DevOps As A Service AWS

The combination of the latest and advanced tools, practices, and techniques to optimize and enhance the productivity of an organization is called DevOps. It helps an organization to serve its customers efficiently. Organizations working in infrastructure management and software development environments can optimize and speed up the processes.

Why AWS for DevOps?

According to cloud DevOps consulting, DevOps as a service AWS is the best solution because of specific reasons such as:

Fully-Managed Services:

DevOps Services and Solutions are fully managed. Your organization and staff must not worry about installing and deploying infrastructure and applications. It helps your team to concentrate and focus on the core task.


Each of the resources and services can be used with the help of the AWS Command Line Interface. Your organization can model and design the customized resources and infrastructure as required.

Quick Start:

If you have an AWS account, these services are ready to start. There’s no need and time consumption for installation or deployment. None of the setups is required to start it.

Secure and Protected:

It has a well-developed Identity and Access Management system, making its services the most secure and protected. Through authentication algorithms, you can monitor and regulate access to resources and limit or restrict sensitive and confidential areas.


It enhances the process and management via automation. You can automate manual tasks such as test workflows, develop workflows, configuration management, deployments, installations, and container management.

Built for Scale:

These services are scalable and flexible; an individual or a full-fledge enterprise can manage these services. These services can help you configure, simplify, and scale compute resources.

Large Partner Ecosystem:

It supports the integration of third-party tools. Your organization might integrate the open-source tools from any other source with AWS tools to form an end-to-end solution. In that way productivity of the solution can be increased.

The following are some of the other main perks of AWS pricing services:

  • No termination fines and penalties
  • Long term contracts
  • Upfront fees
  • Customized purchase period
  • You can terminate the subscription at any time

What are the Benefits of DevOps?

DevOps as a service AWS is the most efficient and reliable DevOps. It can offer your organization the following benefits:

  1. Immediate delivery and responses to the customer response
  2. Rapid speed of the process
  3. Reliability is ensured by the best practices
  4. Interoperable technology
  5. Quick adopt and deploy, leading to time and cost-saving
  6. Scalability and flexibility are the key benefit
  7. Security and protection from risks and vulnerabilities by the incident response and management
  8. Supports collaboration of third-party
  9. Open source tools can be integrated with AWS tools

What are the Core Practices of DevOps?

The following are the core practices of DevOps as a service:

  1. Continuous Testing:

It ensures the continuous assessment of the changes in the development process. Testing techniques and strategies give quick feedback to developers, ensure quality, and reduce bottlenecks in the whole delivery development process.

  1. DevSecOps:

Application security is the most crucial point for the security of your management and monitoring processes. It can save your effort, cost, and time in determining and screening the security flaws and vulnerabilities, leading to a secure and protected environment and workspace.

  1. Code Repos and Artifact:

Artifact management solutions and Code repositories based on Git are the critical components of all DevOps practices. They can help in the following ways:

  • Optimize the management process
  • Supports the use of multiple applications
  • Independent delivery and offering of values and services to the customer
  • Helps the team maintain autonomy
  1. Incident Management:

It provides the best incident practices by ensuring the following offerings:

  • Effective incident response and management
  • Implements continuous monitoring and regulating solutions
  • Excellence and performance efficiency of the application
  • Automated issue tracking and tracking
  • Process, delivery, and application management
  • Routing of the responses to the inquiries and queries
  1. Infrastructure as a Code:

Infrastructure as a code helps in the below-mentioned ways:

  • Eliminates the time taking and consuming rollbacks
  • Supports configuration, programmatical build, and destruction of the workspace
  • Enables self-service
  • Reduce the chances of errors and risks
  • Automates the maintenance processes
  1. Observability and Monitoring:

Continuous delivery and continuous delivery pipeline influence and supports insights such as:

  • Data-driven insights
  • DevSecOps lifecycle
  • Implements automation
  • Reliability, health, and performance of the application
  • Automation and virtuous cycles
  • Scalability of the infrastructure in IT operations

What is the Architecture of AWS DevOps?

The architecture of AWS DevOps consists of the mentioned components:

  1. Load balancing
  2. Amazon CloudFront
  3. Amazon Security Group
  4. Amazon Relational Database Services (ARDS)
  5. Elastic caches
  6. Amazon’s simple storage service (S3)
  7. Amazon Auto-Scaling
  8. Amazon Elastic Book Store (EBS)

What are the AWS DevOps Services?

AWS provides the following DevOps services and solutions:

  1. DevOps on AWS cloud
  2. AWS managed services
  3. AWS migration services
  4. AWS assessment services

Bottom line

As a service by AWS, DevOps offers the best cloud services and solutions for your organization with tools ranging from application development to management.


How AI can Improve Cloud Computing?

The cloud is the natural environment for artificial intelligence. The AI cloud, a concept that combines artificial intelligence (AI) with cloud computing, is just now being used by businesses. There are two reasons for this: Cloud computing is no longer only a cost-effective solution for data storage and processing but a critical component in the adoption of AI.

Using AI to aid in the automation of routine IT infrastructure improves efficiency. The combination of cloud computing with artificial intelligence (AI) provides a massive network capable of storing enormous data while also learning and improving over time now; let us explain how AI can improve cloud computing.

How AI can Improve Cloud Computing?

The AI cloud’s ability to address problems is the most compelling advantage. In this way, artificial intelligence (AI) becomes more accessible to a broader range of people. Because AI-enabled transformation decreases adoption costs and makes it simpler to collaborate and generate new ideas, enterprises benefit from AI-enabled transformation.

Using AI to give strategic inputs for decision-making is made possible by the cloud’s agility, adaptability, and scale. The cloud substantially enhances AI’s reach and impact, first with the user organization and then moving to the larger market. AI and the cloud are mutually reinforcing, enabling AI to blossom on the cloud to its full potential.

