devopsy.kinsta.cloud

Category: Cloud Management

  • Deploying a Service Mesh: Challenges and Solutions

    Deploying a Service Mesh: Challenges and Solutions

    A service mesh is a dedicated infrastructure layer that enables communication between microservices in a distributed application. It helps to abstract the underlying communication infrastructure, such as network protocols and load balancing and provides a consistent interface for microservices to communicate with each other.

    In a service mesh, each microservice in the application is represented as a “service” within the mesh, and the mesh acts as a proxy between the services, routing requests and responses between them. It also includes a control plane, which manages and configures the proxy instances and provides observability and monitoring capabilities for the services.

    Some of the benefits include:

    • Improved observability: A service mesh provides visibility into the communication between microservices, which can be helpful for debugging and monitoring the performance of the application.
    • Resilience: It can help to make microservices more resilient by providing features such as retries, timeouts and circuit breakers, which can help to prevent cascading failures.
    • Security: A service mesh can help to secure communication between microservices by providing features such as mutual TLS (mTLS) and rate limiting.
    • Ease of use: It provides a consistent interface for microservices to communicate with each other, which can make it easier for developers to build and manage distributed applications.

    Why is a Service Mesh Important?

    A service mesh is important because it helps to abstract the underlying communication infrastructure for microservices-based applications, which can make it easier for DevOps teams to build and manage these types of applications.

    One of the main benefits is that it provides a consistent interface for microservices to communicate with each other, which can make it easier for developers to build and manage distributed applications. For example, a service mesh can provide features such as load balancing, retries and timeouts, which can be useful for ensuring the resilience and reliability of the application.

    It can also help to improve observability for microservices-based applications by providing visibility into the communication between the microservices. This can be helpful for debugging and monitoring the performance of the application, which can, in turn, make it easier for DevOps teams to identify and resolve issues more quickly.

    What are the Main Deployment Challenges?

    There are several key challenges that a DevOps organization may face:

    • Complexity: Service meshes can be complex to set up and manage, especially in large, distributed applications. This can make it challenging for organizations to implement and ensure that it is configured correctly.
    • Operational overhead: Service meshes can add a layer of complexity to the application stack, which can increase the operational overhead of managing the application. This can be especially challenging for organizations that are not used to operating one.
    • Cost: While service mesh software is typically open source, the need to run a sidecar container alongside every container can increase the compute capacity needed to run a Kubernetes cluster.
    • Integration with existing systems: They can be difficult to integrate with existing systems and processes, especially if the organization has not previously used a service mesh. This can make it challenging to get the full benefits.
    • Lack of expertise: Service meshes are relatively new technologies, and there may be a lack of expertise within the organization. This can make it challenging for organizations to get started and ensure it is used effectively.
    • Performance overhead: Service meshes can add a performance overhead to the application as they introduce an additional layer of proxying between microservices. This can make it challenging to ensure that the application is performant and scalable.

    Best Practices to Ease Service Mesh Pain

    Here are a few best practices that can turn service mesh deployments from a pain to a pleasure.

    Use Configuration-as-Code in a GitOps Approach

    Using configuration as code in a GitOps approach is a best practice to improve reliability and maintainability.

    GitOps is a way of managing infrastructure and applications using Git as the single source of truth. In a GitOps approach, all configuration and deployment information is stored in Git, and changes to the infrastructure and applications are made by committing code changes to Git.

    Using configuration-as-code in a GitOps approach can help to improve the reliability and maintainability of the service mesh in several ways:

    • Version control: Storing configuration-as-code in Git allows you to track changes to the service mesh configuration and roll back changes if necessary. This can help improve the service mesh’s reliability by making it easier to identify and fix issues.
    • Collaboration: Git allows multiple people to work on configuration at the same time, which can make it easier to collaborate on changes and ensure that the service mesh is properly maintained.
    • Automation: GitOps approaches often use automation tools, such as continuous integration and delivery (CI/CD) pipelines, to automatically deploy changes to the service mesh when code is committed to Git. This can make it easier to manage and maintain and can help to improve its reliability by reducing the risk of errors.

    Focus On Developer Experience

    Ensuring a positive developer experience is a best practice because it can help to improve the productivity and effectiveness of the development team. A positive developer experience means that developers can easily understand and use the service mesh, and that it does not introduce unnecessary complexity or frustration into their workflow.

