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7 Reasons Why Cloud Computing Is The Best For Agile Software Development

Businesses today are reaping huge benefits from cloud computing. Cloud computing has churned a completely new gamut of services and solutions that has enabled businesses to exhibit their software development prowess. The innovative features and user friendly nature of cloud has made itself appealing to the IT community as a whole. The range of cloud computing services encompasses a wide range, so much so, that some of these services are still beyond imagination. Often the disadvantages of cloud computing are shrouded by its advantages; however, this doesn’t deter users from optimizing its potential. The Nexus between Cloud Computing and Agile Software Development Agile development methods, being iterative and continuous in nature can experience a slack due to various infrastructure and software shortcomings. This is best addressed by cloud computing services that involve cloud platforms, software and virtualized machines. Cloud computing and virtualization are fast, interactive and flexible so that the development process runs smoothly right up to production. Cloud computing and virtualization make it easy for Agile development teams to seamlessly combine multiple development, test and production environments with other cloud services. Let’s look at some reasons why cloud computing is best for Agile software development. How cloud computing aids Agile software development process 1. Saves time due to multiple servers A developer using physical servers is restricted to one server for development, staging and production, leading to slower processes. Developers working on the cloud have access to an unlimited number of servers, virtual servers or cloud instances; thus speeding up their work. They are independent of physical servers being available for them to continue working. 2. Provisioning servers to suit your needs With a physical environment, developers are reliant on IT staff to provision the servers or install the desired platforms, software, etc. Despite using responsive development methods, you could experience delays in such situations. With cloud computing, developers can install the necessary software or platforms on their own, without reliance on the IT department. 3. Cloud Computing encourages innovation via investigation Agile development teams can create instances on the go as and when the need arises. Not just that, they can also experiment with novel instances whenever they stumble upon an interesting user story. As these instances can be coded and tested simultaneously, there is no waiting time involved. Developers can develop experimental instances and test them in a cloud computing environment. This helps them to stay true to the Agile philosophy of innovation through experimentation. 4. Boosts continuous integration and continuous delivery Builds and automation take time to develop. For codes that don’t yield results during automation, the Agile team will have to code and test them recurrently until the desired results are seen. With the availability of large number of virtual machines, Agile teams can fix the errors faster. Cloud computing accelerates the speed on delivery. Hence virtualization enhances integration and delivery. 5. Cloud computing simplifies code branching In Agile, the development cycle outlasts the release cycle. Code refactoring is generally enhanced and used during the production phase. At such times, code branching becomes absolutely necessary so that modifications happen in parallel along the branches. Having a cloud computing software means reduced cost of renting servers for this purpose. 6. Increases accessibility of development platforms and external services Agile development needs several project management, issue management, and automated testing environments. Most of these services are available as SaaS, including Salesforce and Basecamp; then there are IaaS offerings like AWS, OpSource, Rackspace cloud etc. and PaaS instances like Oracle Database Cloud Service and Google app engine. These services are known to specifically assist Agile development. 7. Parallel Testing Another advantage of the cloud is the ability to create multiple environments, where you can easily build a new environment and isolate the versions of code that you are testing. You can have multiple environments where one developer tests for a feature while another environment is created for another developer testing a different feature. This arrangement allows multiple people to work on different parts of the code and work in parallel. Agile Development For Cloud Related Services IaaS platforms offer great functionality around provisioning new instances with a full range of features and configuration options. When entrusted to system administrators and Agile developers, these platforms can provide the flexibility to create custom environments perfectly suited to the requirements of an application. Cloud computing and its related services are extremely essential when Agile teams aim to produce products via continuous integration and delivery. This makes Agile development a more parallel activity than a linear one. Virtual servers also eliminate delays in provisioning. Thus enterprises utilize this combination for innovation with standard business ideas.

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agile

7 Ways to Mitigate Your SaaS Application Security Risks

If you’re a SaaS entrepreneur or you’re looking to build a SaaS application, in that case, you may already be aware of the fact that there is a new economy that has evolved around SaaS (Software as a Service). Core business services are offered to the consumers as a subscription model via pay-per-use in this SaaS market. Studies have revealed that Software as a service (SaaS) enterprises are evolving at a sky-rocket speed. They are becoming the first choice due to their simple up-gradation, scalability, and low infrastructure obligations. Per Smartkarrot.com, the SaaS industry’s market capitalization in 2020 was approximately $110 Billion and is expected to touch the $126 billion mark by the end of 2021. And it is expected to reach $143 billion by the year 2022. However, security is one of the primary reasons why small and medium businesses hold back from taking full advantage of powerful cloud technologies. Though the total cost of ownership was once viewed as the main blockage for possible SaaS customers, security is now on top of that list. The anxieties with SaaS security evolved with more and more users embracing the new technology, but is everything all that bad as reviews and opinions hint? Here are 7 SaaS security best practices that can help you in curbing SaaS security risks, that too cost-effectively: 1. Use a Powerful Hosting Service (AWS, Azure, GCP, etc.) and Make Full Use of their Security The biggest cloud providers have spent millions of dollars on security research and development and made it available worldwide. Leverage their infrastructure and the best SaaS cybersecurity practices that they have made available to the public and focus your energy on the core issue(s) your software resolves. API Gateway Services Security Monitoring Services Encryption Services 2. SaaS Application Security — Reduce Attack Surface and Vectors Software/Hardware – For example, do not define endpoints in your public API for admin related tasks. If the endpoint doesn’t exist, there is nothing else to secure (when it comes to SaaS endpoint protection)! People – Limit the access people have to any sensitive data. If required, for a user to access sensitive data, log all the actions taken and, if possible, make it necessary to have more than one person involved in accessing the data. 3. SaaS Security Checklist — Do not Save Sensitive Data Only capture data you absolutely need. For instance, if you never use a person’s national ID number (e.g., SSN), don’t ask for it) Assign a third party for sensitive data storing. In this, for example, your system never holds possession of any credit card number, so you don’t have to worry about protecting it. 4. Encrypt all your Customer Data — Adopt the Best SaaS Security Solutions Data at Rest: When any data is saved either as a file or inside a database, it is considered “at rest.” Almost every data storage service can store the data when it is encrypted and then decrypt it when you ask for it. For example, SQL Server enables you to turn on a setting to encrypt the stored data with their Transparent Data Encryption (TDE) feature. Data in Flight: When data is read from storage and transferred out of the currently running process, it is called “in-flight.” Sending data over any networking protocol, be it FTP, TCP, HTTP, is data that is “in-flight.” Network sniffers (if attached to your network) can read this data, and if it is not encrypted, it can be stolen. Employing SSL/TLS for HTTP is a typical example. 5. Log All Access and Modifications to Sensitive Data — Opt for a Robust SaaS Security Architecture There’s no guarantee that your system’s security will never be breached. It is more of a question of “when will it happen” rather than “if it will happen.” For this very reason, it is crucial to log all changes and access to stored sensitive data and adjustments to user permissions and login attempts. When something actually goes wrong, you have an audit log that can be used to solve how the breach occurred and know what needs to change to stop any further similar security breaches. 6. Implement Two-factor Authentication Social engineering is the most common way which hackers use to breach any system. Make social engineering hacks more complex by asking users to have a second step to authenticate with your system. Implement a system that needs at least two of the following three types of information: Something the user knows (e.g., username/password) Something the user has (e.g., phone) Something the user is (e.g., fingerprint) Sending a code to a user’s phone or email is a simple yet effective way to implement two-factor authentication. To balance the added security with the demand for usability, give your clients the option of choosing if they would like to use the phone or email and an option for the code validity for the device being used. 7. Use a Key Vault Service Key Vaults allow the stored sensitive data to be accessed only by applications that have been given access to the Key Vault, removing the need for a person to handle the secrets. A Key Vault stores all secrets to encrypt data, databases/datastores access, electronically signed files, etc. Cloud platforms like Azure and AWS offer highly secure and configurable Key Vault services. For extra security, use different key vaults for different customers. For advanced security, allow your customers to bring their keys. Takeaway There are several reasons why businesses must take advantage of cloud computing to enhance their operational efficiency and reduce their costs. Nevertheless, security concerns often hold back businesses from placing their valuable data in the cloud. But, with the right technology and best practices, SaaS can be far more secure than any on-premise application, and you can have numerous options for retaining control over your security infrastructure and address the security issues head-on with your respective provider.