AI Cloud Solutions

Companies may become more efficient, strategic, and insight-driven using cloud computing enabled by artificial intelligence. In order to boost productivity, artificial intelligence (AI) can do complex and repetitive tasks and analyze data without human intervention.

An AI system may analyze data sets of any size for patterns and trends. Because it contrasts old and new data, data-driven insight is valuable to IT workers. As a result, companies can answer customers’ queries and concerns more swiftly and effectively, thanks to AI technology. Artificial Intelligence (AI) may provide insights and suggestions that lead to improved results may be provided through Artificial Intelligence (AI). With Amazon Personalize, you can provide your customers with in-app recommendations that are updated in real-time. EES cloud computing consulting services can help you modernize your infrastructure.

Benefits of using AI Cloud Solutions


  • To design AI solutions, cloud computing makes it simpler. You may be able to receive better results for less money.
  • Google, Amazon Web Services (AWS), or Microsoft Azure may all be used to store your data in the cloud. We can develop solutions that minimize the danger of lock-in to protect your investment.
  • Develop an end-to-end Cloud solution or integrate AI, machine learning, or forecasting into an existing application.
  • Familiar with Google Cloud AI Platform, Sagemaker, AWS Azure Machine Learning, and Cloud Python and R data science deployments.
  • Knowledgeable
  • Maintenance training will be required when the project is completed.

Cloud AI Services Consulting

Companies are working hard to ensure that cloud computing services are consistently enhanced, although general and not tailored to specific requirements. Cognitive computing may teach a computer to provide certain services depending on the information it gets from its consumers. Finding the best algorithm or training model is no longer necessary.

Expertise from cloud computing consultants can help businesses take advantage of the most recent and finest cloud data centers, clouds, and data warehouses. Consultants aid in selecting and implementing best practices for your company’s use cases in the cloud. If your firm is contemplating migrating to the cloud or implementing new technologies, hiring the services of a cloud computing specialist might be a good decision.

Cloud consulting services are provided by several prominent firms, including Deloitte, Accenture, AWS, Capgemini, IBM, Cognizant, too many of the Fortune 100 global enterprises. These cloud consultants’ clients have very particular and comprehensive requirements from all across the globe. A cloud AI services consulting firm with an excellent reputation and considerable industry experience may be the ideal choice for medium- and small-sized businesses., for example, is a fantastic choice. We provide a wide range of cloud services for several platforms.

Final Verdict

It is becoming more critical for organizations to secure their data in the cloud as more and more cloud-based services are used. Using AI-powered tools, IT departments can monitor and analyze traffic on their networks. A flag may be raised when an AI-powered system notices anything out of the ordinary. This proactive approach assures the safety of confidential information. An example of this is Amazon GuardDuty, which uses AI and machine learning to detect potential risks.

AI cloud solution has made data processing, administration, and organization simpler. AI’s marketing, customer service, and supply chain data management may benefit substantially from more reliable real-time data describing how AI can improve cloud computing. Data can be consumed, updated, and managed more efficiently using artificial intelligence (AI) tools. Use Google Cloud Stream analytics for real-time personalization and anomaly detection to help IT organizations better plan maintenance scenarios.


How is Machine Learning used in E-Commerce?

E-commerce organizations can use machine learning to provide a more personalized client experience. Customers today not only want to engage with their favourite businesses on a personal level; instead, they have evolved to demand it. In fact, according to research, 73 per cent of customers are tired of being bombarded with useless content.

Retailers may use artificial intelligence and machine learning to tailor each connection with their customers, giving them a better experience. They can use machine learning consulting to prevent customer service problems in advance.

Cart turnover rates should decrease as a result, and sales should increase. Customer support bots, unlike humans, can deliver unbiased responses 24 hours a day, seven days a week.

How is Machine Learning used in E-commerce?


The recommendation engine is the most extensively utilized role of AI in e-commerce. A good product recommendation algorithm can significantly increase your income and average order value.

A recommendation method is a sophisticated data filtering tool that uses machine learning algorithms to suggest the most appropriate product to a buyer.

The algorithms use information such as the customer’s most recent purchase, purchasing history, preferred colors, typical budgets, etc.

Pricing Optimization

Using machine learning consulting, retailers can calibrate prices driven by supply and demand, minimum price, operational expenses, competitiveness, and other factors.

Manually completing all of this isn’t easy. AI automates massive volumes of data collecting, processing, and analysis to provide better real-time dynamic pricing. This also aids organizations in recognizing early trends and forecasting demand for products for which transaction data is not available.

Fraud Protection

Chargebacks are the biggest nightmare of any online retailer. Most shoppers, especially first-time customers, believe that e-stores are untrustworthy. E-commerce stores are vulnerable to fraudulent activity. E-commerce business owners must exercise extraordinary prudence. It is not uncommon for businesses, especially internet businesses, to shut their gates due to a bad image. As a result, companies must not cut corners when detecting and combating fraud.

Machine learning can substantially limit the scope of fraudulent behavior. It can quickly evaluate large amounts of time-consuming, recurring data and detect illegal transactions earlier on by proactively detecting any abnormalities.

Image Processing

Retailers engage in artificial intelligence (AI) and image recognition technologies to influence consumer (buyer) behavior and automate processes. Investing in information visualization with visual search capabilities could help you match images of consumers with similar clothing sold online, for example. This could be determined by a user’s request based on the type of things they typically purchase (color, brand) and data from media platforms.

Another e-commerce machine learning application is its help in automatically filling in the subject information based on the photo.

Retargeting, Upselling, and Discounts

Not every person who visits your website will make a purchase. Some may seek product information, while others may put something in their cart and then abandon it. Using dynamic retargeting, upselling, and discounts, machine learning consulting can assist get more individuals to finish their transactions.

Machine learning allows e-commerce stores to better retarget consumers by analyzing data to see what has worked in the past to acquire similar profiles via retargeting. ML analyses millions of profiles, analyzing their behavior and outcomes to anticipate what will most likely convert a consumer.