    Here are some ways to improve the developer experience:

    • Provide clear documentation: It is important to provide clear and comprehensive documentation on how to use the service mesh, including examples and tutorials. This will make it easier for developers to understand and use.
    • Integrate with existing tools and processes: The service mesh should integrate seamlessly with the existing tools and processes that the development team is already using. This will help to minimize disruptions to the team’s workflow and make it easier for them to work with.
    • Provide support and training: It is important to provide support and training to help developers understand and use the service mesh effectively. This can include online resources, in-person training, and support from the vendor.

    Reduce Costs With Low-Cost Cloud CPUs

    A service mesh increases the cost of an entire containerized deployment because it requires deploying a sidecar container alongside all workloads. When running on Amazon Web Services (AWS), the AWS Graviton processor can ease deployment by reducing the cost of running service mesh infrastructure.

    The AWS Graviton processor is a custom ARM-based processor designed specifically for use in Amazon Web Services (AWS) environments. It is optimized for running workloads commonly found in the cloud, such as microservices and containerized applications.

    Using the AWS Graviton processor can help to reduce the compute costs of a service mesh because it is generally less expensive than other processors, such as Intel Xeon processors. The AWS Graviton processor is also designed to be highly efficient, which can help reduce the service mesh’s overall resource utilization. This can help to reduce the cost.

    Choose the Right Control Plane

    Choosing the right control plane is a best practice because it can impact the performance, reliability and maintainability of the service mesh. The control plane is the central component that manages the proxy servers and enables you to configure and monitor the communication between microservices.

    Here are some considerations for choosing a good control plane:

    • Compatibility: It is important to choose a control plane that is compatible with the rest of the service mesh infrastructure, as well as with the application and its dependencies. This will ensure that the control plane can operate effectively and support the needs of the application.
    • Performance: The control plane should be able to handle the traffic and data volumes of the application without experiencing performance degradation. It should also be able to scale up or down as needed to meet changing demand.
    • Reliability: The control plane should be reliable and able to withstand failures without interruption. It should also provide features such as circuit breaking, retries and timeouts to help improve the resiliency of the service mesh.
    • Ease of use: The control plane should be easy to use and understand, with clear documentation and a user-friendly interface. This will make it easier for the DevOps team to manage and maintain the service mesh.
    • Integration with other tools: It is important to consider how the control plane integrates with other tools and systems, such as monitoring and logging tools, and how it can be integrated into the overall workflow of the organization.

    Conclusion

    In conclusion, deploying a service mesh can be a complex and challenging process, but it can also provide significant benefits in terms of improving the reliability, scalability and security of a cloud-native application. 

    Some of the key challenges include complexity, operational overhead, integration with existing systems, lack of expertise and performance overhead. 

    To overcome these challenges, it is important to choose the right service mesh, use configuration-as-code in a GitOps approach, choose the right control plane and ensure a positive developer experience. By addressing these challenges and following best practices, organizations can successfully deploy a service mesh and reap the many benefits it has to offer.

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  • Devs Increasingly Rely on IaC to Manage Multiple Clouds

    Devs Increasingly Rely on IaC to Manage Multiple Clouds

    A survey of more than 300 DevOps professionals conducted by Firefly, a provider of a platform for automating cloud provisioning, found that more than a third of organizations (36%) have allocated the equivalent of two or more full-time engineers per month to writing infrastructure-as-code (IaC) templates.

    A full 82% are also deploying the templates within the context of a DevOps pipeline, with 68% reporting more than half of their cloud instances are now managed using IaC tools, according to the survey. A total of 27% reported they are now managing every aspect of IT as code.

    The challenge is that 61% of respondents also admitted they can’t automatically detect configuration drift over time, with more than a third (35%) spending days or weeks remediating IaC templates. Well over half of respondents (56%) said they are also retrofitting existing cloud instances using IaC tools.

    Cindy Blake, vice president of marketing for Firefly, said this issue is likely to become more challenging to address as the number of clouds in use continues to increase. The survey found 44% of respondents already use multiple cloud providers. Overall, 42% reported having more than 10 cloud accounts.

    The top IaC benefits identified by survey respondents are improved efficiency (75%), increased reliability (55%) and easier compliance (52%) and simpler troubleshooting (49%).

    Not surprisingly, the survey identified knowledge (46%) followed closely by complexity (43%) as the top challenges organizations face when using code to manage cloud infrastructure. Factors increasing complexity included cost and complexity (70%), followed by security (61%).