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Application Security Cloud Security SaaS Security

8 Things to Consider Before Choosing Your DRaaS Provider

In today’s era, business information is much more valuable and sensitive than ever before. According to a recent survey held by the University of Texas, you’ll be surprised to know that nearly 94% of companies undergoing a severe data loss do not survive, 43% never reopen, and almost 51% close within 2 years of the loss. Also, per Gartner, 7 out of 10 SMBs go out of business within a year of experiencing a major data loss. These statistics clearly show that with a growing dependency on information technology, the prospect of downtime, mass loss of data, and losing revenue is a very real concern, not to mention the long-term damage these occurrences bring to your company’s image and potential profit. The surge of disaster recovery as a service (DRaaS) presents a range of opportunities to safeguard our infrastructure and resources. DRaaS uses the infrastructure and computing resources of cloud services and presents a practical option to an on-site technology DR program. Administrators and IT leaders can make use of it to supplement their existing DR exercises by adding more comprehensive performance abilities. They can also employ the technology to replace their current DR activities entirely. Disaster Recovery as a Service (DRaaS) offers faster and more flexible recovery options for physical and virtual systems across different locations, with shorter and quicker recovery times. Yet, like any other advanced technology, DRaaS also bring various risks to the table. A vital tool for overcoming such DRaaS risks is known as a service-level agreement (SLA). It includes what the DRaaS vendor will provide based on performance metrics, such as uptime percent, percent availability of resources, and blocked security breaches. It also spells out solutions, such as financial penalties or refunds of maintenance costs for vendor failure to satisfy SLA conditions. Below, we discuss a few top risks involved with DRaaS and ways to mitigate them. Risk Issues of DRaaS and Ways to Mitigate Them 1. Access control In case of an emergency, securing access to critical data and systems is imperative to prevent any unauthorized access and possible damage. If a vendor has a Service Organization Control 2 (SOC 2) report available, make sure you ask for a copy of the same. But why? Because it provides you the audit data that addresses security, availability, confidentiality, processing integrity, and privacy metrics. 2. Security Considering that your critical company data might soon reside or already residing in a cloud environment, the security of that data is of greater concern than when the data was stored on site. Hence, ensure that your DRaaS provider has an extensive set of security resources to ensure that your critical business data is safeguarded and is always accessible. One such approach that you can follow is to work with a vendor that has multiple data centers with redundant storage facilities so that your critical business data can be kept and stored in more than one location. 3. Recovery and restoration These are the two key metrics in a DRaaS program that indicate how quickly a company’s data and systems can be restored to service after a disruptive incident. If your DRaaS provider’s track record during disasters compels you to take a pause for concern, adjust the parameters accordingly in the SLA or consider returning critical systems and data on-site to an alternate DRaaS vendor. 4. Scalability and elasticity The most important reason for the growing demand for managed services is their ability to adapt to changing business requirements quickly. While negotiating contracts and SLAs, you must make sure to evaluate the additional resources that can be made available during an emergency and how soon they can be activated. A vendor must fully disclose where the data and systems are kept and how resources are federated among other vendors. This is necessary to make sure that the data is accessible whenever required. 5. Availability It would be best to make sure that your resources are accessible when and where you need them. It is essential to keep in mind that every minute that technology and/or data aren’t restored in case of a disaster, your business runs the risk of a severe disruption to operations. Data in a SOC 2 report can shed some light on potential availability issues. 6. Data protection Never forget that lack of adequate data integrity controls can really endanger customer systems and data. So make sure that your vendor provides suitable data protection controls. 7. Updating of protected systems System and data backups must be made according to a client’s requirements. For example, full backups and added backups and security access to those backups must be safeguarded. Again, your SOC 2 reports can provide valuable information on these activities. 8.Verification of different data, data backups, and disaster recovery Your vendor’s capability to quickly verify data backup and system recovery is necessary for your IT management. So that, in any case of disaster, those key activities can be fully confirmed. Final Thoughts To summarize, true disaster recovery is a process of a continuous feedback loop, where testing and new information are included in the program to enhance your recovery options. But, without constant testing and feedback, your disaster recovery plan is ineffective. The point of all this is not to confuse you in any way, but instead, to help you open your eyes to the realities of DraaS risks you might experience in the near future. With all this knowledge, you must appropriately create a recovery plan that is extensive and well thought of, rather than full of missteps. Consider all this information when you start looking for a DRaaS provider to prepare the best plan possible.

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Cloud Security DRaaS Recovery as a service