Trend Analysis

Before you put things available for auction on an e-site, you should research their popularity: is it a best-seller, a regular seller, or out of date?

Whether from an outsourcing provider or internal fulfillment, procurement is influenced by trend analysis. If statistics are not carefully monitored, returned items will play a significant role in procurement. As a result, analyzing a product’s trend is crucial, as it can help lower the catalog’s total size, product maintenance costs, and warehouse space utilization.

This is made simple with machine learning because it analyses and compares product evaluations, ratings, and media platform inputs. Low-rated products may be removed from the site’s inventory.

Better Inventory Management

Inventory management is one of the most persistent issues in e-commerce. Manual stock control can be time-consuming (particularly for e-commerce stores) and can hurt accurate sales forecasting, leading to financial flow issues. ML can significantly improve the accuracy of future demand predictions. It will make supply chain management more accessible, but it will also ensure that you better understand your clients and their behaviors.

Stock replenishment is required to avoid stockouts and guarantee that client requests are met promptly. Inventory replenishment can be automated using Artificial Intelligence algorithms based on previous and current sales information. This can be set up for “Pick up from store” and “Deliver to customer” scenarios.

Final Verdict

Machine learning is here to stay in e-commerce. It has various practical applications in eCommerce, as we’ve seen. How machine learning is used in e-commerce may interest you if you wish to improve your e-commerce operations.

Machine learning is being embraced by many e-commerce companies, which are reaping significant benefits from it. ML may be a substantial advantage for firms that automate time-consuming, labor-intensive, and costly manual procedures. It can provide internet retailers with helpful information on their customers. They can assist internet businesses in increasing clicks, converting prospects into customers, keeping them, and even developing strong customer relationships.



How to Use AI and Machine Learning for Cyber Security?

You’re probably familiar with the term “machine learning.” You might have heard of “artificial intelligence,” too. But do you know the difference between AI and machine learning? And how does machine learning consulting work?

We’ve got answers.

What is Machine Learning?

Machine learning is a study that comes after artificial intelligence that allows machines to learn from data without a human. This is possible through statistical modelling and machine learning algorithms, which are used to identify sketches in data and make assumptions based on what they find. Models are then trained, validated, and tested before they can be deployed to the real world.

That’s essentially what machine learning consulting is all about: building models that give you insights into your data so you can take action based on what you find.

How to Use AI & Machine Learning for Cybersecurity?

In cybersecurity, machine learning is primarily used to protect networks.

It could be protecting a company’s network or even a national grid from cyberattacks or natural disasters. The goal of these types of applications is to protect valuable information like patient records or confidential military secrets from falling into the wrong hands. To accomplish this, companies use Machine Learning Consulting services.

Here’s the good news for AI and machine learning consulting: Machine learning is a very powerful tool for cyber security. The bad news? It can be confusing.

What Exactly makes AI and Machine Learning so Valuable for Cyber Security

Machine learning is an essential part of any robust system that wants to protect itself against unwanted intrusions. In short, it helps your system learn to recognize patterns that might indicate an intrusion. This means that your system will become more adept at detecting threats over time and tailor its responses to new types of threats as they emerge.

Machine learning works by “training” the system to recognize patterns and then using those patterns to make predictions. This type of program has two primary parts: one, which we’ll call the “model,” is responsible for making predictions, while another, which we’ll call the “code,” uses these predictions to update the model as new data becomes available.

When you use a machine-learning algorithm, it’s important to remember that it’s not just a set of instructions—it’s also an evolving process. The code needs to adapt over time in order to stay effective against new threats. As hackers get smarter and more aggressive, you need to stay one step ahead. And that’s why we’re here to help.

We’ll teach you how to use AI and machine learning in cyber security to identify threats before they happen and take action when they do to your business. Our team of experts will guide you through the world of AI and machine learning, look at your current systems, and work with you to design a solution that works for your business. As your consultants, we’ll make sure you have the knowledge and tools you need to protect your business from cyberattacks—now and in the future.

Here are some Factors that AI and Machine Learning can be used for Cyber Security


Artificial Intelligence (AI) and Machine Learning (ML) have been in the news for quite some time and have generated a lot of buzz. Companies are using these technologies from various industries to solve different problems. Machine learning uses AI to identify patterns in massive data sets and utilize those patterns to make predictions about new data.

In today’s digital landscape, new threats are popping up every day. Fortunately, we’ve got an arsenal of tools that can help us guard against these threats and protect both our data and our people.

Artificial intelligence (AI) and machine learning have gained traction recently as some of the most useful weapons in the fight against cyber security threats. When used correctly, they allow us to identify malicious files before they attack our systems, recognize patterns that indicate potential future problems, and even take automatic action to defend against attacks.

In cyber security, machine learning is used to detect threats, prevent attacks, and respond to breaches by using algorithms that can process huge amounts of data in real time.

Get The Right Help With EES

A machine learning consulting firm like EES can help you figure out how best to implement this technology in your business and how to develop the resources needed for a successful implementation. The difference between AI and ML is like a robot and a computer. While they both rely on each other, they are separate entities.

Robots rely on AI to function, and computers rely on machine learning. They are both parts of a whole but different.


What are the Characteristics of Big Data?

Big data consulting is a service where experts work with you to help you identify, collect, and analyze big data in your business. Cloud data management services are often built on cloud infrastructure and provide a way for your company to store, manage, and protect its data. Big data is any dataset that’s too big for the tools you have to analyze it or your computer’s memory. If you’re using Excel to store and analyze your data, you’re probably only dealing with small data—but if your dataset is so large that Excel can’t handle it, you’re dealing with big data.

When you need help handling your big data projects, get in touch with EES Corporation, a big data consulting firm. We offer a wide range of cloud-based data management services that make it easier to work with massive datasets, no matter what format they’re in.