    In addition, only 14% of respondents reported that all their engineers are IaC literate. More than a third (36%) said they only have one IaC-literate engineer. As a result, many organizations are now attempting to navigate IaC bottleneck issues that could be alleviated if they relied more on automation that can be integrated within a continuous integration/continuous delivery (CI/CD) platform, noted Blake. She added that many organizations are already allocating too much engineering time to manually writing IaC templates.

    Those manual efforts often result in misconfigurations that are easily exploited by cybercriminals, added Blake. Many developers using IaC tools such as Terraform have had little to no cybersecurity training, so the odds they will make a mistake are high.

    At a time when more organizations are focused on the productivity of DevOps teams and ensuring the integrity of software supply chains, there is a clear need to automate processes that increasingly span multiple clouds. More organizations than ever are employing multiple clouds to ensure application availability in the wake of a series of outages over the past few years, Blake said.

    Regardless of the motivation, multi-cloud computing is here to stay. Developers opt for different clouds based on the performance capabilities they can provide for various classes of workloads. There may be one cloud platform that runs the bulk of the workloads, but the number of organizations that have standardized on a single cloud are comparatively few. The issue is finding the best way to manage multiple clouds that doesn’t require as much manual effort so organizations can reduce the total cost of managing IT environments.

  • Cloudflare Adds Digital Experience Monitoring to CDN Portfolio

    Cloudflare Adds Digital Experience Monitoring to CDN Portfolio

    At an online CIO Week event, Cloudflare today added a digital experience monitoring capability to a portfolio of services layered on top of its core content delivery network (CDN).

    Corey Mahan, director of product management for Cloudflare, said the Cloudflare Digital Experience Monitoring service extends a Cloudflare Zero Trust platform based on agent software dubbed Cloudflare WARP. The solutions delivers a wide range of software-as-a-service (SaaS) offerings spanning everything from data loss prevention (DLP) to email security.

    He added that the overall goal is to reduce the total cost of IT by delivering SaaS application services more efficiently using a single agent rather than having to deploy multiple agents for each service.

    The Cloudflare Digital Experience Monitoring service, available as a private beta, will enable IT teams to leverage the Cloudflare CDN to measure and analyze controlled data flows to public or private resources by emulating traffic flows using synthetic data. Via integration with the Cloudflare Zero Trust platform, IT teams can also access real-time data visualizations highlighting anomalies in connectivity or performance that might, for example, be indicative of a security breach, noted Mahan.

    While there’s no doubt IT organizations are looking to streamline the number of IT vendors they need to manage, it’s not clear what the center of gravity will be for achieving that goal. Cloudflare is making a case for using the same global CDN that many organizations already rely on for networking services.

    The Cloudflare Digital Experience Monitoring service leverages the company’s CDN to make it simpler to understand, for example, why users in one geography experience sub-optimal application experiences compared to another, said Mahan. That’s especially critical when more organizations than ever have employees working from home across multiple geographies, he added.

    In the longer term, more networking and security functions will be consumed as a service. The challenge then becomes integrating those services into the DevOps workflows that are employed to deploy applications across a highly distributed computing environment. In many cases, what might initially appear to be an application performance issue winds up being a network connectivity problem that is more easily solved.

    One way or another, the management of IT services in the months and years ahead will continue to converge. Organizations of all sizes will need to determine whether it makes economic sense to acquire platforms they need to manage versus consuming a service that is managed on their behalf. Most of the time, a service will be easier to consume and free up resources that can be applied to other IT functions, such as application development.

    Of course, organizations will also need to take care to avoid locking themselves into a specific services provider. Ultimately, however, the question is whether managing a specific IT function provides enough differentiated value to be worth the time and effort when there is so much more to do.

  • Survey Sheds Light On Cloud, API Expertise Skills Gap

    Survey Sheds Light On Cloud, API Expertise Skills Gap

    Enterprise IT faces a three-pronged onslaught: Digital transformation, open APIs and security threats. First, most organizations are still navigating ongoing digital transformations and cloud migrations. Second, development teams continue to increase their use of open APIs, leading to sprawl concerns. And third, we’ve witnessed a slew of cybersecurity threats that appear to be growing in sophistication. Tech leaders are attempting to govern this influx of new tools and risks, yet it can be challenging to innovate quickly while ensuring that sensitive data is always protected.

    The Axway 2022 Open Everything Survey shed light on some of the above challenges and attitudes of those invested in API development and API-enabled managed file transfer (MFT). Most notably, the survey found that 86% of respondents feared an expertise gap in the coming years, in which their organization won’t have the skilled software and IT infrastructure talent they needed to innovate. Below, we’ll review other findings from the survey, focusing on the responses from those who indicated they’re invested in API development.

