devopsy.kinsta.cloud

Category: Cloud Computing

  • The Benefits of a Distributed Cloud

    The Benefits of a Distributed Cloud

    The way applications are created has changed dramatically in just a few short years. It’s now all about rapid assembly and integration; applications built using microservices and containerized. Containers and the cloud have certainly been the catalyst for this progress and will continue to be the infrastructure on which developers create new and innovative applications. 

    As workloads are moving to the cloud, however, more and more businesses are realizing they need a cloud that can be rapidly adapted to their specific needs. Computing environments may be a blend of server types: On-premises, bare metal, colocated and distributed across multiple continents. No single cloud architecture can offer consistently exceptional application performance for all users.  

    Between hybrid, on-premises, multi-cloud, colocated, centralized and distributed clouds, it can be hard to keep all the terminology straight. What are the differences between these cloud architectures? Why use one rather than the other? In this article, we’ll focus on just one of these: The distributed cloud. 

    What is a Distributed Cloud?

    As opposed to the large public cloud where all computing is done in a central location, a distributed cloud consists of a system of servers that are not all in the same place—even though they are managed through a single cloud provider. The servers in a distributed cloud can be actually anywhere in the world. This allows for computing to be done closer to the end user, which improves the user experience in a multitude of ways.

    What Are the Advantages of Using a Distributed Cloud?

    Below are six of the key benefits of using a distributed, rather than a centralized, cloud.

    One Size Does Not Fit All

    Computing environments may be a blend of server types: On-premises, bare-metal, colocated and distributed across multiple continents. Cloud providers need to offer flexibility to customize a cloud for their end users and their business needs.

    Data Regulation Compliance

    Many countries have specific compliance requirements for their citizens’ data and do not allow for personal/financial data to be hosted outside of their borders. Thus, having a distributed server within those countries alleviates that issue. 

    Reduced Latency

    In a distributed cloud model, servers can be placed in a wide array of locations, including in an edge cloud. When servers are placed closer to end users as opposed to in a centralized location, data does not need to travel as far to get back to the server. 

    Improved CDNs

    A distributed cloud can be used to deploy content delivery networks, or CDNs, to speed up content and service delivery. Heavy content (e.g. videos) can be stored and delivered by the distributed cloud closer to end users, which enhances the user experience.

    Network Resilience

    Network connectivity is always a worry for cloud providers. If their system goes down, none of the user’s workloads will run. In a distributed cloud system, however, the network is at a reduced risk of failure because if the system crashes, cloud services can reside in a local subnet.

    Location Flexibility

    A distributed cloud can always become more distributed. More locations can be added to the network, broadening the global compute zones available within that cloud. Companies that want to reach users in specific locations around the world can use a distributed cloud to reach them.

    Changing How People Think About Cloud Computing

    To address the demand for versatility, a new type of cloud has emerged: The unified distributed cloud (UDC), in which workloads can run in thousands of locations anywhere on earth. Such a cloud connects to existing infrastructure around the world via one API. Businesses can enjoy the benefit of running workloads in multiple locations without needing to maintain any of the distributed infrastructure. From a single UI, users pick an existing data center to send their workloads to and, within minutes, begin deploying. 

    A UDC transforms heterogeneous infrastructure into a homogeneous cloud computing platform, which can then be leveraged to support the delivery of cloud services in proximity to end users. It is designed to be interoperable with any private, hybrid cloud or multi-cloud architecture. As a result, enterprises can create an optimized cloud computing strategy, taking advantage of existing and available infrastructure in the location—or locations—of their choosing.  And because it sits on existing infrastructure, it doesn’t require any additional capital expenditure.

    As opposed to the traditional cloud model, the UDC can change the way people think about the public cloud. While the large public cloud providers benefit from economies of scale, a distributed cloud takes advantage of the economies of locality and distribution and thus has the flexibility to handle emerging location-dependent apps, such as the new wave of internet-of-things applications.

  • A Guide to Cloud Migration Trends and Strategies

    A Guide to Cloud Migration Trends and Strategies

    For several years, we have witnessed widescale cloud adoption as a software infrastructure growth and maintenance strategy. Spending on cloud application services (SaaS) continues to grow as monolithic applications are replaced by microservices-based apps and monoliths become relics of the past. In 2021 alone, companies spent $410.9 billion on public cloud services, and Gartner expects this number to rise by 20.4% in 2022 to reach $494.7 billion. But as this movement continues to evolve, engineering leaders preparing their cloud migration strategy must be up to speed on the latest key trends.