A Quick Overview of the Big Data

Big data is a term that refers to the fact that companies and organizations are now able to collect and analyze massive amounts of data. This is possible due to increased computing power, advances in technology, and the increasing amount of information people create online and offline. Big data can also be characterized by its velocity, variety, and veracity. Velocity refers to how quickly the data is being generated; variety refers to the different types of datasets being analyzed; veracity refers to how reliable or trustworthy the datasets are.

The volume of data that companies collect is staggering; even if you’re not actively collecting data as part of your business model, there are important insights to be gained from the information you already have. While you may already be familiar with some types of data analysis, like running reports on sales or website traffic in Google Analytics, there are a number of other areas where your business can benefit from taking the time to analyze your data.

Some Characteristics of Big Data are:


  1. It’s not always easy to analyze with traditional tools
  2. It can be difficult to get accurate results without a lot of time and effort
  3. It can provide insights into customer behavior and preferences, which may lead to more sales or improved marketing efforts
  4. The amount of information available is enormous, but so are the possibilities!

If you’re new to the world of big data, it’s not the easiest concept to understand. At a very basic level, big data simply describes large volumes of data that are hard to work with using traditional methods. But beyond that, several factors contribute to what qualifies as big data:

Volume, It’s all in the name! Big data describes data sets that are so large they’re difficult to deal with in more traditional ways. The amount of data can be so much that it occupies storage space on several servers instead of just one. This volume can include anything from tweets and emails to website traffic logs and medical records.

The first V, volume, measures how much data is generated – but there is more to this than simply considering the amount of information coming in. Different types of information are often measured in different ways; for example, one megabyte of text is equivalent to 1 million characters but only 8 million bits (a bit is a single binary digit).

Velocity, This refers to how quickly new information is generated, collected and stored. For example, every second, Facebook users share over 684,478 pieces of content. Logging all this content in real-time would be impossible—so companies use automated tools to do it for them and then go back through it later at their leisure.

The Second V, Velocity, describes how fast your company or organization receives new information from its sources.

Variety, Not all information is created equal, especially when it comes to big data. There’s a wide variety of information that companies need to manage, including a mix of structured data (data with fixed fields) and instruction.

The third V, variety, refers to how many different types of data are collected. Some sources may be more valuable than others depending on what the business needs; for example, if you’re working at a hospital, you may want easy access to patient health records, but that same type of data wouldn’t be relevant in an auto shop.

Big Data Consulting

It is a form of consulting that helps businesses understand big data capabilities and work with it to improve their operations or make other kinds of business decisions. Big data actually states the large amounts of data that companies collect across social media, search engines, and other places. EES can help its clients and customers sort any kind of heavy data to sort it out for them. As businesses grow, they accumulate more and more of this data, which can be analyzed for patterns.


Top 5 Big Data Challenges

It is not easy to name the top 5 Big data challenges as it is data with volume, velocity, variety, and veracity. A massive amount of unstructured, raw, coming from different platforms and uncertain and imprecise is called big data. It can be defined as:


The volume of big data is primarily terabytes or even exceeding exabytes.


Data is created at the pace of approximately 1.7 megabytes per person per second.


The data is associated with various platforms as it is unstructured and raw when it is received.


A massive amount of data is imprecise and uncertain.

Top 5 Big Data Challenges

Big data faces the following top 5 challenges:

Big Data Security and Loopholes

Usually, at the time of big data deployment, security issues are ignored at the initial stages and phases, which is a significant challenge for the big data deployment process. Organizations and enterprises focus on analyzing, managing, storing, understanding, monitoring, and regulating the security data set aside. It sets the ground for attackers and hackers. Data breaches, record breaches, and database heists can lead to the loss worth up to the millions. Without spending a fortune, you can get multiple advantages from EES corporation agile, reliable, and scalable Cloud Big Data Consulting services, such as finding meaningful insights, performing data analytics, etc.


Big data security issues and loopholes can be handled in the following ways:

  • Organizations and companies should recruit more cybersecurity professionals.
  • Data encryption and segregation should be implemented in every phase.
  • Identity and access control and management should be regulated continuously.
  • Endpoint security should be practiced.
  • Real-time security tools and techniques should be used.

Scarcity of Professionals and Spending a Lot of Money

Most companies and enterprises lack skilled data professionals compatible with modern and advanced data tools and techniques. These qualified data professionals and expertise include data analysts, data specialists, and data engineers. Data managing and handling tools evolve and advance as per data need and time passage; meanwhile, data knowledge and understanding are not evolved accordingly. It creates a gap and space between tools and data professionals.

Big data adoption needs a lot of money investment such as:

  • Hiring and recruitments
  • Electricity and power expenses
  • Cloud services
  • Maintenance of frameworks
  • Expansions
  • Software development
  • Software configuration
  • Hardware maintenance and repair


Following are the best possible solutions for meeting the challenge of scarcity of professionals and spending a lot of money:

  • Companies and organizations should invest more in recruiting and hiring skilled professionals.
  • Companies should conduct more training programs and workshops.
  • Enterprises should buy artificial intelligence-powered knowledge analytic solutions.
  • Hybrid cloud solutions for companies with low budgets.
  • Data lakes offer the most reasonable data storage opportunities.
  • Optimized algorithms help reduce and decrease the power consumption of computers and systems being used.

Lack of Understanding and Knowledge of Big Data


Most of the time, organizations and enterprises neglect the comprehension of big data. Enterprises ignore the pros and cons of big data, the infrastructure needed to deploy correctly, and all other basic knowledge of big data. Suppose the current processes and algorithms of big data are not altered according to the requirements of the enterprise, instead of advancement. In that case, it can resist the organization from going for improvement and progress.

As big data is capable of massive changes, its knowledge and understanding are vital for all employees, including top management to ordinary workers. The utilization and deployment of big data depend on the acknowledgment of workers.


Enterprises and organizations should conduct regular workshops and training to ensure acknowledgment.