    Cloud Migrations Are Still Underway

    Digital transformations are still underway in the vast majority of organizations. Only 12% reported being wholly digital and leading innovation. The rest were either just beginning transformations, were midway through or were still largely brick-and-mortar. More than one-third (38%) also said their company’s digital makeup is a hybrid of old and new technology.

    The most-adopted computing environment is the public AWS cloud, at 47%. Yet other options trailed close behind, including hybrid (37%), managed cloud services (32%), Azure (28%), private (25%) and Google Cloud Platform (18%). Other reports substantiated how modern IT is becoming increasingly hybrid and multi-cloud. As digital journeys continue to shift and evolve, some organizations are embracing multiple fit-for-purpose clouds.

    Although multi-cloud offers unparalleled flexibility, the primary drawback is security. Just over half (55%) of respondents said that tracking and controlling the flow of personal data into and through the cloud is a key hurdle to a multi-cloud strategy. And 53% reported that dealing with different security requirements for regional instances of cloud infrastructure was a top challenge. This concern is warranted, as companies doing business internationally must carefully navigate many specific regional data regulations.

    Open Data Strategies Abound

    As the Open Everything name indicates, many different sectors are becoming more “open.” The report highlighted the adoption habits of APIs within supply chains, where they are most often used to configure applications, operate and monitor applications and integrate internal data sources. Popular use cases here included payment and tracking systems. APIs also have a significant role to play in the financial world—41% of those working in finance said open banking is an opportunity to discover new business models. But nowhere is the need for more open data more crucial than in health care, which was found to be the area most in need of digital transformation.

    We’d like to think of the API revolution as being driven by API-first startups and SaaS services. While these trends get attention, it’s not the most common use case for APIs. In fact, 44% of the time APIs are used to support IT consulting and system integration requirements. This is followed by providing cloud applications for customers (35%), developing a partner network (35%) and offering cloud services for customers or partners (34%). Although there are certainly business use cases for generating revenue through APIs, they are most often adopted to supplement existing platforms or to glue together internal services and data.

    Most Technology Leaders Fear API Sprawl

    Security is an encompassing concern for all walks of IT, but is especially top-of-mind when opening up data. Respondents said security is the most important concern when creating APIs (30%). This concern is warranted, as attacks on APIs have increased exponentially in recent years. Other top concerns are API adoption or consumption (15%), customer experience (14%), ease of API management (14%) and design and development (11%).

    As APIs and microservices become more abundant within an organization, it’s easier for sprawl to set in. Unbridled technology sprawl can have a deteriorating effect on design standards and lead to unknown shadow APIs that may pose a security vulnerability. As a result, over two-thirds of respondents said the prospect of API sprawl worries them.

    To mitigate sprawl and address other concerns, most companies are investing in tools to help manage the growing number of APIs. The majority (83%) said their budget for API management has either increased or stayed the same over the last two years. For 18%, this budget has risen by over 25%. Operationalizing API life cycle management capabilities can have benefits such as standardizing design style and increasing the discoverability of internal services.

    API Security Must Still Mature

    In a perfect world, we could share data without fear of misuse. But in reality, APIs are a common target for hackers. Publicly exposed endpoints with broken access control or missing object-level authorization can be easily abused for things like privilege escalation and data exfiltration. And although these risks persist, many APIs don’t adopt industry best practices regarding API security.

    Although most APIs use authentication and token schemes, under half (43%) implemented OAuth. Furthermore, only 30% implemented policies with an API gateway. OAuth 2.0 and gateways have become best practices in serving APIs, as there are too many vulnerabilities to rely solely on HTTP Basic Authentication and API keys. As such, we will likely see these adoption rates increase as API security matures.

    As with other cybersecurity endeavors, it’s really about taking a holistic perspective and applying defense-in-depth. Thankfully, most technology professionals understand this point—developing a more holistic approach to security was ranked as the top strategy for protecting personal data. Other strategies, like data encryption, advanced multifactor authentication, data loss prevention tools and highly-secured data transactions will also be necessary to protect cloud-native assets.

    Final Thoughts

    The Axway 2022 Open Everything Survey asked 1,000 IT leaders, architects and developers about their top concerns. Above, we focused on results from technology leaders engrossed in cloud and API development. For more insights and the findings from those using managed file transfer (MFT), readers can pick up a copy behind an email gate here.