    Is Migrating to the Cloud Cost-Effective?

    For companies migrating to the cloud now, the process is no longer a simple transition from on-premises to remotely hosted servers. Cloud service providers now offer a wide variety of options, and companies run the risk of overspending in the cloud marketplace.

    A lack of clarity of their business and product needs or submission to shiny object syndrome can drive companies to spend on non-essential services, especially during migration. It is easy to fall into this trap; companies only realize it after they have committed and try to undo the damage by reversing the process.

    Although many public cloud providers offer pay-as-you-go pricing, companies often purchase more services than they use. When companies are unclear about their objectives, such expenditure is more extravagant than the utility. This awareness of cloud spending has encouraged companies to take stock of their needs and expenses, and when they do not add up, to consider partly shifting back to on-premises.

    But Isn’t On-Premises a Thing of the Past?

    Not yet, but gone are the days of mindlessly unloading entire infrastructures into the cloud. Increasingly, companies are aware of the costs of pulling their data from the cloud.

    For many, security and control concerns motivate them to keep data on-premises. The public cloud has its benefits, but private storage has its place, too, especially for some components of your software. All in all, on-premises is here to stay, as companies continue to acknowledge and appreciate its value despite their reliance on public cloud environments.

    Why Do Companies Choose Cloud Migration in 2022?

    Cloud technologies can potentially deliver faster and better-performing experiences to end users, while innovations are giving rise to new services that cloud vendors can capitalize on. Various use cases are surfacing as companies understand the cloud better and see its potential. They are pushing the boundaries on how they can use the cloud, and cloud service providers are keeping track of the changing nature of the demand.

    For example, cloud-based gaming platforms like Amazon Luna are seeing significant growth. The cloud is also of great value to artificial intelligence and machine learning efforts, and these are often intertwined.

    The Great Resignation phenomenon also drives some companies towards the cloud. Although some knowledge is needed when moving to the cloud, cloud services offer automation and require less employee supervision in the long term.

    The COVID-19 pandemic has also been a catalyst for accelerating cloud adoption, making resiliency a priority. Companies can stay afloat in an emergency if their workloads are moved to the cloud. It comes at a cost, sure, but allows companies to outsource time-consuming responsibilities and focus resources elsewhere. While this was most significant in 2020 and 2021, this logic remains relevant.

    Cloud computing is also helping companies improve performance, efficiency and scalability. In addition to AI, the cloud will be instrumental in the development of more powerful augmented and virtual reality apps.

    Approaches Defining Cloud Migration Today

    The possibility of these approaches or facilities also motivates companies to migrate to the cloud:

    Containerization: The process of compiling and storing a service, along with its dependencies, in a container. Due to their small size, multiple containerized applications can run on a server, allowing for easier and cheaper shipping of the service. According to CNCF’s 2021 Annual Survey, containerization is now a mainstream practice, and Kubernetes, for instance, is a heavyweight in this domain, with 96% of companies employing or evaluating it.

    Security: In Q1 of 2022 alone, 90% of data breaches had their origins in cyberattacks. Mindful of this alarming trend, companies are factoring security concerns into their cloud adoption strategies. We are also witnessing a shift in businesses’ approach to security via DevSecOps: Incorporating security as a continuous practice from the beginning of the software development life cycle instead of relegating it to the back-burner until the last moment. Additionally, frameworks like secure access service edge (SASE) and customized cloud disaster recovery strategies are becoming essential elements of cloud adoption.

    Sustainability: Sustainability is becoming a key component in most business models. Companies are eager to adopt practices and models that reduce their carbon footprint. This impetus is also emerging from business partners and investors who are beginning to employ sustainability as a critical factor when deciding which companies to work with. When a cloud migration is planned carefully, chances are that you will retire certain services in your infrastructure and make decisions about what to migrate and what to retain. By optimizing your migration strategy, you are likely to only run and pay for the services you need, ensuring that your energy expenditure is under control.

    Edge computing: Edge computing, a $176 billion market in 2022, emphasizes the importance of building data centers locally; i.e., closer to where they are needed for storage and computational purposes. It solves any bandwidth and latency issues. Improved security is another added benefit of this practice. Edge computing has a bright future as it attempts to compensate for some of the pitfalls of using centralized servers in the cloud.