Big Data Growth Issues

One of the biggest challenges for companies, organizations, enterprises and businesses is to handle the rapidly increasing quantity of data. Usually, information received is unstructured, scattered, and dispersed from different sources such as text files, documents, audios, videos, and emails, making it difficult to search and find in a database. As the company progresses, data stored also grows exponentially as time passes.


Big data growth issues can be solved by several techniques such as compression, deduplication, and tiering techniques.


The compression techniques are used to reduce and compress the data bits leading to a significant reduction in the actual size of the data.


Deduplication includes removing and eliminating the duplicated and unwanted data from the bulk of data to decrease the overall data size.


Data tiering is technique companies and organizations use to store data bulks in appropriate and suitable spaces and environments, data storage tiers. Data tiers include the followings:

  • Public clouds
  • Private clouds
  • Counting on the information size
  • Flash storage

Integrating Data

Integrating data from all different platforms is one of the most challenging works for IT personnel. Most of the data come in dispersed and disassembled forms from other platforms. Sometimes half of the platforms are not supported locally. The developer must continuously alter the program or source code if the data is received in an unsupported form. It leads to the slow processing of the advancement cycle of the organization or enterprise.

In that way, many big data processing platforms create a huge hindrance and challenge for IT to re-arrange the complete infrastructure.


The best solution for this challenge is the software automation tools with APIs for considerable data, records, and databases.

Capgemini vs Deloitte: Which is best for cloud services?

Deloitte is one of the largest and most prominent services worldwide. However, Capgemini offers impressive project management, meeting presence, updates, and implementation. Also, they are easy on customer pockets. This article will highlight and compare Capgemini vs Deloitte cloud services in detail.

Capgemini vs Deloitte – Cloud Services

The Cloud is laying the foundation for businesses to become digitally agile.


Capgemini Cloud helps businesses harness innovation to open new collaboration and value chain optimization avenues. It is revolutionizing how we work and live by giving people the capacity to do more with less—accelerating human novelty.


Deloitte propels business transformation using innovative applications in the Cloud. Its services combine integrated business technology, a people-first approach, and business acumen to discover and activate potential. It also offers a full spectrum of capabilities that help businesses implement a compelling Cloud journey.

Benefits of Cloud Services

capgemini vs deloitte

Modernized Datacenter

  • Enhanced agility and quality at reduced costs.
  • Public Cloud Application Migration.
  • On-Premise Automation via Private Cloud.

Modernized Applications

  • Enhance performance, scalability, and productivity.
  • SaaS or managed ISV Public Cloud applications.
  • Custom Cloud Applications.

Business Agility

  • Reduced time to market.
  • Identify new business opportunities.
  • Build Cloud-native applications for new services.
  • Cloud Application Integrations.
  • Real-time APIs development and deployment.

Capgemini vs Deloitte Cloud Offerings


Capgemini helps businesses develop a business-case-based Cloud roadmap by providing different services, which include:

Cloud Strategy

Cloud adoption gets limited by people not having a comprehensive business transformation plan and failing to identify risks. Capgemini offers cloud strategy sessions that fuel digital transformation using:

  • Cloud Business Vision: Aligns business objectives with cloud strategies to create targets and goals.
  • Cloud Value: Highlight the costs and benefits of your Cloud journey.
  • Cloud Roadmap: Scour through different options and activities and plot your Cloud journey.
  • Cloud Transformation Plan: Underline business skills and changes required to harness the Cloud’s full potential.

Cloud Applications

Capgemini offers Cloud application services that help businesses transform agility, efficiency, and performance, including:

Capgemini Enterprise iPaaS

A cloud-agnostic platform assisting businesses in enhancing the delivery of APIs and other services. Capgemini Enterprise iPaaS helps clients by providing:

  • Flexible pricing
  • Open-source products
  • Dedicated Data Isolation Instances

Software-as-a-Service (SaaS)

Accelerate your Cloud journey by choosing, deploying, and integrating the right Software-as-a-Service (SaaS). Capgemini provides SaaS solutions and business integrations using pre-built accelerators. It enables users to access software from top vendors, including Microsoft, Google, Salesforce, SAP, Netsuite, Oracle, and Workday.

Cloud-Native Applications (PaaS)

Build cloud-native applications and increase business agility. Capgemini offers a good deal of enhancement services, and you can deploy enhancements continually to improve services.

Migrating Workloads to the Cloud

Capgemini offers robust methods for migrating workloads to the Cloud. Their services include aligning your cloud architecture and migration pattern with your business goals:

Cloud Architecture

Define your business case and establish the architecture and operating model needed to succeed.

Migration Execution

Manage factory model migration.

AWS Cloud Migration for SAP

Capgemini offers its Cloud Choice with AWS end-to-end portfolio that helps businesses leverage SAP on the AWS Cloud for enhanced efficiency and automation.

  • Workloads Assessment: Transforms businesses’ agility and application portfolio using a Cloud-first approach to reduce cost. It provides a systematic, cloud-agnostic assessment of applications and helps clients make informed decisions:
  • Business case: Illustrating the business value of Cloud design.
  • Cloud Suitability: Evaluating applications for migration by checking value and sensitivity
  • Proof of Concept Planning: Underlining a migration roadmap
  • Cloud options: Choosing the suitable Cloud service model and assessing how applications perform in a cloud environment.
  • Capgemini Cloud Platform: Businesses leverage the right technology and processes to harness the total efficiency and agility of the Cloud. Capgemini provides a portfolio of cloud services and business enhancers using its cloud management platform.


Deloitte engineers business transformation by providing services that help organizations manifest their unique cloud advantage:

Cloud Strategy

Cloud transformation approaches are pretty complex, and there’s no one-size-fits-all. Deloitte customizes solutions to meet the industry demands of different businesses by assessing how a practical roadmap can get created to maximize cloud potential.

Application Modernization & Migration

Businesses can reimagine their architecture and IT functions with high efficiency.

  • Cloud Modernization
  • Cloud Migration

Cloud Analytics & AI

Deloitte cloud services allow businesses to harness advanced analytics, make insight-driven decisions, understand modern business operations, and increase value.