  • Best of 2022: CI/CD is the New Lock-In

    Best of 2022: CI/CD is the New Lock-In

    As we close out 2022, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022.

    Welcome to 2022! Let’s start this year’s blogging off with a bang, and point out that we are in the process of creating the biggest lock-in that we have ever had. And I do mean ever. Maybe the hardware lock-in of the old days where vendor A was incompatible with vendor B was worse, but at least that one we acknowledged when we signed the contract. This one is growing on us as I type.

    Our DevOps environments in 2022 cannot run without what I like to call the “toolchain controller”: GitLab, Github CI/CD, Atlassian, CircleCI, Jenkins—whatever you are using. Like you need some form of faucet or flow control to make running water work, you need the CI/CD environment to make DevOps work.

    You. Can’t. Live. Without. It. And just like any other vendor solution, CI/CD vendors are not going to be in a rush to help you move to a competitor. It won’t be easy or cheap to switch, largely because we are moving everything that might have been on a computer that once had developed code running on it into the toolchain.

    Sooner or later, we’ll back off the kitchen sink definition of “What is DevOps?”, but I predict even then we will have to answer “…A lot of what we do,” because DevOps is, by definition, end-to-end. It is about the process and all the steps from design to production.

    No matter how long or complex the process through which an organization’s CI/CD tool runs, a plan must be in place to replace it. A workable plan, not a check box plan. When Atlassian decided they preferred cloud-based customers, their customer base was shocked. Atlassian was wise enough to leave an option for customers who really had to have an on-site solution, but it is not difficult to imagine them phasing that option out, or to imagine another vendor dropping on-site support altogether. Some of the more competitive offerings in the space—GitLab springs to mind—are online-only already, making that option more appealing to other vendors as it’s now proven viable.

    So, have a plan. This is more important, IMO, than cloud vendor lock-in. Cloud vendors are a small community, and each understands the others, so if push came to shove you could find help moving between the big three cloud vendors. There are dozens of DevOps master controller-type solutions in regular use, and some of them are not at all CI/CD solutions (application release orchestration tools and software infrastructure management tools are two areas doing CI/CD duty at some orgs, for example), so there is not going to be much help moving between them unless you manage to find a very specialized skill set that matches your desired move.

    So, have a plan. Yes, I am indeed repeating myself. Know what you’re going to have to do before you have to do it. Include what to do if the master DevOps controller goes down. Because it will, sooner or later.

    And keep rocking it. Protect your masterworks by protecting what builds them. And keep rolling out the tools your users need. It’s a new year—learn a new skill and use that to turn out even more cool stuff. I haven’t picked a new skill yet, but I’m taking that last bit of advice myself. And again, in the new year, thank you, for all those who don’t know to say it.

  • Opvizor Extends Monitoring Reach to the Cloud

    Opvizor Extends Monitoring Reach to the Cloud

    Opvizor, a unit of Codenotary, has extended its monitoring capabilities to cloud computing environments starting with support for Amazon Web Services (AWS) and Microsoft Azure.

    Codenotary CTO Dennis Zimmer said Opvizor aggregates data to provide a more efficient approach to applying analytics to surface performance and risk issues.

    Previously, Opvizor was optimized for instances of VMware vSphere running in an on-premises IT environment. Now the unit of Codenotary, a provider of a service for generating software bills of materials (SBOMs), is extending those monitoring capabilities to the cloud.

    That transition comes as many organizations are looking to strike a balance between monitoring pre-defined metrics and observability platforms that make it possible to surface unknown potential issues that could adversely affect IT environments.
    It’s still early days as far as observability is concerned, so Opvizor is focused on meeting most IT teams where they are today as they further embrace cloud computing, said Zimmer.

    Observability, in general, promises to query not just logs and metrics but also distributed traces that are applied to specific processes. In that way, observability allows organizations to detect patterns that have not been predefined. In effect, an observability platform makes it simpler to debug application environments where the number of dependencies that exist between services are becoming too complex to track manually, much less decipher. Without the aid of an observability platform it can take weeks to discover the exact cause of an application’s performance degradation.

    Of course, those applications will need to be instrumented using agent software capable of generating the data observability platforms require. Fortunately, open source projects such as OpenTelemetry are helping to drive down the total cost of instrumentation.

    However, in the absence of observability, most IT teams will rely on existing monitoring tools. Opvizor is making a case for centralizing monitoring across multiple platforms to reduce costs, noted Zimmer.