A Complete Guide To Cloud Containers

This blog article briefs the current technological trends and advances made to enable cloud scale orchestration possible. VMware brought physical machine virtualization to commercial world about a decade ago. Today it is Containers based micro services that is doing it again. Docker, Kubernetes and Mesos are being discussed everywhere and are projected as the next big thing to watch out for.This article tries to explore this latest buzz around Containers.1 IntroductionPhysical machine virtualization has started off a great trend in many areas. Today virtualization is an umbrella term widely used everywhere. Any place, where a logical handle of a physical resource is provided, enabling sharing of the physical resource is deemed virtualized. Virtualization by extended definition enables higher utilization of deployed resources. There is not just compute [CPU] virtualization, there is storage and network virtualization too. It has been known for some time that CPU performance lay wasted, as its performance is far ahead than either the network or memory components. Therefore it was assumed virtualizing CPU would provide more benefits. The success of virtual machine adaptation in varied domain puts any argument against to rest, beyond any doubt.Companies widely posted their success stories to describe the scaling of their physical infrastructure and failure resolution. Industry got busy integrating virtual machines as part of standard workflow. But then there was Google, who were not just experimenting but deploying with great success in live networks another new model called Containers. In short, containers are lightweight totally isolated userland sandbox for running processes when compared to virtual machines 1.Before Software defined anything was even spoken about, Google had designed their very own Borg Cluster running and managing container based micro services. Google made lots of assumptions to begin with, and in hindsight some of them were great. This learning they had with container management is being used in the design and implementation of Kubernetes. The container lifecycle management by itself is done by Docker engine, part of Docker. And then there is Mesos.To understand and appreciate Kubernetes, Mesos and Docker engine, it will be worth the effort to look at their fundamental building blocks.Figure 1: VM vs Containers2 Some HistorySolaris projects/zones, BSD Jails and LXC containers all do userspace compartments. The basis for all this stems from chroot system call introduced way back in 1982! Although chroot accomplished a new root filesystem view for applications to run, it opened up the need for rest of the OS pieces to be virtualized too. And *bsd jails has been doing total container virtualization since time immemorial. But today, Linux seems to rule the world! With relatively recent advancements in Linux for control groups and namespaces, it enhanced Linux to have highly sandboxed environment for containers. And Docker Inc, opensourced a suite of tools, that provides a clean and easy workflow to distribute, create and run container based solutions.And Kubernetes and Mesos applications are built over native OS support on containerization. It would be prudent to note that only userspace virtualization is possible in container world. If different versions of OS, or different OS are needed, then virtual machines are needed still. And with Windows OS, also working with Docker for container integration, we sure will see many cloud services being run as containers on multiple OS’es.With that background out of our way, let us understand the major pieces that Docker has brought in today.3 Build, Ship and Run anywhereWhy does everyone love containers? It makes development, test and deployment easy, by recreating the same environment from development everywhere.Normally, requirements come from customers and an engineering team starts working on it. Once the application is signed off by dev team, then testing team tries to install the application, where all application dependencies needs to be satisfied. That is inhouse and the environment can be controlled. But deployment is never easy, because the customers environment can have conflicting set of applications running, and satisfying dependencies for the new application along with those existing, is to lightly put a nightmare. What does container world do here? Every application has its own set of libraries in the filesystem defined part of its image, and completely isolated from other processes/application in the system. Voila!! no more deployment nightmares. And setting up that entire applications based on containers has been nicely solved by Docker.4 Docker SuiteDocker comes out with a suite of tools that together help organize, manage and deploy easily containers for real life applications.4.1 Docker EngineDocker engine is the core technology that enables creating, destroying and deploying containers. They connect to Docker Registry to pull/push container images. Docker engine has two parts to it. Docker engine server is a daemon that manages container lifecycle methods and exposes its functionality through a REST endpoint. A Docker command line program exists that can run anywhere and manage containers by connecting to the REST endpoint over the network.4.2 Docker RegistryDocker Registry hosts container Images. These Registries are publicly available through Docker Hub. Additionally, these Registries can be setup inhouse as well. Docker Images are the containers filesystem. So, by defining a method for hosting these Images at a Registry, Docker has made is really easy to share Images across. Versioning of Docker images is also supported. Additionally, Docker Images are being developed inline with opencontainer initiative. https://www.opencontainers.org/4.3 Docker ComposeThis is a utility that helps setting up a multiple container application environment. With Docker Compose, a template can be defined that captures all the dependencies. This can then be passed along to Docker Compose, to create this environment repeatedly and easily everytime. As simple as running ”‘docker-compose up”’.Figure 2: CloudApplications4.4 Docker MachineDocker machine can create virtual machines that can be readily used for container deployment. It uses virtualbox, or other supported drivers https://docs.docker.com/build/builders/drivers/docker/ to create the virtual machine that is docker ready.4.5 KiteMaticKiteMatic is Docker native GUI for working with containers locally on personal machine. It is currently supported on Mac and will support Windows soon. It installs a virtualbox and provisions containers inside a virtual machine locally.4.6 Docker SwarmDocker Swarm supports managing a cluster of machines in a network that is running Docker engine. Swarm agents running on each machine, run a voting algorithm and elect a master node for the cluster. All operations on the cluster are routed to the swarm master node. A distributed kv store like etcd, zookeeper or consul is used to keep the swarm nodes in good health and recover from node failures.5 So what is Kubernetes and Mesos about?Kubernetes and Mesos are higher level software stack used for managing applications on a cluster built over containers.Just like the technology, applications 2 are changing too. We are so used to client-server applications where the applications were small and the servers powerful(consider databases, workflow apps etc). Those class of applications are fast changing. Today, cloud scale applications are another class of applications where the applications are resource hungry and individual servers can hardly satisfy them (think of youtube, twitter, facebook etc). So we should understand that LXC (linux containers) and docker engine play a key part in creating largerFigure 3: Kubernetes StackFigure 4: Mesos Cluster Configurationframeworks. But apart from using container technology as its basis, Kubernetes and Mesos approach cluster utilization in two different ways.Kubernetes 3 understands and manages container based application lifecyles great. While Docker engine can ease out sharing container images, creating and running containers; applications are a slew of containers, that needs to be constantly updated, bugs fixed and new enhancements brought it or downgraded for any critical issues that are found, provide fault tolerance etc. Kubernetes is very good at enforcing application lifecycle management. We could really appreciate the power Kubernetes brings to the table. Google has applied its vast experience in running containers to the design, and it shows. Try comparing Kubernetes with Docker Compose or the concept of PODs, Replication Controller or Services on Kubernetes which are non-existant in Docker. But not all applications are micro services that can easily be packaged as a containers.And that is where Mesos excels! Mesos 4 solves this other class of problems by integrating frameworks http://mesos.apache.org/documentation/latest/ mesos-frameworks/. Each of these frameworks are plugins to the Mesos. And these frameworks teach Mesos to handle new application classes, like mapreduce, MPI etc. Mesos natively only controls cluster membership and failovers.Figure 5: Mesosphere StackThe scheduling is offloaded to frameworks. Mesos slaves inform masters about resource availability, Mesos Master runs an Allocation Policy Module, which determines the framework to offer this resource. Frameworks decide to either accept or reject the offer. If accepted, then they provide details of the tasks to run, and the Mesos Master shares the task information to Mesos Slaves, that continue to run them and provide results and status as necessary.What if one were to integrate these two software stacks together to get the best of both worlds! Mesosphere 5 did just that, they call it Datacenter Operating Systems (DCOS). But that is a story for another day. ReferencesDocker Inc, https://www.docker.comKubernetes, https://kubernetes.ioMesos, http://mesos.apache.org/Linux Containers, https://en.wikipedia.org/wiki/LXCFreeBSD Jails, https://en.wikipedia.org/wiki/FreeBSD jailMesos, http://www.slideshare.net/Docker/building-web-scale-apps-withdocker-and-mesosMesosphere, http://www.slideshare.net/mesosphere/apache-mesos-andmesosphere-live-webcast-by-ceo-and-cofounder-florian-liMesos tech paper, http://mesos.berkeley.edu/mesos tech report.pdfKubernetes, http://www.slideshare.net/wattsteve/kubernetes-48013640Containers for masses, http://patg.net/containers,virtualization,docker/2014/06/05/dockerintro/

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Amazon Aws

A Comprehensive Guide to Cloud Migration Services: Streamlining Your Digital Transformation Journey