    Cloud-native applications: Cloud-native applications are easier to work with on the cloud, as they are designed and built on the cloud itself, not rearchitected to ensure compatibility with cloud services. When compatibility is not a concern, they can leverage various benefits offered by cloud services. As a result, scalability, flexibility and resilience are built into these applications. With cloud adoption, companies are increasingly in favor of cloud-native applications. This subsequently informs their migration strategy as they decide which services to retire, rearchitect or build anew once the actual migration is complete.

    How Does the Hybrid Cloud Fit In?

    Hybrid computing is on the rise as it leverages the public and the private cloud to deliver maximum benefit to companies with little to no compromise. The public cloud offers scalability, flexibility and speed, while the private cloud provides cost-effectiveness, security and compliance with regulations. While sensitive data can rest on the private cloud, frequently accessed data can be stored in public servers like AWS and Google Cloud. Investing in a hybrid cloud strategy from the point of migration itself can go a long way in giving companies access to the best of both worlds.

    Similar to a hybrid cloud environment, a multi-cloud strategy where companies distribute workloads across multiple clouds put some control into the company’s hands and ensures additional flexibility. By working across cloud services, companies can pick and choose which services are most compatible with their application’s components. These can include services offered by different cloud providers.

    Cloud Providers Seeing Growth, and What They are Doing Differently

    Serverless cloud environments: Cloud vendors like Amazon, Microsoft and IBM are pushing serverless cloud services. Although these continue to rely on servers (despite the name), companies don’t rent servers or pay fixed charges. Instead, the storage and bandwidth infrastructure scales with the software as and when it requires it. Companies do not need to concern themselves with technicalities and can focus on innovation and improving their existing applications. An added advantage is the provision of safe testing environments that encourage developers to tinker with cloud services and develop solutions for potential failures or outages. Serverless cloud solutions are also beneficial for smaller companies that need not invest large amounts of capital to ensure growth.

    Partnerships: To meet the soaring demand for cloud services, partnerships among cloud providers are also on the rise. By partnering with other service providers, companies can offer more services by leveraging the resources and reputations of one another while strengthening their competitive edge in the cloud market.

    Industry optimization: Cloud adoption is not limited to software companies. Businesses across industries like healthcare, finance and retail are migrating their infrastructures to the cloud. This variety in demand has encouraged providers to customize their services to meet the specific requirements of each industry. Often, these include regulatory compliance needs in these sectors.

    The cloud is only getting bigger and better. You can develop a well-curated transition strategy with the knowledge of current cloud migration trends. Additionally, identifying your requirements at an early stage will go a long way in leveraging the cloud to your advantage.

  • API Gateway Vs. Service Mesh: What’s the Difference?

    API Gateway Vs. Service Mesh: What’s the Difference?

    In the average microservices architecture, app programs trade the stability and rigidity a call stack offers for the network’s flexibility. Consequently, latency, security and traceability issues that were previously absent become a service call concern. 

    Service mesh is the resulting solution to eliminate these issues and allow developers to focus on more important business solutions. The caveat is the functionality overlap that exists between a service mesh and an API gateway. But while the two are similar, there are also key differences between both options. Here’s what you need to know.

    Defining a Service Mesh

    A service mesh is a comprehensive architectural pattern set designed to deal with enterprise concerns like instability, debugging and security. These concerns arise when a team moves from a call stack to network calls. 

    For instance, a function call via a call stack recognizes the constant availability of the requested function. On the other end of the equation, a network call doesn’t offer this functionality. 

    A service mesh is the preferred option because it assists the system’s client endpoint in managing network instability. The primary method for solving this network instability is frontrunning retries transparent from the client app’s viewpoint. 

    The service mesh also assists the server’s endpoint by rerouting incoming requests to the server node that’s best able to deal with the incoming request. The choice of server node is a function of previously determined policies for routing incoming traffic.

    The ideal service mesh is installed with two layers: The control plane and the data plane. The latter is a proxy for any connection’s server and client endpoints. 

    The data plane also enforces policies from the former while running operation metrics to a monitoring tool. Conversely, the control plane layer manages all attending service policies alongside the data plane’s operation. 

    service mesh

    Image Source

    Key Features of a Service Mesh

    The average service mesh has a number of primary features. 