    Heading into 2023, each IT team will need to decide how and when to rely on traditional monitoring tools versus observability platforms. Many observability platform providers are justifying the acquisition of a new platform based on cost and the ability to eliminate the need for multiple monitoring tools. However, it remains to be seen whether IT organizations will prefer to employ both monitoring tools to track predefined metrics alongside observability platforms.

    Regardless of approach, the reality is that IT environments are becoming more complex to manage. In addition to running workloads in multiple cloud platforms and on-premises IT environments, organizations are deploying emerging cloud-native applications based on containers alongside existing monolithic applications deployed on legacy virtual machines. As workloads are deployed on multiple platforms, the total cost of IT starts to rise. One way to contain those costs is to standardize on a set of tools that can be applied to multiple platforms.

    The pressure to rationalize toolsets only increases during any period of economic uncertainty. The challenge, of course, is convincing one team to give up their preferred tool in favor of another to reduce costs.

  • How Enterprise Software Architects can Design for Sustainability

    How Enterprise Software Architects can Design for Sustainability

    Organizations of all sizes are feeling the pressure to introduce more aggressive sustainability measures to combat climate change. For example, most cloud service providers have announced significant climate pledges to either reduce or offset their carbon emissions. But these initiatives can only go far to move the needle—it’s up to individual companies and departments to participate in curbing their climate impact, and DevOps certainly has a role to play in enacting positive change.

    One way to design for sustainability is to optimize information technology systems to reduce waste. Enterprise IT typically supports a lot of unnecessary technical debt and perpetuates toilsome tasks that contribute to energy inefficiencies. Removing unused instances and features or idle workloads that aren’t contributing value could be an easy way to reduce waste. Yet other optimizations will require more effort.

    I recently chatted with André Christ, co-founder and CEO of LeanIX, to discover what techniques enterprise-level software architects can use to get the most out of their technology modernization efforts while leaving the least carbon footprint. According to Christ, optimizing existing processes, using cloud-native technologies and leveraging value stream management are some tactics architects can take to “do more with less.”

    1. Match Technology to Sustainability Targets

    First, technology leaders must understand the capabilities of their business that could help contribute to meeting sustainability targets. “This requires understanding and systematic mapping,” said Christ. “It’s really about understanding what you can do as a company to contribute to sustainability in a more holistic way.”

    For example, a routing and logistics provider might optimize operations by redesigning its floor plan to maximize efficiency and reduce energy use. Similarly, Christ recommended software professionals take stock of their existing capabilities to determine what should change. This could equate to discovering internal microservices that aid one department and extending them across the entire organization.

    Optimizing data transfers is another way to create a leaner IT system. For example, teams could reduce constant polling by eliminating overfetching and underfetching or embracing a new API standard, like GraphQL, said Christ. Cutting out these superfluous calls reduces unneeded energy consumption.

    2. Ensure Cloud-Architected, Not Lift-and-Shifted

    Cloud migrations can reap significant benefits in terms of scalability and flexibility. But not every cloud migration delivers tangible sustainability benefits. AWS identified six unique strategies for migrating applications into the cloud: Rehosting (known as lift-and-shift), replatforming, repurchasing, refactoring, retiring and retaining. While early gains may be met simply by rehosting applications, replatforming or refactoring them completely with cloud-native components will likely deliver the best optimizations.

    “If you only lift-and-shift applications into the cloud, they will keep running just as inefficiently as a virtual machine,” said Christ. Therefore, architects should design for cloud-native whenever possible rather than simply porting legacy applications to the cloud. On the other hand, it may be prudent to replace specific legacy components with SaaS or retire them altogether. As such, it’s crucial to analyze your existing landscape before making a cloud migration to ensure changes are both cost-effective and advancing sustainability goals.

    3. Practice Value Stream Management

    Practicing value stream management is another potential strategy to cut bloat by ensuring product teams always create more value for the end customer. Planview defined value stream management as such:

    “Value Stream Management is a management technique or practice that focuses on increasing the flow of business value from customer request to customer delivery.”

    This frame of mind could help engineers make more streamlined decisions about what they’re creating. But to achieve value stream management, organizations will require enhanced visibility into how individual services perform, their dependencies under the hood and their approximate emissions.

    The core question you should be asking product teams, said Christ, is how carbon-efficiently are you operating in relation to the number of users you are serving? The answers will highlight which aspects of the business require the most optimization.

    4. Tie Sustainability to the Business Bottom Line

    Many sustainability pledges are founded on carbon offsetting, in which the company purchases “offsets” of its emissions, usually by planting trees or preserving forests. But, the practice of carbon offsetting has received criticism as being ineffective at stemming rising global temperature levels. So what does an honest climate pledge look like that’s more than greenwash? Well, perhaps one more closely associated with the bottom line.