In today’s digital age, organizations increasingly embrace cloud technology to drive innovation, enhance agility, and optimize operational efficiency. Cloud migration services facilitate this transition, enabling businesses to seamlessly move their applications, data, and workloads to cloud environments.As a seasoned professional in cloud computing, I understand the intricacies involved in cloud migration and the critical factors that contribute to a successful migration journey.Understanding Cloud Migration ServicesCloud migration services encompass a range of processes, methodologies, and tools to transition an organization’s IT infrastructure and assets to cloud-based platforms. From assessing the current environment to designing a migration strategy, executing the migration plan, and ensuring post-migration optimization, these cloud experts’ services cover the entire spectrum of activities required to achieve a seamless transition to the cloud.Benefits of Cloud MigrationSource: MindInventoryAdopting cloud migration services offers numerous benefits for organizations looking to modernize their IT infrastructure and embrace cloud-native technologies. These include:ScalabilityCloud environments provide on-demand scalability, allowing organizations to scale resources up or down based on fluctuating demand and workload requirements. This is achieved through features such as auto-scaling, which automatically adjusts resource capacity based on predefined metrics such as CPU usage or network traffic.With cloud-based scalability, organizations can handle sudden spikes in traffic or even existing workload without experiencing performance degradation or downtime, ensuring optimal user experience and resource efficiency.Cost EfficiencyCloud migration often leads to cost savings by eliminating the need for upfront hardware investments, reducing maintenance costs, and optimizing resource utilization. Organizations can also benefit from a pay-as-you-go pricing and operating model, where they only pay for the resources they consume, allowing for cost optimization and better budget management.Cloud providers offer various pricing options, including reserved instances, spot instances, and pay-per-use models, allowing organizations to choose the most cost-effective pricing strategy based on their usage patterns and requirements.Flexibility and AgilityCloud offers greater flexibility and agility, enabling organizations to innovate, experiment with new technologies, and respond quickly to market changes. With cloud-based infrastructure, organizations can quickly spin up new resources, deploy applications, and transform services in minutes rather than weeks or months.This agility allows organizations to assess and adapt to changing business needs and requirements, launch new products and services faster, and stay ahead of the competition in today’s fast-paced digital economy.Enhanced SecurityCloud providers invest heavily in robust security measures, offering advanced encryption, identity management, and compliance capabilities to safeguard data and applications. Cloud environments adhere to industry-standard security certifications and compliance frameworks, such as ISO 27001, SOC 2, and GDPR, ensuring data safety, privacy, and regulatory compliance.Cloud providers offer security features such as encryption at rest and in transit, network segmentation, and threat detection and response, providing organizations with a secure and resilient infrastructure to protect against cyber threats and data breaches.Improved PerformanceCloud environments deliver superior performance to on-premises infrastructure thanks to high-speed networks, advanced hardware, and optimized architectures. Cloud providers offer a global network of data centers strategically located to minimize latency and maximize throughput, ensuring fast and reliable access to resources and services from anywhere in the world.Cloud platforms leverage advanced technologies such as SSD storage, GPU accelerators, and custom hardware optimizations to deliver high-performance computing capabilities for demanding workloads such as machine learning, big data analytics, and high-performance computing.Key Considerations for Cloud Migration ServicesBefore embarking on a cloud migration journey, it’s essential to consider several factors to ensure a smooth and successful transition. These include:Assessment and PlanningConducting a thorough assessment of your current IT environment is critical to understanding the scope and complexity of your cloud migration project. This assessment should include an inventory of existing infrastructure, applications, and dependencies and an analysis of performance metrics and utilization patterns. By gathering this data, you can identify potential challenges and risks, such as legacy systems, outdated software dependencies, or performance bottlenecks, which may impact the migration process.Once you have completed the assessment, develop a detailed migration plan that outlines your objectives, timelines, and resource requirements. Consider migration methods (lift and shift, re-platforming, re-architecting), and migration tools and technologies. A well-defined migration plan will serve as a roadmap for your migration journey, helping to ensure alignment with business goals and objectives.Data Migration StrategyData migration is one of the most critical aspects of any cloud migration project, as it involves transferring large volumes of data securely and efficiently to the cloud. Develop a robust data migration strategy that addresses key considerations such as data volume, complexity, and compliance requirements. Consider factors such as data residency, data sovereignty, and data transfer speeds when designing your migration and cloud strategy too.Choose the right data migration tools and technologies to streamline the migration process and minimize downtime. Consider using data replication, synchronization, or backup and restore techniques to transfer data to the cloud while ensuring data integrity and consistency. Implement encryption, data masking, and access controls to protect sensitive data during transit and storage in the cloud.Application CompatibilityEvaluate the compatibility of your applications with the target cloud platform to ensure seamless migration and optimal performance. When assessing compatibility, consider factors such as application architecture, dependencies, and performance requirements. Determine whether applications need to be refactored, rehosted, or replaced to function optimally in the cloud.Use cloud migration assessment tools and application profiling techniques to analyze application dependencies and identify potential compatibility issues. Develop a migration strategy that addresses these issues and mitigates risks associated with application migration. Consider leveraging cloud-native services such as containers, microservices, and serverless computing to modernize and optimize applications for the cloud.Security and ComplianceSecurity and compliance are paramount considerations in any cloud migration project. Implement robust security controls and compliance mechanisms to protect sensitive data and ensure regulatory compliance throughout migration. Consider data encryption, access controls, and identity management when designing your security architecture.Perform a comprehensive security risk assessment to identify potential threats and vulnerabilities in your cloud environment. Implement security best practices such as network segmentation, intrusion detection, and security monitoring to mitigate risks and prevent security breaches. Establish clear security policies and procedures to govern access to cloud resources and data, and regularly audit and assess your security posture to ensure ongoing compliance.Performance OptimizationOptimizing performance is essential to maximizing the benefits of cloud migration and ensuring a positive user experience. Leverage cloud-native services such as auto-scaling, caching, and content delivery networks (CDNs) to enhance application responsiveness and reduce latency. Use performance monitoring and optimization tools to identify and address performance bottlenecks and optimize resource utilization in the cloud.Implement performance testing and benchmarking to evaluate application performance under different load conditions and identify opportunities for optimization. Use performance metrics and monitoring tools to track application performance in real time and proactively identify and address performance issues. Optimize and fine-tune your cloud environment to ensure optimal performance as your workload grows.Types of Cloud Migration ProcessCloud migration services encompass various migration strategies, each suited to different business requirements and business objectives. The three primary types of cloud migration include:Rehosting (Lift and Shift)Rehosting involves lifting existing applications and workloads from on-premises infrastructure and shifting them to the public cloud, without significantly changing their architecture. While rehosting offers quick migration with minimal disruption, it may not fully leverage cloud-native capabilities.Replatforming (Lift, Tinker, and Shift)Replatforming involves minor adjustments to applications or infrastructure components to optimize them for the cloud environment. This approach retains much of the existing architecture while taking advantage of cloud services for improved performance, on-demand support, and cost efficiency.Refactoring (Re-architecting)Refactoring involves fully redesigning applications or workloads to leverage cloud-native services and architectures. This approach often requires significant changes to application code, architecture, or data models to maximize the benefits of cloud migration and modernization.Best Practices for Successful Cloud MigrationFollowing industry best practices and adhering to proven methodologies is essential to an optimal migration strategy to ensure a successful cloud migration journey. Some key best practices include:Start with a Pilot Project: Begin with a small-scale pilot project to test migration strategies, validate assumptions, and identify potential challenges before scaling to more significant migrations.Prioritize Workloads: Prioritize workloads based on business value, complexity, and criticality, focusing on low-risk, non-disruptive migrations initially before tackling mission-critical applications.Establish Governance and Controls: Establish robust governance and control mechanisms to manage the migration process effectively, including clear roles and responsibilities, change management procedures, and risk mitigation strategies.Monitor and Measure Performance: Implement monitoring and performance measurement tools to track migration progress, identify bottlenecks, and optimize resource utilization throughout the migration lifecycle.Train and Educate Stakeholders: Provide comprehensive training and education to stakeholders, including IT teams, business users, and executive leadership, to ensure buy-in, alignment, and successful adoption of cloud technologies.Challenges and ConsiderationsDespite the numerous benefits of cloud migration, organizations may encounter challenges and considerations. These include:Legacy Systems and Dependencies: Legacy systems and complex dependencies may pose challenges during migration, requiring careful planning and coordination to ensure compatibility and continuity.Data Security and Compliance: Data security and compliance remain top concerns for organizations migrating to the cloud, necessitating robust security controls, encryption mechanisms, and compliance frameworks.Performance and Latency: Performance issues and latency concerns may arise due to network constraints, data transfer speeds, and geographic distances between users and cloud regions, requiring optimization and tuning.Cost Management: Cost management and optimization are critical considerations, as cloud spending can escalate rapidly if not monitored and managed effectively. Organizations must implement cost control measures, such as rightsizing instances, optimizing usage, and leveraging reserved instances.Vendor Lock-in: Vendor lock-in is a potential risk when migrating to the cloud, as organizations may become dependent on specific cloud providers or proprietary services. To mitigate this risk, consider multi-cloud or hybrid-cloud strategies to maintain flexibility and avoid vendor lock-in.ConclusionCloud migration services are vital in helping organizations modernize their IT infrastructure, drive innovation, and achieve digital transformation. By following best practices, considering key factors, and effectively addressing challenges, organizations can successfully navigate the cloud migration journey and reap the benefits of cloud computing. As a trusted partner in cloud migration solutions, I remain committed to assisting organizations in their journey toward cloud adoption and empowering them to thrive in the digital era.MSys’ Effective Cloud Migration ServicesAs part of our cloud infrastructure migrations, we provide clients with a smooth transition of business data to cloud services such as Azure Cloud Platform, GCP, AWS, IBM, and other cloud services. Aziro (formerly MSys Technologies) has been helping customers provide reliable and efficient cloud migration services for over 15 years. In addition to these proven and tested procedures, there’s a way we can help you reorganize your processes.FAQs1. What are cloud migration services?Cloud migration services facilitate the transfer of applications, data, and infrastructure from on-premises environments to cloud platforms.2. What are the 6 different cloud migration strategy?The five cloud migration strategy are rehost, migrate, refactor, revise, rebuild, and replace.3. What are the 4 approaches for cloud migration?The four approaches for cloud migration strategy are lift and shift, refactor, re-platform, and rebuild.4. What are AWS cloud migration offerings?AWS migration services include AWS Migration Hub, AWS Database Migration Service, AWS Server Migration Service, and AWS Snow Family.