    But there are a few things that bear mentioning. Say your app development team is working on a small business phone system. This particular service implementation doesn’t need every feature listed below. It depends on your team’s specific needs and traffic setup.

    Traffic Routing

    This feature enables the service mesh to route requests based on preset configuration or a predetermined policy. The system may prioritize traffic from specific client applications. Alternatively, a service mesh can re-route traffic to different service versions for:

    • A/B testing
    • Canary release
    • Service versioning

    Observability

    Service mesh implementations feature proxies that record service calls for individual clients and services. This feature takes the manual burden of the call-logging process away from the developers. 

    Plus, teams can leverage downstream analysis and monitoring tools to report on system availability and overall performance. These monitoring tools also provide a framework for basic tracing across all call chains. 

    The observability capabilities of a service mesh extend beyond the above. For example, some coding work can allow developers to improve call chain monitoring to allow for accurate tracing for enterprise business transactions.  

    Common service mesh observability features include: 

    • Latency, error rate and throughput alerts
    • On-demand service dashboards and graphs depicting the connection between individual services
    • Tracing the journey a business transaction or request makes through the service mesh

    Image Source

    Security Policies

    An application with multiple independent services has a huge attack surface. Essentially, each independent service is a vulnerable entry point that requires protection. A service mesh has proxies on both the server and client endpoints to secure any communication between both terminals. 

    A service mesh also improves security by eliminating the dependence on developers to manually program security into every service. Instead, the server proxies will handle authorization, authentication and encryption for each independent service. The resultant effect is a zero-trust security framework.  

    Identity

    A service mesh manages who can access individual services. It also maintains a real-time log of stakeholders accessing each service and when they did so. The system validates identity through JSON Web Tokens (JWTs) while allowing authorization depending on the requesting service and the stakeholder. 

    Encryption

    Compliance, security and data protection are key considerations. Well, communication between all services in a service mesh is fully encrypted. The control plane is responsible for certificate management functionality including certificate rotation and generation. 

    Furthermore, a service mesh uses mutual TLS where both server and client endpoints whitelist the certificates that can operate on the other side of any connection. A service mesh provides robust mutual TLS authentication, allowing for seamless system authentication and encryption. 

    Resilience

    This feature defines the ability of a service mesh to insulate developers in scenarios where the principal service function goes offline. In some instances, the proxy may follow an alternative service path or switch to a backup framework. 

    For illustration, streaming giant Netflix has a personalized user recommendation feature that suggests titles to its users. If this service goes offline, a service mesh system can ensure a switch to a default recommendation feature with zero personalization. Only when this backup fails will the system return an error code. 

    A service mesh assures developers that when a service fails, the proxy has done all it can to manage communication errors. In some cases, the mesh can ensure optimal performance by switching to a different service with the lowest latency.

    Examples of configurable resilience patterns for a service mesh include 

    • Circuit breaker patterns
    • Rate limiting
    • Retry policies

    Another illustration of a service mesh’s resilience is the ability to build chaos engineering capabilities. The service mesh can inject itself into the endpoints within the network, providing the observability required to monitor a chaos test. 

    Image Source

    What an API Gateway Entails

    Whether the team is working on contract management software for small business or an expense calculator app, the choice of API can determine the results of your team’s app development efforts. But more than the choice of API, proper management is another crucial talking point. The best results come with a system that identifies incoming calls, directing them to the appropriate resource. 

    API gateway is the future of DevOps and is the solution to that need. It’s the technology framework for routing API client calls to the ideal application. It also processes the call, forwarding resulting responses to the client’s network.

    At the technical level, an API gateway isn’t a must-have. Find a developer with a digital business card, hire them, and they can always program an embedded code responsible for call request routing. The only caveat to this alternative is the manpower and resources necessary to program and insert codes for individual call requests. As such, it’s always better to have an API gateway to handle this task. 

    An API gateway is a more innovative solution because extensive coding always holds the possibility of risks and errors. Furthermore, these errors can complicate app development stages like maintenance, bug fixing and application testing. 