    Taking the idea of value stream management one step further, Christ argued that a real climate pledge would involve reducing carbon footprint by a certain percentage for each new dollar generated. As a business scales and its revenue increases, it should constantly reduce emissions in parallel with this growth. This would equate to assigning a dollar value for every CO2 ton and putting it into the balance sheet, said Christ.

    Doing More With Less

    Nations are striving to reduce carbon emissions through sweeping legislation. Yet, national goals will be insufficient to meet the target decline of 43% percent by 2030 and net zero by 2050, the United Nations reported. Thus, it will take effort from the private sector, as well.

    We’ve identified some steps above to do more with less, yet many current, unsustainable practices are culturally ingrained, making them challenging to change. It will be the work of enterprise software architects to break it down and apply smarter designs to cloud-native applications. This will likely require centralizing views of internal services to enhance visibility and reporting. “You need good visibility into what you’re building and what it’s composed of to reduce the footprint,” said Christ.

  • EU Data Privacy: Try Again | SkyPilot: Choose Cheapest Cloud | WFH: Better Meetings

    EU Data Privacy: Try Again | SkyPilot: Choose Cheapest Cloud | WFH: Better Meetings

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: EU-U.S. Data Privacy Framework reemerges, Berkeley brings cloud selection box, and proof that remote work is good work. (more…)

  • Migration to AWS Cloud: Do’s and Don’ts

    Migration to AWS Cloud: Do’s and Don’ts

    What if one day, you were told to migrate to AWS/GCP/Azure/any other cloud provider? It would likely introduce some stress, to understate the case, right?

    I’ve seen quite a few migrations in my career and, in this article, I would like to share some thoughts to help DevOps engineers, architects, managers or anyone else who might be involved in such a migration. I’m focusing on migration to AWS mostly because I have a specialization in this subject and because it’s fairly common, but I think these experiences are applicable to any other cloud provider. For this case, I’ll cover migration from on-premises to a cloud because these types of migrations are much more difficult (in my opinion) than cloud-to-cloud migrations. I’ll also share my own perspective on do’s and don’ts of migrations. But please filter them through critical thinking and remember that everybody has their own background and experience. What’s good for one might be bad for another.

    What is a Cloud Migration?

    Let’s start by defining what migration is. How do you know if it’s a migration? I like the following definition: 

    Cloud migration is the process of moving a data center’s capabilities to IaaS providers.

    “Capabilities” is the keyword. A business does not migrate servers/virtual machines/hardware/data or anything else. A business migrates its capabilities.

    There are seven migration strategies (or seven Rs): Relocate, rehost (lift and shift), replatform, repurchase, rearchitect/refactor, retain and retire.

    For example, I’ve seen situations when a company was creating a new product that would replace an existing one hosted on-premises. The product would be designed to be well-architected and cloud-native from the very beginning and would be hosted in a cloud. Is that migration or greenfield project type? From the definition above, we can say that this is a migration. This is a rearchitecture strategy for migration.

    What if we buy a new SaaS subscription instead of some software we host on-premises? This is also a migration: A repurchase strategy.

    Let’s dig deeper into these seven migration strategies:

    Relocate. We host some workloads on-premises and move them as-is into the cloud. This is possible in limited cases; when we migrate cloud-agnostic workloads or when a platform might be cloud-native. Examples: Relocate a Kubernetes cluster from on-premises to the cloud or relocate VMware machines with VMware Cloud.

    Rehost. This is also known as lift and shift. We convert virtual machines/servers on-premises to virtual machines in the cloud. Examples: Migrate on-premises virtual machines to EC2 instances with CloudEndure, or create EC2 instances, install the software and apply the same configuration as on-premises.

    Replatform. We migrate a workload to a cloud-native platform without rearchitecting systems. Examples: Migrating PostgreSQL to AWS RDS or Docker containers to ECS.

    Repurchase. We replace some custom/legacy system with SaaS. Example: Replace custom on-premises email system with SendGrid or replace CRM with Salesforce.

    Rearchitect. We change your application’s architecture to be cloud-native and use managed cloud services. That also includes rebuilding from scratch. Examples: Change the code of your apps to upload files to S3 instead of local storage or containerize an app and migrate to ECS.

    Retire. We decide that a piece of the workload will be eliminated if not needed. Example: Log servers are no longer needed as migrated applications use CloudWatch.