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An Introduction to Serverless and FaaS (Functions as a Service)

Evolution of Serverless ComputingWe started with building monolithic applications for installing and configuring OS. This was followed by installing application code on every PC to VM’s to meet their user’s demand. It simplified the deployment and management of the servers. Datacenter providers started supporting a virtual machine, but this still required a lot of configuration and setup before being able to deploy the application code.After a few years, Containers came to the rescueDockers made its mark in the era of Containers, which made the deploying of applications easier. They provided a simpler interface to shipping code directly into production. They also made it possible for platform providers to get creative. Platforms could improve the scalability of users’ applications. But what if developers could focus on even less? It can be possible with Serverless Computing. What exactly is “Serverless”?Serverless computing is a cloud computing model which aims to abstract server management and low-level infrastructure decisions away from developers. In this model, the allocation of resources is managed by the cloud provider instead of the application architect, which brings some serious benefits. In other words, serverless aims to do exactly what it sounds like—allow applications to be developed without concerns for implementing, tweaking, or scaling a server.In the below diagram, you can understand that you wrap your Business Logic inside functions. In response to the events, these functions execute on the cloud. All the heavy lifting like Authentication, DB, File storage, Reporting, Scaling will be handled by your Serverless Platform. For Example AWS Lamba, Apache IBM openWhisk.When we say “Serverless Computing,” does it mean no servers involved?The answer is No. Let’s switch our mindset completely. Think about using only functions — no more managing servers. You (Developer) only care about the business logic and leave the rest to the Ops to handle.Functions as a Service (FaaS)It is an amazing concept based on Serverless Computing. It provides means to achieve the Serverless dream allowing developers to execute code in response to events without building out or maintaining a complex infrastructure. What this means is that you can simply upload modular chunks of functionality into the cloud that are executed independently. Sounds simple, right? Well, it is.If you’ve ever written a REST API, you’ll feel right at home. All the services and endpoints you would usually keep in one place are now sliced up into a bunch of tiny snippets, Microservices. The goal is to completely abstract away servers from the developer and only bill based on the number of times the functions have been invoked.Key components of FaaS:Function: Independent unit of the deployment. E.g.: file processing, performing a scheduled taskEvents: Anything that triggers the execution of the function is regarded as an event. E.g.: message publishing, file uploadResources: Refers to the infrastructure or the components used by the function. E.g.: database services, file system servicesQualities of a FaaS / Functions as a ServiceExecute logic in response to events. In this context, all logic (including multiple functions or methods) are grouped into a deployable unit, known as a “Function.”Handle packaging, deployment, scaling transparentlyScale your functions automatically and independently with usageMore time focused on writing code/app specific logic—higher developer velocity.Built-in availability and fault tolerancePay only for used resourcesUse cases for FaaSWeb/Mobile ApplicationsMultimedia processing: The implementation of functions that execute a transformational process in response to a file uploadDatabase changes or change data capture: Auditing or ensuring changes meet quality standardsIoT sensor input messages: The ability to respond to messages and scale in responseStream processing at scale: Processing data within a potentially infinite stream of messagesChatbots: Scaling automatically for peak demandsBatch jobs scheduled tasks: Jobs that require intense parallel computation, IO or network accessSome of the platforms for ServerlessIntroduction to AWS Lambda (Event-driven, Serverless computing platform)Introduced in November 2014, Amazon provides it as part of Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. Some of the features are:Runs Stateless – request-driven code called Lambda functions in Java, NodeJS & PythonTriggered by events (state transitions) in other AWS servicesPay only for the requests served and the compute timeAllows to Focus on business logic, not infrastructureHandles your codes: Capacity, Scaling, Monitoring and Logging, Fault Tolerance, and Security PatchingSample code on writing your first lambda function:This code demonstrates simple-cron-job written in NodeJS which makes HTTP POST Request for every 1 minute to some external service.For detail tutorial, you can read on https://parall.ax/blog/view/3202/tutorial- serverless-scheduled-tasksOutput: Makes a POST call for every minute. The function that is firing POST request is actually running on AWS Lambda (Serverless Platform).Conclusion: In conclusion, serverless platforms today are useful for tasks requiring high-throughput rather than very low latency. It also helps to complete individual requests in a relatively short time window. But the road to serverless can get challenging depending on the use case. And like any new technology innovations, serverless architectures will continue to evolve to become a well-established standard.References: https://blog.cloudability.com/serverless-computing-101/ https://www.doc.ic.ac.uk/~rbc/papers/fse-serverless-17.pdf https://blog.g2crowd.com/blog/trends/digital-platforms/2018-dp/serverless-computing/ https://www.manning.com/books/serverless-applications-with-node-js