  • Machine Learning
  • Data Analytics
  • Artificial Intelligence

Cloud Business Transformation

Deloitte Cloud services allow businesses to create sustainable value by systematically identifying meaningful opportunities and capitalizing.

  • Self-funded Transformation
  • Cloud Strategy
  • Business Change Management

Cloud Infrastructure & Engineering

Businesses can modernize infrastructure by harnessing next-generation technology to enhance:

  • Security Design
  • Data Center Modernization
  • Network Transformation & 5G/Edge Capabilities

Cloud-Native Development

Deloitte cloud speeds up the deployment of cloud applications. It creates cloud-native solutions that are easy to build and deploy.

  • Modern App Development
  • DevOps
  • Cloud Integration

Cloud Operate

Deloitte’s operations and management support provide businesses with a flexible, scalable cloud solution that speeds up business development.

  • Cloud Managed Services
  • FinOps as a Service and Observability
  • Application Managed Services

Cloud Workforce & Operating Model

Businesses can transform their Cloud operating model and workforce. Including:

  • Cloud Processes & Tools
  • AIOps
  • Smart Workforce with the Deloitte Cloud Institute
  • Organizational Readiness

Cyber & Strategic Risk

Become more innovative and resilient against persistent cyber-attacks.

  • Control and Compliance Management
  • Digital Identity
  • Infrastructure and Application Security Management
  • Detection and Response Management

ERP & SaaS

Businesses can deploy comprehensive next-generation ERP & SaaS services, scalable from anywhere.

  • SAP on Cloud
  • Cloud SaaS Solutions
  • Oracle on Cloud

Hybrid Cloud

Businesses can maximize agility by integrating cloud infrastructure and apps to build a hybrid cloud ecosystem:

  • Planning, Strategy, and Deployment
  • Edge Computing
  • Application Modernization and Migration

Capgemini vs Deloitte Takeaway

Capgemini has a neutral social sentiment when analyzing social media channels and online mentions. So does Deloitte. Deloitte aims to tackle the core business issues of today and the future. Capgemini has in-house tools, which help analyze the data and find key insights.

The solutions are advanced and can handle errors smoothly. It allows businesses to start and expand their insurance wings to expand market capitalization.

Deloitte provides the ability to conduct real-time scenario planning and modeling. The Cloud platform can ingest a range of datasets and produce clear outputs. The team also offers knowledgeable data scientists to help you interpret the data.

Cloud Readiness Assessment: A Comprehensive Guide

With the day-by-day advancements of technology, more and more impactful and valuable methods are being introduced to ease operational labor. “Cloud” or “Cloud Computing” is one of the advancements made in the modern era. A cloud is basically “all the stuff on the internet.” The data uploaded on the internet servers each second is being stored on millions of computers and storage devices all at once which are connected through various modes. That interconnected data has essentially termed the cloud, and this process of accessing the data and working with it is called cloud computing.

More and more organizations, whether small-scale organizations or multi-tenant groups with hundreds of employees are shifting to the cloud rapidly and getting “cloud-ready.”

What is Cloud Readiness Assessment?

It is the method in which an organization surveys its data and applications to determine whether they can be shifted to the cloud environment with minimal labor and effort. Cloud Readiness Assessment not only helps an organization to conclusively find out about the capabilities of their systems but also helps them to take adequate steps to shift to the cloud. Integrating the resources with the cloud can often be a very messy job and should be done with care. And this process helps you make sure a coherent integration with the cloud happens, and the mitigation with its resources is seamless.

With EES cloud computing consulting services, you can harness the real benefits of the advanced, secure, reliable, and scalable cloud environment. We assist from cloud migration to cloud optimization at surprisingly lower operational costs because quality is what we focus on!

In this article, we will discuss the guidelines for an effective Cloud Readiness Assessment and the steps taken to ensure it. But the most important part is not how it is, however, the why and what. Before shifting all your resources to the cloud, it is imperative to make sure why you need a shift in the first place? If you don’t know why you should migrate to the cloud, it is the same as driving without headlights.

Reasons and Goals for Integrating into The Cloud

  • To maintain economic balance
  •  Increased productivity and scalability
  •  Increased collaboration with the resources
  • Improving the fail-over capacity of the system.

One thing which should also be highlighted here is the organization. Before moving to the cloud, the organization should know what resources to integrate with the cloud and what resources should be left untouched, as moving all your eggs in a single basket could prove fatal in the long run.

Cloud Readiness Assessment Guide

Following are some important steps in guiding one towards a seamless shift to the evergreen and upcoming cloud environment:

Finding Out the Scope and Business Objectives Towards the Shift

An organization should have a crystal clear image of why it should move to the cloud and to what extent. Once the reasons for the move are decided, an organization should be clear about what of its resources should be moved to the cloud as it would be foolish and problematic to shift all of its data and resources to the cloud. One example could be the security and authentication resources which ensure the company about the privacy and administrative settings of an organization. They should be in the authoritative control of the organization itself.

Some business objectives for shifting towards the cloud are as follows:

  •  To maintain economic balance
  •  Increased productivity and scalability
  •  Increased collaboration with the resources
  • Improving the fail-over capacity of the system.

Analyze The Potential of Your Resources and Fill the Gaps

The next major goal is to analyze and scrutinize the resources at your disposal—the IT team, for example. You should know what potential they have and do they even have enough knowledge for shifting to a cloud-based environment or not. Once you analyze, you need to fill in the gaps where necessary. Following are the things you should look for in your resources:

  • Do they possess the right and real skills for such a task
  • Are they fully available on the scene for the mitigation
  • Do they have any prior experience
  • Do they have the right tools and technologies

If you identify any shortcomings among the points mentioned above, you should immediately adhere to damage control and fix the problems. One way to make your IT staff more productive in itself is to educate them on new and upcoming technologies and organize workshops and seminars for them to be further guided about cloud readiness assessment. 