    The API gateway ensures all API requests reach their intended destination with zero diversion. Plus, it also offers the following added functionalities:

    • API request monitoring
    • Shifting API requests between individual nodes
    • Request balancing for multiple instance situations

    The Major Differences Between API Gateway and Service Mesh

    An important digital workplace definition that differentiates both frameworks is the placement location. The API gateway is necessarily present on public-facing systems. Other key areas where an API gateway and service mesh differ include:

    Observability

    Observing the performance of the average API gateway is a more concrete task. The framework can provide actionable data insights like how long the API takes to respond to requests, problematic features, and their impact on network traffic. 

    With the service mesh, the ability to spot performance issues is a given. However, the system can’t ascertain any effects of performance lags on end-user response and experience. Therefore, while troubleshooting is easy, gauging the extent of the problem’s impact is more complicated. 

    The Communications They Handle

    Both frameworks manage different communication nodes—one handles internal discussions and the other external ones. The API gateway is the component responsible for routing external communications. For example, the API gateway handles chatbot connections, purchase orders and visits to specific pages. 

    Conversely, the service mesh is responsible for internal communications in the system. For illustration, a discussion between multiple microservices under the same app environment will fall under the service mesh’s purview. 

    In other words, the API gateway manages client-server discussions. Meanwhile, service-service communications are for the service mesh. 

    Management

    Both frameworks may have some areas of overlap, but the amount of management each one requires isn’t one of them. API gateways are simpler to manage and develop. As such, they’re easier for your app development team to manage. 

    The deployment for an API gateway happens just once, regardless of the service app. Plus, post-deployment centralization and monitoring are easy tasks. 

    In contrast, a service mesh is more complicated and tedious to manage. Your app development team must deploy the service mesh function for individual app systems. 

    Compatible Tools

    Most API gateway tools and software resources are highly expensive. Plus, they’re compatible with every popular app architecture. 

    The other end of the equation offers more accessibility. There are countless service mesh tools and resources for varied functionality. Plus, the majority of these support tools come at zero cost because they are open source.  For example, there’s Envoy and Istio, both of which are free and open source. 

    However, you shouldn’t expect to enjoy cross-platform compatibility across these service mesh tools. For example, Istio is only compatible with Google. On the other hand, AWS App Mesh—another service mesh tool—is compatible with AWS Cloud. 

    Image Source

     

    Difference  API Gateway  Service Mesh
    Existing Functionalities
    • Useful for API requests between the client and server
    • Compatible with external API requests and internal calls. 
    • Handles internal communications 
    • Best for improving the portability of service-to-service calls 
    Digital Transformation Functionality
    • Longer app delivery cycles 
    • Zero security risks
    • Useful for effective microservices management 
    • Speeds up the network’s delivery cycle 
    • Security risks due to open loopholes when the program runs alone
    Operations Reroutes API calls present outside of the given application environment  Works within the application architecture 
    Maturity Level API gateway is mature technology. It has been a core developer tool for several years now Service mesh is still a relatively new technology and requires more research and development
    Security Processing Automated security protocol Manual security systems 
    Usage Complexity Application complexity remains constant with endpoints remaining unchanged  Business scalability can be complex as each update comes with new endpoints 

    Can Service Mesh and an API Gateway Be Used Together?

    The unlikeliest of brands often form marketing partnerships. In the same way, there are instances where using both a service mesh and an API gateway is a logical and feasible idea. 

    While differences exist between an API gateway and a service mesh, it’s not an “either/or” situation.

    Cloud contact center teams looking to streamline communications at both the internal and external levels are already leveraging both technologies. And you can also leverage both systems to achieve the following:

    Improved Innovation

    Effective API use, especially during external interactions, requires internal resource optimization, which is better when teams deploy a service mesh alongside an API gateway. 

     

    Image Source

    Accelerated Digital Transformation

    Leveraging both resources improves enterprise digital transformation rates. Plus, any application with both technologies will enjoy a unified API gateway for internal service mesh management. If there are any linked applications, the unified API makes them simpler to handle.

    Increased Security Scalability

    Scalable container security is achievable when you deploy a service mesh and API gateway together. The service mech will boost the system’s interservice connectivity while the API gateway acts as a central point for all client-server requests. 

    The API gateway also provides the much-needed technical support for increased proxy security. It also fosters quick threat detection and resolution at the proxy level. 

    API Gateway and Service Mesh are Different

    Both the API gateway and service mesh are designed to simplify communication while also reducing any coding responsibility on the app development team. While both systems can ensure network calls through an enterprise contact center reach the target destination, they’re structurally different.