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AWS Infrastructure Automation: Streamlining Cloud Management

I’ve always been fascinated by cloud computing’s potential to transform businesses. Amazon Web Services (AWS) stands out as a leader among the many cloud service providers, offering a robust platform for building and managing applications. However, managing infrastructure on AWS can be complex and time-consuming. This is where AWS infrastructure automation comes into play, simplifying cloud management and enhancing efficiency.Source: SpectralThe Need for Automation in Cloud ManagementManual management of cloud infrastructure is labor-intensive and highly prone to errors. Manual configuration is particularly error-prone and can lead to configuration drift. As businesses scale, the complexity of their infrastructure grows exponentially, making manual oversight increasingly untenable. Manual processes, such as manual configuration, deployment, and support, are unreliable and inefficient, further underscoring the need for automation. This is where AWS infrastructure automation becomes essential.Automation significantly reduces human error and ensures consistency across deployments. Using tools like AWS CloudFormation, Elastic Beanstalk, and Systems Manager, businesses can automate routine tasks such as provisioning, configuring, and scaling resources, thereby maintaining a stable environment with minimal intervention.Defining AWS Infrastructure AutomationAWS infrastructure automation leverages various tools and scripts to manage and orchestrate AWS resources automatically, simplifying the complex and often error-prone tasks associated with cloud management. By utilizing services such as AWS CloudFormation, Elastic Beanstalk, and OpsWorks, we can define our infrastructure as code and automate infrastructure provisioning, configuration, and scaling. Infrastructure deployment automation tools facilitate the adoption of Infrastructure as Code practices, making the setup and monitoring of AWS infrastructure more efficient.Moreover, automation ensures that our infrastructure remains desired without requiring manual intervention. Tools like AWS Systems Manager provide ongoing maintenance and compliance capabilities, automatically applying updates, patches, and security configurations as needed. Additionally, services such as Auto Scaling can dynamically adjust resource allocation based on real-time demand, optimizing performance and cost-efficiency.Key Benefits of AWS Infrastructure Automation1. Enhanced Efficiency and ProductivityApplication deployment significantly accelerates resource deployment and management, transforming processes that once took hours or even days into tasks that are completed in minutes. This drastic reduction in time requirements enables teams to minimize downtime and effectively meet project deadlines. With routine operations handled automatically, teams can redirect their focus toward more strategic and innovative initiatives.2. Consistency and ReliabilityUtilizing automation scripts ensures that resources are consistently provisioned and configured uniformly every single time. This consistency is critical for maintaining the integrity of your infrastructure, as it virtually eliminates the risk of configuration drift, where systems gradually diverge from their intended state. By maintaining uniformity across all deployments, we enhance the reliability of our systems, ensuring that they perform predictably and meet compliance standards.3. Cost ManagementAutomation is pivotal in optimizing cost management by dynamically adjusting resource allocation based on real-time demand. Through services like AWS Auto Scaling, resources can be scaled up during peak usage periods and scaled-down during low-demand times, ensuring optimal utilization. This dynamic scaling mechanism ensures that we only pay for the resources we need at any moment, avoiding unnecessary expenditures.Core AWS Services for Infrastructure Automation1. AWS CloudFormationAWS CloudFormation allows us to define our infrastructure as code (IaC), offering a powerful approach to managing AWS resources. By creating templates in JSON or YAML, we can describe and provision all the infrastructure resources of our cloud environment—from EC2 instances and S3 buckets to IAM roles and VPC configurations. This infrastructure-as-code methodology simplifies the setup process, enabling us to easily deploy consistent environments across multiple stages (development, testing, production).2. AWS Elastic BeanstalkElastic Beanstalk is a versatile, user-friendly service designed to deploy and scale web applications and services. The beauty of Elastic Beanstalk lies in its simplicity: after uploading our code, the service takes over the heavy lifting of deployment. It automatically handles capacity provisioning, load balancing, and auto-scaling, ensuring the application remains responsive under varying traffic loads. Additionally, it supports a wide range of platforms, including Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker, making it a flexible choice for diverse development needs by leveraging familiar programming languages.3. AWS OpsWorksOpsWorks offers a robust configuration management service that utilizes Chef and Puppet, two popular automation platforms. These tools allow us to define our infrastructure’s desired state and configuration in a declarative and repeatable way. Through OpsWorks, we can automate application deployments, manage server configurations, and manage infrastructure, ensuring that our infrastructure remains consistent and compliant with predefined policies. OpsWorks Stacks and OpsWorks for Chef Automate provide different layers of abstraction and control, catering to high-level and granular management needs.4. AWS CodePipelineAWS CodePipeline is a dynamic continuous integration and continuous delivery (CI/CD) service that automates the entire release process. It orchestrates the build, test, and deploy phases, ensuring that every change is rapidly and reliably propagated through all application lifecycle stages. CodePipeline integrates seamlessly with other AWS services and third-party tools, providing flexibility and customization to meet specific workflow requirements.Best Practices for AWS Infrastructure AutomationVersion Control Everything: Our infrastructure code should be stored in a version control system like application code. This allows us to track changes, collaborate with team members, and roll back to previous states if necessary.Modularize Your Infrastructure Code: Breaking down our infrastructure code into reusable modules makes it easier to manage and scale. Tools like Terraform support this modular approach, allowing us to create small, reusable components that can be combined to form complete environments.Use Tags and Naming Conventions: Consistent tagging and naming conventions make managing and organizing resources easier. Tags can identify resources by environment, owner, or project, simplifying monitoring and cost allocation.Implement Continuous Integration and Continuous Deployment (CI/CD): By integrating infrastructure code into our CI/CD pipeline, we can automatically test and deploy changes, reducing the risk of errors and ensuring that our environments are always up-to-date.Monitor and Log Everything: Monitoring and logging are essential for maintaining visibility into our automated infrastructure. AWS provides services like CloudWatch and CloudTrail to monitor performance, log activity, and alert us to any issues.Real-World Use Cases of AWS Infrastructure AutomationAuto-Scaling Web ApplicationsOne of the most common use cases for AWS infrastructure automation is auto-scaling web applications. By utilizing services like Elastic Load Balancing (ELB) and Auto Scaling, we can automatically adjust the number of instances based on real-time traffic patterns, ensuring that our applications maintain optimal performance during peak usage and efficiently scale down during off-peak times to save costs. ELB distributes incoming application traffic across multiple targets, such as EC2 instances, containers, and IP addresses, enhancing fault tolerance and availability.When combined with Auto Scaling, we can set predefined scaling policies that trigger adding or removing instances based on metrics such as CPU utilization or request rate. This dynamic adjustment ensures that users experience consistent and responsive applications and optimizes resource utilization, reducing operational costs.Disaster RecoveryAutomation is critical in disaster recovery, enabling swift and reliable responses to unforeseen events. Through tools like AWS CloudFormation and AWS Backup, we can automate creating and managing backup copies for our critical data and infrastructure components. AWS CloudFormation allows us to define and deploy infrastructure templates that can be quickly replicated in different regions, ensuring business continuity.In a disaster, the failover process can be automated to minimize downtime, seamlessly shifting workloads to backup instances. AWS Backup simplifies and centralizes backup management by creating and managing backups across various AWS services, ensuring that data is regularly saved and easily recoverable. Automating these processes ensures that our systems are resilient and can recover rapidly from disruptions, protecting data integrity and service availability.DevOps and Continuous DeliveryDevOps practices rely heavily on automation to streamline the development, testing, and deployment processes, enhancing collaboration and efficiency. AWS CodePipeline and AWS CodeDeploy are key services facilitating continuous integration and delivery (CI/CD). AWS CodePipeline automates the end-to-end release process, orchestrating the building, testing, and deploying code changes seamlessly across various environments.AWS CodeDeploy automates the deployment of applications to various compute services such as EC2 instances, Lambda functions, and on-premises servers. It supports blue/green and rolling updates, minimizing downtime and reducing the risk of deploying changes. By integrating these tools into our DevOps workflows, we can accelerate the delivery of high-quality software, respond more quickly to market demands, and foster a culture of continuous improvement.Challenges and Considerations in AWS Infrastructure Automation1. Complexity and Learning CurveWhile automation offers many benefits, it also introduces complexity. Learning to use AWS automation tools effectively requires time and effort, and implementing automation at scale can be challenging.2. Managing State and DependenciesManaging the state of our infrastructure and its dependencies can be complex, especially in dynamic environments. It is crucial to ensure that our automation scripts accurately reflect the desired state and handle dependencies correctly.3. Balancing Automation and ControlFinding the right balance between automation and manual control is essential. Over-automation can lead to a loss of visibility and control, while under-automation can limit efficiency and scalability.Future Trends in AWS Infrastructure Automation1. Increased Adoption of AI and Machine LearningArtificial intelligence (AI) and machine learning (ML) are revolutionizing infrastructure automation by enabling more intelligent and efficient management of cloud environments. AWS offers services integrating AI and ML capabilities, such as AWS SageMaker and AWS AI. These services can automate complex tasks like predictive scaling, where the system anticipates future resource needs based on historical data and usage patterns.This proactive approach ensures optimal performance and cost-efficiency without manual intervention. Additionally, AI and ML can be used for anomaly detection, identifying unusual behavior or potential security threats in real time. By leveraging these advanced technologies, we can create a more resilient and adaptive infrastructure that can respond to changes dynamically, reducing downtime and enhancing overall reliability.2. Serverless ComputingServerless computing fundamentally transforms how we approach infrastructure management by abstracting away the underlying server infrastructure. Services like AWS Lambda allow us to execute code in response to events without provisioning or managing servers. This simplifies the development and deployment process and enhances scalability and cost-efficiency.Furthermore, serverless computing integrates seamlessly with other AWS services, enabling the creation of highly modular and event-driven applications. This paradigm shift towards serverless architecture empowers developers to innovate faster and operate more efficiently in a cloud-native environment.3. Infrastructure as Code 2.0Infrastructure as Code (IaC) is evolving, bringing forth a new generation of tools and frameworks that offer enhanced automation capabilities and greater flexibility. Tools like Pulumi and the AWS Cloud Development Kit (CDK) are at the forefront of this evolution. Unlike traditional IaC tools that rely primarily on domain-specific languages (DSLs) such as JSON or YAML, these new tools support higher-level programming languages like TypeScript, Python, and Go.Pulumi, for example, provides a unified programming model for configuring cloud resources across multiple providers, enabling more sophisticated and cross-platform automation. Similarly, AWS CDK offers high-level abstractions and reusable components, making it easier to build and maintain complex cloud architectures. The emergence of these advanced IaC tools marks a significant step forward in infrastructure automation, allowing for more powerful, flexible, and maintainable solutions.Conclusion: Embracing the Future of Cloud ManagementAs we navigate the complexities of modern cloud environments, AWS infrastructure automation stands out as a critical enabler of efficiency, scalability, and reliability. By leveraging the power of AWS automation tools, we can streamline cloud management, reduce costs, and drive innovation. This automation enhances our ability to deploy and manage resources rapidly and ensures that our infrastructure remains secure and compliant with industry standards. Ultimately, embracing AWS infrastructure automation positions us to meet the demands of an ever-evolving digital landscape with agility and confidence.