Assess Infrastructure Requirements

An organization must do internal research within its resources and its infrastructure to ensure that they have all the possible resources, applications, and tools required for a move towards the cloud. Planning for a new environment or shifting on a large scale can take a load on the company’s resources, tools, and applications, and they should have future planning beforehand. The steps taken now will ensure the feasibility of your organization; otherwise, all the resources could choke.

The following can be important requirements regarding infrastructure that need to be assessed:

  • Modification of the applications
  • Costs and technologies used
  • Application dependencies

Security Needs

Whenever an organization makes a shift from conventional ways of computing towards a more advanced method such as cloud environment, security and privacy is one of the main concerns of a company. Choosing the right cloud platform is the primitive need of a company. When choosing to migrate to a cloud-based environment, it is essential that they keep in mind all the key factors behind such an environment. You need to assess the provider’s cloud-based system and select the one best meeting your security requirements.

Following are some of the security concerns highlighted in the Cloud Readiness Assessment:


Many companies decide to mitigate towards a cloud-based environment before discussing the costing and budgeting of the whole process. A company needs to manage its budgeting policies beforehand as it is one of the biggest challenges in choosing a cloud-based environment. The best practice is to decide on a budget and stick to it. Without proper reasoning and planning, such an infrastructure can surpass the estimated cost value, and organizations can be led to a mismanagement of a situation.

Some key parameters to be considered are:

  • Usage (per month/year)
  • Growth rate
  • Maintenance, Automation, etc.
  • Average resources

Final Verdict

All in all, it can be said that cloud-based environments are the talk of the town these days, but choosing and shifting to it is a rather intricate process and requires adequate thinking and planning. With good reasoning and planning or Cloud Readiness Assessment, one can choose a good cloud-based for its needs and have a profound and profitable future.

Mitigating Mobile Malware Attacks with MDM

The number of mobile-oriented malware has increased exponentially over the past few years. According to Statista, the first half of 2021 saw over 2.3 million mobile malware installation packages. The number of attacks detected has decreased compared to the previous year but the attacks have become more sophisticated, as per Kaspersky. IT professionals are seeing mobile-specific malware that is designed to target smartphone features and exploit vulnerabilities.

As mobile devices become central to modern life, more sensitive and high-value data is exchanged on the go making it a popular target for cybercriminals. For organizations that depend on mobile devices to conduct business activities daily or allow employees to carry their personal smartphones and tablets as a part of their BYOD policy, the threat of mobile malware attacks is high and needs to be addressed urgently.

What is Mobile Malware?

Mobile malware is malicious software created to target mobile devices such as smartphones and tablets. It is specifically written to exploit particular mobile operating systems and related technology. Cybercriminals use many types of mobile malware variants and distribution methods to infect mobile devices. They may have one or several objectives, including stealing private data, locking a fleet of corporate devices for demanding money for its release, or charging users fees for services they did not sign up for.

Mobile Malware Attack is Exploding

  • Earlier this month in February, researchers at Proofpoint detected a 500% jump in mobile malware delivery attempts in Europe.[*]
  • The number of stalkerware attacks on the personal data of mobile device users increased to 67,500 in 2019, almost double the number of attacks the year before.[*]
  • Android is the most popular target for attacks. The platform is open to multiple app stores and users can sideload apps from anywhere on the internet. This allows bad actors to compromise Android phones in just a few steps.

Different Types of Mobile Malware


Madware, a portmanteau combining the words mobile and adware, installs a script or program on a mobile phone without the user’s consent. The purpose of madware is to collect data and spam users with ads. There is an element of spyware in which the madware collects data about phone usage and shares it with a third party. This data may include location, passwords, and contacts.

Mobile Ransomware

Attackers use mobile ransomware to steal sensitive data from a smartphone or lock a device, demanding payment to return the data to the user or unlock the device. Using social engineering techniques, users are tricked into downloading benign content or critical software. It then shows a fake message accusing users of unlawful activity before encrypting corporate data and locking the device.

Mobile Phishing

Mobile phishing is a popular sub-type of phishing method. For phishing emails, users have the ability to hover over the link to see where it redirects and potentially identify a harmful URL. Mobile phishing, however, uses applications to deliver mobile malware. Users cannot differentiate between a legitimate application or a fake application, making this type of attack effective. Phishing campaigns through SMS and MMS applications have created a sub-category of mobile phishing called smishing.

Viruses and Trojans

Such types of mobile malware often fly under the radar and go undetected by users. They may carry harmless payloads, such as changing language or wallpaper settings. But a majority of them have malicious intent in mind. Bank trojans appear as legitimate applications and look to compromise users who conduct their banking transactions from their mobile devices. Such trojans aim to steal financial details and passwords.

Browser Exploits

Browsers are inherently designed to interact with other websites and applications. Browser exploits are code that allows attackers to exploit the vulnerabilities in browsers and their related extensions, applications, and third-party plugins. When a vulnerable browser meets a website infected in the previously mentioned ways, attackers take control of the browser and applications associated with it.

How to Protect Against Mobile Malware with Mobile Device Management

Organizations that plan to protect their corporate-owned devices or employee mobile devices under its BYOD policy, can benefit from an MDM-first approach. Besides the threats mentioned above, many other factors compromise the security of mobile devices such as poor passwords or jailbreaking. An effective MDM software can nullify mobile threats by:

  • Controlling apps: MDM solutions are designed to help IT teams remotely monitor and control devices, including allowing only enterprise apps and blocking unauthorized apps. Users can be restricted to access safe listed websites as per the organization’s security policies.
  • Updating OS: Users exploit OS vulnerabilities to jailbreak their phones and obtain root permissions. Device management allows IT professionals to deploy the latest and most secure OS versions. Some modern MDM platforms also provide alerts for users trying to invade the restrictions with jailbreaking.
  • Managing Wi-Fi: Public Wi-Fi and other unsecured networks make it easier for attackers to perform man-in-the-middle and other attacks. Controlling Wi-Fi settings and preventing access to public Wi-Fi networks and ensuring corporate data is accessed using VPN can be achieved via an MDM.
  • Enabling remote wipe on all devices: When attackers get physical access to a mobile device, a number of options exist for bypassing a screen lock. Remote data wipe is an MDM security feature that allows IT administrators to protect data from compromise when a device is lost or stolen.
  • Setting up a geofence: Most MDM solutions identify lost or missing devices by remotely obtaining the device location. Few modern MDM solutions also enable companies to set virtual boundaries to physical locations. Geofencing restricts device functionality to a particular geographical location and secures corporate data.