    Above, we’ve highlighted the key differences between both frameworks. But despite these differences, both systems are compatible and can work together for improved app development. We recommend leveraging a service mesh and an API gateway together for better security, innovation and app scalability.

  • Moving From Lift-and-Shift to Cloud-Native

    Moving From Lift-and-Shift to Cloud-Native

    Analyst firm Forrester recently predicted that 2022 “will see big organizations move decisively away from lift-and-shift approaches to the cloud, embracing cloud-native technologies instead.”

    According to Gartner, more than 85% of enterprises “will embrace a cloud-first principle by 2025 and will not be able to fully execute on their digital strategies without the use of cloud-native architectures and technologies.”

    As the Gartner analysts put it, “cloud-native platforms improve on the traditional lift-and-shift approach to cloud, which fails to take advantage of the benefits of cloud and adds complexity to maintenance.”

    What’s happening here? Is lift-and-shift–long seen as a relatively quick and inexpensive way to migrate existing workloads to the cloud–really going the way of the dinosaur? Has the cloud-native future really arrived?

    I think the true answer is somewhere in the middle right now. Yes, many companies have adopted a cloud-first strategy, turning to the cloud as an assumed starting point for most or all of their application needs. But many others still have a mix of on-premises infrastructure and public cloud infrastructure with opportunistic lifting-and-shifting from one to the other rather than a holistic cloud-native model.

    Lift-and-shift has been and remains a perfectly natural and effective step in many organizations’ cloud journeys. All you do is redirect a copy of an application from an on-premises data center to the cloud–no need to redesign the app’s architecture or code.

    This method offers a fast and efficient way to leverage the cloud’s benefits: The ability to focus IT dollars on operational (rent) rather than capital (own) expense and take advantage of the extensible computing power, storage and other services in the cloud.

    In contrast with lifting and shifting, a cloud-native approach takes longer and is more labor-intensive because it takes many moving parts to redesign the entire app ecosystem. The payoff comes later with lower total cost of ownership and more flexible, responsive infrastructure.

    If many companies are still lifting-and-shifting, why are the analysts so bullish that it is on its way out? Because lift-and-shift isn’t as simple and inexpensive as it looks. It essentially defers the eventual re-engineering to cloud-native and yet still requires an investment in capacity, people, money and time.

    First, despite lift-and-shift’s promise as an easy way to migrate existing applications to the cloud, it is common for organizations, no matter how much they plan, to hit some technical roadblocks in the execution. An app that worked a certain way in the legacy environment might not work exactly the same way in the cloud, and these details must be worked out.

    Second, companies are often caught off guard by cloud “sticker shock”–the unpleasant billing surprises that occur when workloads exceed the capacity agreed on with the cloud provider.

    Third, while lift-and-shift is a way to advance on the cloud path, it’s not the ultimate destination.

    The Cloud Native Computing Foundation defines cloud-native technologies as empowering organizations “to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach.”

    That’s a much bigger vision than the intermediary steps that lift-and-shift entails.

    What should companies still engaged in a lot of lifting-and-shifting be doing to prepare for their cloud-first future?

    1. Containerize like crazy. Virtualization was a game-changer because it allowed companies to abstract away hardware and run multiple virtual machines (VMs) on a single piece of hardware. This allowed a move in best practices toward a VM-per-function. Process containers, made famous by Docker and Kubernetes, are a logical extension of this concept: Stripping out redundant pieces of an operating system so that each logical unit contains only what is needed for the function it is designed to achieve. That, combined with a more deliberate approach to separating application and data, is the secret sauce of a cloud-native enterprise. Container adoption has been growing rapidly in enterprises–Gartner has predicted that containers will be the “default choice for 75% of new customer enterprise applications” by 2024. This trend bodes well for the move away from lift-and-shift to cloud-native and brings organizations closer to “write once, deploy anywhere” as each of the major cloud platforms and many on-premises tools provide mechanisms to run containers as first-class citizens.

    2. Consider the skills equation and where you want to focus your efforts. Every company embarking on a cloud-native strategy needs to carefully examine to what extent they’ll need architects and other skilled pros to carry it out. They need to think about what makes sense in terms of hiring people in-house, outsourcing to third-party experts and leveraging public cloud offerings such as serverless computing that reduce labor requirements.  It may be more sensible, for example, to focus on migrating application development to containers but rely on public cloud container platforms, low-ops Kubernetes or managed data center Kubernetes services rather than trying to build that competence in parallel.

