS regions;
Into or out of AWS edge locations;
Within an AWS region.

AWS Data Transfers (Source: Amazon Web Services, aws.amazon.com)

Data transferred in and out of an AWS region

In this paragraph, we compiled the information concerning the inter-regional transfer costs for commonly used AWS services.

Pricing of transferred AWS Direct Connect data

AWS Direct Connect gives companies the opportunity to provide a private dedicated network connection to the deployed AWS services. That way your network traffic remains on the AWS global network during the transit and doesn’t interfere with the public internet. It reduces the chance of unexpected latency.

Below you can see a table representing Direct Connect pricing from regions within the United States to its other regions or outside.

Pricing of transferred EC2 data

To start with, AWS EC2s provide users with a resizable computing capacity in the cloud. Talking about the EC2s data transfers, they aren’t free and the cost of transferring the data doesn’t depend on the type of the EC2 instance deployed (Spot, On-Demand, or Reserved ones). It depends mostly on the volume of data transferred and the region where the data is directed to.

Data Transfer from EC2 to the internet (within the US)

Data Transfer from EC2 to the internet (within the US)

Data Transfer from EC2 to other regions

Pricing of transferred ElastiCache data

AWS ElastiCache accelerates apps’ performance and builds low-latency data stores (cache) that enable to retrieve the information faster. ElastiCache data transfer (in or out of an Amazon ElastiCache itself) is free; the traffic in or out of a given EC2 instance associated with the ElastiCache node is paid ($0.01 per GB).

Pricing of transferred RDS data

AWS RDS can speed up the setup and operation of cloud relationship databases. RDS data transfer pricing depends on the database deployed. There are six database engines to choose from, and you can follow the pricing pages for more detail:

Notice that transfers into Amazon RDS are free up to 1GB per month (if above, it becomes paid), while outbound transfers to Amazon Cloudfront aren’t charged at all.

Data Transfer into RDS

Data Transfer out of RDS

Pricing of transferred Redshift data

Amazon Redshift is used to analyze exabytes of data and run complex analytical queries, which makes this AWS service one of the most popular cloud data warehouses. With Redshift, the process of running and scaling analytics on all the data takes minutes or even seconds. Also, users don’t have to manage their data warehouse infrastructure.

Generally, the usage of Redshift implies that you pay according to the standard data transfer rates. Data transfer to or from an S3 resource if performed within the same AWS region is the only exception here.

Data transferred within an AWS region

Data transfers in or out of services like EC2, RDS, ElastiCache, and Redshift within a specific AWS region usually cost $0.01 per GB. However, data transfers within the same AZ are free of charge (VPC Peering Connections is an exception in this case).

Data Transfers within an AWS region are charged per GB

Free Data Transfers within an AWS region

Data Transfer in and out of an AWS Edge Location

CloudFront Content Delivery Network (CDN) service includes the AWS Edge Locations that are typically used to provide a faster and more reliable delivery of content, API actions, and other data.

Data transfer into AWS edge locations from the Internet is free, while data transfer out of AWS edge locations to the Internet is billed at region-specific rates.

Data transfer into AWS edge locations from AWS regions is also free. Data transfer out of AWS edge locations to origin in AWS regions is billed at region-specific data transfer rates.

Additionally, after the first 150TB of data transfers for services in the US, the cost drops by $0.02 per GB, when compared with the standard data transfer rates and it goes down to $0.04 per GB.

Note: as illustrated in the table below, higher discounts can be achieved if you commit to a larger worth of data (10TB+). In this case, you can contact AWS and sign a private pricing agreement.

3 simple steps to reduce AWS Data Transfer costs

Previously we’ve explained the reasons why it’s worth taking into account the multi-regional infrastructure, as well as investigated pricing rates for transferring the data across the most widely-used Amazon services. The last question is how to reduce data transfer costs and cut down AWS bills.

Step 1: Examine current Data Transfer costs

To act wisely in the future, analyze all your existing resources, discover your historical cost patterns, and have the whole picture of your current spending trends.

A detailed view of Data Transfer expenditures can be achieved by filtering cost data in the AWS console. Here is a step-by-step instruction to follow:

Open the AWS Console.
Proceed to the AWS Cost Explorer.
Filter the data by the “EC2 Other” service.
After that, group by “Usage Type”.

Examine current Data Transfer costs (Source: Amazon Web Services, aws.amazon.com)

You can recognize the data transfer line by the “USW2-DataTransfer-Regional-Bytes” code.

To improve the grouping of your spending, assign Cost Allocation Tags to your ELBs and EC2 instances. Once you apply these tags, you can identify transfers driving maximum cost and filter them by regions, availability zones, navigation (in or out), CloudFront, etc. It’s a good practice to focus on the cost trends to observe how transfer expenses are changing in time and understand the cost pattern.

Besides, estimate the hypothetical data transfers between the different regions with the help of the AWS Calculator.

Step 2: Architect your environment to optimize Data Transfers

Consider the following strategies to save budget and optimize your AWS expenditures.

Reduce the number of outbound data transfers

The easiest way to cut down AWS data transfer costs is to minimize sending outbound data. The example below illustrates the cost of inbound data transfers for the US West (Oregon) region, which is absolutely free. In comparison, outbound data transfers are charged and their cost fluctuates depending on the volume of data transferred.

Data Transfer Pricing for US West (Oregon) (Source: Amazon Web Services, aws.amazon.com)

There can be cases when it’s impossible to limit the outbound data transfers. For instance, when you’re delivering some media content to your customers over the internet. Transferring more data than you need to decrease the price per GB can affect your total AWS spend.

Keep your data within the same Availability Zone

AWS services users may launch their instances in different AZs without even realizing it. This results in additional costs, as the data transfer between several Availability Zones isn’t free. We recommend launching AWS services within the same AZs. The exception can be made in case your company intentionally stores data in different Availability Zones to ensure disaster recovery.

Keep your data within the same region

Keeping data in two separate AZs may be beneficial if one AZ goes offline. Then another separate building with its own network and power can save a business from possible downtimes. However, in the case of a natural disaster like an earthquake or tsunami, the data stored in different Availability Zones but in the same region can be gone for good.

Use a less expensive region

If there is a need to use the regions outside the United States, examine the rates of each region. The table below presents the data transfer pricing rates by the regions, so you can choose the most profitable one.

AWS Data Transfer Pricing by several regions

Step 3: Consider a third-party tool to manage AWS Data Transfer costs

Сloud cost optimization tools can help you cut down overall cloud spending. Also, you can reduce data transfer costs particularly, as third-party tools like Binadox provide features that make it possible.

One of them – Automation rules that simplify cost management processes by replacing 24/7 manual checks with customized rule-based algorithms. All you need to do it to create a set of conditions with associated values to trigger automated checks of all your resources. Once resources that are matching the parameters are identified, the system sends you a notification. Then you can take the required actions to save money.

Want to optimize your cloud cost, automate your cloud and increase profitability?

Sign up for a free Binadox trial or book a demo.

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