Wrapping Up

To drive a successful mobile malware protection initiative, organizations need solid technology and employee awareness. Mobile device cybersecurity training is essential for teaching users the risks associated with unwise actions such as downloading untrusted apps and visiting unsafe websites. Combining responsible user behavior with a robust MDM solution should prepare companies against potential attacks.

What is Disaster Recovery in Cloud Computing?

Disaster recovery refers to the method and techniques employed by an organization to keep and maintain access and control over its IT infrastructure even after a disaster happens, whether natural or cyberattack, including business distortions caused by COVID-19. A disaster recovery plan is a crucial component of business continuity. You can employ a variety of disaster recovery (DR) methods to stay aloof from all disasters. Disaster recovery uses data replication techniques and computer processing in a remote data center that the disaster cannot affect. Whenever servers a disaster causes servers to go down, such as cyber-attacks or equipment failure, businesses need a secondary location to recover lost data from a backup server.

Businesses can also transfer computer processing to a remote server to ensure round-the-clock uptime and continue operations.

What is Disaster Recovery & its Benefits?

No business should take the risk of ignoring disaster recovery techniques. The two most essential advantages of a proper disaster recovery plan include:

Fast Recovery

A company can resume operations quickly after a disaster.

Cost Savings

Disaster recovery can help businesses save thousands or even millions. Sometimes it also determines whether a company survives a disaster or cannot recover and shuts down.

What are the Different Disaster Recovery Techniques?

There are many disaster recovery techniques that businesses can choose, or combine several to make an ultimate solution:

Disaster Recovery as a Service

DRaaS vendors migrate an organization’s data and computer processing to its cloud infrastructure. It allows businesses to continue operations seamlessly from the vendor’s location, even if an organization’s servers are down.


This simple disaster recovery method focuses on the storage of data remotely or using a removable disk. Still, backing up your information barely contributes to business continuity because the network infrastructure itself remains untouched.

Cold Site

This type of disaster recovery involves setting up basic business network infrastructure in a secondary facility. It ensures that employees still have a space to work, even after a fatal disaster. Cold sites help with business continuity by allowing operations to carry on. However, it lacks the provision to protect or recover sensitive data. Therefore, you can combine this technique to develop a more effective disaster recovery strategy.

Hot Site

A hot site helps maintain updated copies of data and files around the clock. However, setting up a hot site can be time-consuming and more costly than cold sites. Still, it dramatically reduces downtime.

Instant Recovery

Instant recovery works like point-in-time copies. However, instant recovery makes copies of the entire virtual machine instead of copying a database alone.

Back-Up as a Service

Like remotely backing up data, Back-Up as a Service involves delivering backup storage to businesses by a third-party provider.


Businesses can back up certain operations or replicate an entire computing environment on cloud virtual machines, safe from physical datacentre disasters. It enables the automation of recovery processes and restores functions faster.

Datacenter Disaster Recovery

Physically protecting a data center can preserve and enhance cloud disaster recovery in specific disasters. Some of these techniques include fire suppressors, which prevent data and infrastructure loss when there’s a fire. Also, backup power supplies guarantee uptime even when there is a power outage.

Point-In-Time Copies

Point-in-time copies/snapshots are backup files of an organization’s database made at given intervals. Users can restore data using the shared copies if they are off-site or unaffected by the disaster.

Building An Effective Disaster Recovery Plan


  1. Get A Disaster Recovery Team: Businesses must assign specialists to create, manage, and implement disaster recovery plans. An effective recovery plan carefully defines the roles and responsibilities of team members. It also outlines proper communication channels for the recovery team, vendors, employees, and customers.
  2. Identify Business-Critical Assets: An effective disaster recovery plan includes detailed documentation of all the critical resources, applications, systems, and data, including the recovery steps.
  3. Backups: Businesses must determine beforehand what data needs backing up and ensure that people explicitly perform backups. An effective backup includes a recovery point objective (RPO) to underline the frequency of backups and a recovery time objective (RTO) to define the maximum amount of downtime.
  4. Testing and Optimization: A business’ data recovery team should perform continuous tests and strategic updates to keep up with changing threats and business needs. It can help ensure that an organization stands firm against disasters.
  5. It’s crucial that organizations consistently test and optimize data protection strategies.
  6. Risk Evaluation: Businesses must carefully assess the potential risks they may encounter. There must be a strategy to determine the actions and resources needed to resume business in the event of an attack or disaster.

Planning For Disaster Recovery and Business Continuity

A network outage can significantly affect business operations, especially with the current pandemic in effect. Your plan should include people and not just focus on technology. The pandemic has asserted that business teams need support and proper resources for effective productivity. Ensure that you have a solid strategy to provide these elements to all employees, more so remote workers.

You can also include some additional cloud, software-as-a-service solutions to increase efficiency and enhance flexibility. It also reduces the burden of relying on a single data center. You can add infectious diseases and potential risks to your business’s disaster recovery plan. An effective strategy for such an emergency can help ensure that things get handled smoothly without affecting business operations.

EES is bringing ultimately flexible, affordable, and secure cloud computing consulting services where you can scale up and down the features per your business needs. Migrate your infrastructure to our cloud platforms to enjoy unparalleled performance!

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