    3. Rely heavily on automation. One of the advantages of containers encapsulating everything they need is that it makes it easier to build, test and deploy them as part of a CI/CD pipeline. Given they are also normally easier to scale horizontally, it is possible to automate how the application will scale to respond to external factors. Taking a model-driven approach to cloud-native applications can help DevOps teams and developers understand the conceptual pieces and relationships between complex software deployments while automating some of the details and life cycle management. Monitoring microservices brings its own set of challenges, so it is important to ensure that the observability tools you are using were designed to be effective with cloud-native applications. Cloud-native can bring great scalability benefits, but only with sufficient automation to limit friction in the cloud-first journey.

    4. Have a strong update strategy. Moving to containers distributes your software provenance and update problem across a much greater number of pieces; containers are not normally updated but instead are replaced with an updated version. This changes your traditional update approach. It is more important than ever that the pieces you are putting into those containers at build-time have a good software provenance and update story.

    5. Think holistically. Ruthlessly evaluate what apps can be cloud-native and which should remain in the data center and then consider the true benefits of hybrid cloud. Some organizations get caught up in thinking they need to move everything to the cloud wholesale. Maybe cloud-native isn’t right for everything.

    The industry-wide transition from lift-and-shift to cloud-native is accelerating. By keeping these five points in mind, companies can feel confident they’re moving forward, too. 

  • DevOps and Hybrid Cloud: Life in the Fast Lane?

    DevOps and Hybrid Cloud: Life in the Fast Lane?

    Scream if you want to go faster! When it comes to a dual hybrid-cloud-and-DevOps rollout, most organizations would admit they’re eager to get going a little bit faster. But what started so enthusiastically can turn to frustration (and a different kind of screaming starts) when they’ve accelerated into this major transformation without considering all the necessary elements.

    The benefits are clear. Hybrid cloud backed up by DevOps is an efficient vehicle for change. A robust DevOps platform can be a make-or-break factor in developing a hybrid cloud strategy that goes the distance. Together, they are a force for transformation, and if organizations aren’t already implementing both DevOps and hybrid cloud, they should be asking themselves why not.

    It is true that the move to hybrid cloud is a different journey for cloud-enabled organizations than it is for cloud-native ones. The trip is harder for cloud-enabled, particularly for larger enterprises. Increased release frequency requires tighter alignment and collaboration than is traditionally seen between lines of business, development and IT operations, and this, in turn, drives the need for enhanced collaboration, automation and information transparency.

    But although the transition might be harder, it must be seen as inevitable. Organizations could wait another year, maybe a little more, but the transformation of technology and business is going to happen—so why not get started? In the first of two articles, I’m going to take a look at what needs to change so that organizations can start living life in the hybrid cloud and DevOps fast lane.

    A Cultural Phenomenon

    As has been covered in these pages in some detail already, the move to hybrid cloud backed by DevOps is doomed to fail if organizations think all they need to worry about is tooling and hiring. It’s not. Underlying both of these transformations is a sweeping cultural change. DevOps is about agility, trust and autonomy, and so is hybrid cloud.

    Most of all, though, DevOps and hybrid cloud are a commitment to enhancing an organization’s developer experience (DevX), and that’s not something that can be achieved with simply a ticketing tool or by adopting a GitOps approach. DevX means autonomous, unbound movement. It means empowerment, user experience and self-service. These are changes that can only happen with a successful change in business culture, not a tool. And this is an important starting point that many organizations are still struggling to understand.

    The People Problem

    People are another well-worn topic, but one that continues to present a major challenge. The cultural transition required to successfully implement DevOps can, theoretically, start with just one person. But for a successful outcome, it actually requires long-term change as deeply-ingrained beliefs are disbanded and tribal loyalties are broken down.

    For instance, many believe that implementing DevOps requires hiring new people. That belief embraces two fallacies: One, that organizations will be able to hire the teams they need and two, that DevOps is just a job title. As we know, a good DevOps team is not hired, it is developed through the melding of development and operations. The old silos, where devs developed and ops operated, is a relic from less-enlightened times.

    Today, it requires learning how to build automation, often open source, while managing on-premises, private and public cloud infrastructure. DevOps is a philosophy that seeks to help others, and with that comes the need for collaboration, encouragement, persuasion and other soft skills.