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How Can Aziro (formerly MSys Technologies) Expertise Help You with SaaS, PaaS, and IaaS

Cloud computing has revolutionized how we provide IT software and infrastructure. Today, many software companies are interested in providing their applications and services in the form of a cloud service rather than packaging their software and licensing it out to customers. There are a number of advantages to this type of service delivery model.Customers have access to applications and data from anywhere. Just a direct connection to the Internet is necessary for a cloud-based application to run. Data is also easily accessible over a network. Data would not be confined to a simple computer system or the internal network of an organization. Hence, access is easy from any location.Cost will come down in this model. You no longer need advanced hardware resources to run an application. A simple thin client can access a cloud-based application from anywhere. The hardware resources to run the application resides in the cloud, and it can be used to profitably run the application on any number of systems. The thin client can include a monitor, I/O devices, and just enough processing power to run the middleware that accesses the application from the cloud.Cloud computing systems are highly scalable. You don’t need to worry about adding additional hardware to run an application. The cloud takes care of all of that.Servers and storage devices take up a lot of physical space. Renting physical space can cost quite a lot of money for an organization. You can, with the cloud, simply host your products and software on someone else’s hardware so as to save a lot of space on your end.Streamlined hardware infrastructure of the cloud will have fewer technical support needs.Since cloud computing takes advantage of a grid computing system in the back end, the front end doesn’t really need to know the infrastructure to run any application of any size. In simpler terms, the advanced calculations a normal computer would take years to complete can be done in seconds through a cloud-computing platform.Cloud ModelsCloud computing takes three major forms: SaaS, PaaS, and IaaS. They are expanded as Software, Platform, and Infrastructure as a Service. In the case of SaaS, users are given access to software applications and associated databases. The installation and operation of the software is done completely from the cloud, and the access through authentication is done from a thin client.Cloud provides the load balancers required to run the application by distributing the work across multiple virtual machines. This complex back end is not even visible to the end user, who simply sees the running application through a single access point. The SaaS applications can be in subscription model, in which you pay a monthly or yearly fee to get access to the application.In the PaaS model, the cloud provides a computing platform that includes typically an operating system (Windows, Mac OS X, Linux, etc.), programming languages required for software development, database, and web servers. These entities are all stored in the cloud. Instances of the PaaS model include Microsoft Azure and Google App Engine.In the IaaS model, you have as many virtual machines as you need on the cloud. A hypervisor, such as VMware ESXi, Oracle VirtualBox, XenServer, or Hyper-V are provided through the IaaS platform. Additionally, virtual machine disk image library, raw block storage, object storage, firewalls, load balancers, virtual LANs, etc., are all provided by the IaaS model. This helps any organization successfully deploy their applications on the cloud. The most popular IaaS provider is probably Amazon Web Services.Deployment ModelsThree types of deployment models exist in the cloud architecture. They are private cloud, public cloud, and hybrid cloud. Private cloud is managed and operated by a single organization internally. Significant amount of virtualization is required for a private cloud deployment, and that can increase the initial investment required. However, when deployed correctly, a private cloud could be highly profitable for any organization.Public cloud is rendered to the public as a service. For instance, Amazon AWS, Microsoft Azure, etc., are provided to the public to use and deploy their applications and infrastructure. This type of architecture requires you to analyze the security and communication concerns of the cloud.In the case of hybrid cloud, as the name implies, both private, community, and public cloud deployments could be there. In hybrid cloud systems, the advantages of both types of systems may be there. Various deployment models are available in the case of hybrid cloud: for instance, a company can store sensitive client data in private cloud architecture while deploying business intelligence services provided by a public cloud vendor.MSys’s Cloud ExpertiseAziro (formerly MSys Technologies) and its subsidiary company Clogeny have done several cloud-based projects in the past. We have analyzed the current infrastructure of clients, and provided a proper road map to cloud deployment. In implementation, we have taken care of the complete design of the cloud computing model, building test environments to check the validity of the design, and migration of apps and data to go live. We also provide fully functional cloud support through transition plans, service review, and service implementations.We have worked with some of the major cloud service providers in the industry including Amazon Web Services, Microsoft Azure, Rackspace, HP Cloud, Google Cloud, OpenStack, Salesforce, Google Apps, Netsuite, Office 365, etc. We have also helped organizations take advantage of their data by providing big data services. Leading companies in storage, server imaging, and datacenter provisioning have been our clients since our inception in 2007. In private and public cloud deployments, a few of our clients include Datapipe, Instance, and Netmagic.Our cloud-based product is known as PurpleStrike RT, which is a load-testing tool that utilizes Amazon’s EC2 platform.ConclusionCloud computing may prove to be the most important technology for future’s IT deployments. Already many companies have moved to the cloud. Many more are in the process of slowly transitioning to the cloud.