    Security and Privacy Are not Straightforward

    Moving to a hybrid cloud means that more care needs to be taken with regard to security and privacy. One of the main problems is that it’s no longer enough for security teams to reign from on high. With control moving from the server room to the cloud and from highly-siloed ops engineers to the whole team, security policies also need to change. Competent developers will make the right decisions, but they need the right bottom-up tooling that takes their decisions from theory to reality and safeguards those who aren’t as aware.

    These must be a catalyst to make organizations sit up and take a long look at what security in the age of cloud, containers and microservices really means. If the simultaneous move to DevOps and hybrid cloud is that catalyst, then so be it. Just as DevOps is revolutionizing the way teams approach their work, DevSecOps is going to revolutionize the way they look at security.

    Security shows its face at various stages of infrastructure: When a cloud organization is created and structured; when a vault is integrated to ensure that key passwords are secured and even when a pipeline is launched that triggers dedicated security software. This isn’t an exhaustive list, but it illustrates how organizations need to start taking a methodical, step-by-step look at security in their hybrid cloud.

    What About GitOps?

    Gartner recently found that the average company uses 28 infrastructure tools. That’s simply too many to be handled and understood by one person. Even specialist DevOps engineers can’t be experts in all the cloud providers, OpenStack and VMware. Other studies showed that a developer generally only uses 5% of their Git repositories or an average of five repositories.

    The mistake lots of companies make is thinking that suddenly shifting to using APIs with a GitOps approach is adequate to handle the change to hybrid cloud. It’s not, and can actually be detrimental to DevX. Why? There’s too big a gap—it’s like just doing a long weekly run the day before a marathon. You might start, but you’ll be severely compromising your ability to meet your goal. Even DevOps engineers struggle to maintain a single source of truth and well-maintained reusable repositories.

    The solution is to plan for the long term. It’s not realistic to believe that one or two DevOps engineers can be the saviors of a hybrid cloud approach. There are far too many tools, best practices and options—between Ansible, Terraform, Kubernetes and Concourse CI/CD to name just a few—to be managed by a handful of devs, no matter how talented they are.

    That’s why the true way to hybrid cloud mastery lies in the ability to get the whole tech team pulling in the same direction, collaborating, upskilling and leveraging their strengths to support the parts that make the whole. This might sound like a pipe dream, but there are companies out there talking the talk and walking the walk.

    Start Your Engines

    It is futile to tell an organization exactly how to get started since many are already taking the first steps and every organization’s situation is unique. There is more to cover; in the next installment, I’ll be taking a look at areas like FinOps, automation and cloud waste. Hopefully, you’ll see the fast lane is clear up ahead.

  • Why Distributed Cloud Is the Future of Cloud Computing

    Why Distributed Cloud Is the Future of Cloud Computing

    A distributed cloud is a public cloud service that allows you to run public cloud infrastructure in multiple physical locations while being centrally managed for performance and compliance. The most innovative companies are moving all their assets to a distributed cloud structure. It is safe to say that distributed cloud is the future of cloud computing.

    Lou Senko, senior vice president of IT and chief availability officer at Q2, will be speaking about distributed cloud, how it can benefit your business and why it is the next generation of cloud computing at DevOps Experience: The Roaring 2020s Virtual Summit, on Oct. 28 at 9:45 a.m. ET. Lou will explain how distributed cloud makes the most of multiple channels and how this emerging strategy can enhance your digital posture.

    During a quick interview with Lou, he explained some of the main benefits and advantages of distributed cloud and shared a sneak peek of his upcoming session. Check out the interview below to find out what to expect at DevOps Experience 2021.

    This year’s DevOps Experience will focus on DevOps and the use of the cloud to enable digital transformation. The two-day event, starting on Oct. 27, will bring together DevOps and cybersecurity luminaries from around the globe for a free, interactive learning experience.

    The agenda for the two-day virtual event features a mix of topics, including technical sessions, deep-dives and case studies covering digital transformation, DevSecOps, cloud-native, Kubernetes, AppSec, CI/CD, open source, value stream management and more. The virtual environment features more than 50 sessions by industry leaders and an expo hall lined with booths full of downloadable resources.

    To check out the full agenda and to register, please visit the DevOps Experience website.