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Beyond Budgets:Unraveling the Five Pinnacles that Set Apart Cloud Cost Management and FinOps

Cloud cost management and FinOps are frequently used interchangeably, yet they encompass distinct nuances. Understanding Cloud Cost Management Cloud cost management entails the systematic tracking, optimization, and governance of cloud computing expenses. This practice revolves around the identification and elimination of superfluous cloud resources, right-sizing existing resources, and optimizing overall cloud utilization. Decoding FinOps As defined by finops.org, FinOps stands as a progressive discipline and cultural practice within cloud financial management. It empowers organizations to extract maximum business value by fostering collaboration among engineering, finance, and business teams in making data-driven spending decisions. The essence of FinOps lies in its role as a dynamic enabler of informed financial strategies in the cloud environment. Within FinOps, individuals from diverse backgrounds, including Engineering, Finance, Business, and executives, collaborate to establish a unified team. The primary objective of this team is to intricately optimize cloud costs. FinOps teams recognize that effective management of cloud expenditure goes beyond mere cost reduction; it entails ensuring that cloud resources align seamlessly with the organization’s overarching business goals. What Makes It Inadvisable to Use these Terms Interchangeably? While Cloud Cost Optimization concentrates on expense reduction, FinOps adopts a more expansive approach, covering not only cost optimization but also financial management elements such as budgeting, forecasting, and insightful reporting. Commencing with cost optimization is undoubtedly a prudent step, but embracing FinOps provides a comprehensive and enduring strategy. However, confusion frequently arises due to the interchangeable use of these terms, potentially leading organizations to believe they are practicing FinOps when deeper optimization opportunities remain unexplored. Now, let’s delve into the five key distinctions between cloud cost management and FinOps: Scope: Technical Dimension Vs Comprehensive Approach Cloud cost management predominantly centers around the technical facets of cloud expenditure. This includes tasks such as resource tagging for cost tracking and management, right-sizing resources, and the identification and termination of unused resources. On the contrary, FinOps embraces a more comprehensive approach to cloud financial management. It not only addresses the technical dimensions of cloud spend but also incorporates business and operational aspects. FinOps teams collaborate with business stakeholders to comprehend resource utilization, identifying opportunities to optimize cloud expenditure while preserving business agility. Additionally, FinOps is utilized to formulate and implement policies and procedures for cloud cost optimization, as well as to automate cloud cost management, encompassing monitoring, forecasting, and governance. In essence, while cloud cost management deals with the “how” of financial management, FinOps delves into the “why” and the “what.” Goals: Cost Savings vs. Cost Optimization Cloud cost management centers on reducing cloud spend, whereas FinOps is geared towards optimizing cloud spend to align with business goals. Cloud cost management primarily focuses on identifying and eliminating unnecessary cloud resources. In contrast, FinOps not only considers the removal of redundant resources but also evaluates how cloud resources can enhance business agility and reduce time to market. In summary, cloud cost management is primarily about saving money, whereas FinOps is about achieving cost savings while concurrently enhancing overall business performance. Metrics: Financial Investment Vs Holistic Overview Cloud cost management traditionally centers on financial metrics, such as total cloud spend and cost per unit of output. This emphasis stems from the overarching goal of reducing cloud expenditure. However, a sole focus on financial metrics may lead organizations to make decisions that inadvertently hinder their business agility. Conversely, FinOps adopts a more holistic perspective, incorporating non-financial metrics such as user satisfaction and business agility. FinOps teams recognize that cloud spend is not solely about cost reduction but also about ensuring that cloud resources contribute effectively to the organization’s business goals. For instance, a FinOps team might advise an organization to invest in a slightly more expensive cloud service that significantly enhances application performance. This might increase cloud costs, but it would concurrently elevate user satisfaction and business agility. In summary, while cloud cost management provides a solid starting point, FinOps emerges as a more comprehensive approach, facilitating organizations in optimizing cloud spend in alignment with their overarching business goals. Culture: Silos vs. Collaboration In the realm of cloud cost management, a common practice involves a siloed approach, where the responsibility for managing cloud costs is relegated to a single team or department. For instance, the IT department may take charge of overseeing cloud costs, while the finance department assumes the role of approving cloud spending. This segregation often results in disjointed efforts, with different teams inadvertently working at cross-purposes and lacking a comprehensive understanding of how cloud costs impact the organization as a whole. Contrastingly, FinOps represents a collaborative approach that engages all stakeholders within the organization in cloud cost management. This inclusive approach involves teams from various domains, such as engineering, operations, and finance. By working collectively, these cross-functional teams can efficiently identify and implement cost-saving measures that align with the organization’s overarching business goals. At the heart of this distinction lies a cultural shift: FinOps ensures a collaborative approach where everyone shares ownership of cost management, fostering a unified and informed effort across the organization. Approach: Reactive vs. Proactive Cloud Financial Management Cloud cost management teams primarily respond to cost issues post-occurrence, delving into investigations after an increase in the cloud bill has been observed.Conversely, FinOps teams proactively avert potential cost challenges by implementing preemptive measures. For instance, they may deploy a cloud cost management tool designed to automatically alert the team when cloud spending approaches a predefined threshold. This proactive approach ensures timely interventions, preventing cost issues from arising in the first place and promoting a more streamlined and cost-effective cloud financial management strategy.

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