    Retain. We leave it on-premises. Usually, it’s temporary. Example: A huge Oracle database with a lot of functions and customization is not moved to AWS because of the massive costs. It’s decided to keep it on-premises until it’s replaced with another solution in the modernization phase.

    I like the following picture that shows the high-level stages of each migration type. It may be a helpful cheat sheet to approach migrations.

    Picture Source: https://aws.amazon.com/blogs/enterprise-strategy/new-possibilities-seven-strategies-to-accelerate-your-application-migration-to-aws/

    Migration Don’ts

    I don’t recommend the following when performing a migration:

    Migrating too quickly. A business might think, “We have to migrate to the cloud quickly. Let’s do lift and shift right now!” It’s better not to start right away. Are you sure that rehosting strategy will really be faster than some other strategy? In one instance, we tried to migrate on-premises VMs, but it didn’t work because the OS on the machines was quite old. Some OS-level dependencies didn’t work on AWS’ hardware. This required a lot of configuration work, custom code and testing and the initial estimates were completely wrong. It eventually turned out to be a replatform. 

    Assess what you have, analyze it, analyze the business case and think. During this engineering work, we should stop and think before we act.

    Migration without clear goals. Why are you migrating? If you can’t answer the question, you probably need to find an answer or not migrate at all. I’ve seen situations in which businesses wanted to migrate to the cloud to reduce costs. They performed a lift and shift migration without doing a total cost analysis. Only after the fact did they realize that it cost even more than when it was in a colocation center. This migration may be considered unsuccessful.

    To avoid this, define clear goals and define the target state that achieves these goals. If costs are the driver, make the proper calculations and plan accordingly. Cost optimization will be the main thing to focus on when you plan your target state. If availability is the reason, measure it, define SLOs and focus on availability in a target state.

    Black box migration. Don’t treat workloads you migrate as a black box. It is almost critically important to know what exactly you migrate, what technical requirements it has, what dependencies it has and how it works. That information will allow you to choose the correct strategy for workload migration. If this is not done, there’s an excellent chance that you will choose the wrong path and the result will be lost. Capturing information about your systems is the most important task when planning.

    Don’t forget well-architected. Migration is stressful. That’s why people tend to try to get through it quickly on as short of a timeline as possible, focusing on the only thing: Making everything work in the cloud ASAP. They set aside well-architected framework pillars. This is a mistake; it may lead to a different set of negative consequences of different severity. Don’t ignore well-architected framework pillars, or you won’t know about potential issues or risks until they have already materialized.

    Use one strategy for everything. It’s always easy to make a single overarching plan for all workloads. For example, deciding to do lift and shift and then rehost everything in the cloud. But what if some things could be retired? What if some components could be replatformed with little effort? You will save significant resources by analyzing all of the components of the workload and deciding on a unique strategy for every component. Collect data and plan properly.

    Cloud Migration Do’s

    Do perform a cloud readiness assessment. If a person migrates to a new location, they should consider:

    • That the climate will be different
    • The language spoken in that location may be different
    • The cost of living will be different and perhaps more expensive

     When a company migrates to the cloud, they should ask questions including: 

    • Have we considered all the risks?
    • What must be changed for the workload to actually work?
    • Do we have the human resources required for all of the work?
    • Do I have the budget to accomplish everything? 

    The Cloud Readiness Assessment is a long-form interview about varying processes in the company that identifies whether a company is ready to live in the cloud. It’s based on the Cloud Adoption Framework (CAF) and allows us to understand what should be changed so that a migration can happen successfully. AWS has a Cloud Readiness Assessment tool which covers all of that. I urge you to use this process for all workloads being considered for migration.

    Create a business case. Describe the business case. What are the drivers for migration? What problems are resolved with the migration? What goals should be achieved by migration? Be specific: If you intend to reduce costs, then calculate the sum. If you intend to improve availability, then define a clear SLO. That will be the number-one driving force for your migration. All other artifacts should be based on it.

    Automate discovery and data collection. Use automated data collection and analysis to create a portfolio for migration. Don’t base your analysis on manually created spreadsheets or verbal communication. Let machines collect data about inventory and usage statistics. The more precise data you collect, the better. AWS Migration Evaluator service will help you to do this in most cases.

    Portfolio management. Create a portfolio of workloads to migrate, analyze them, choose a migration strategy for each, choose some for the pilot/first wave migration, estimate timelines and prepare a plan. Execute the migration after that. Repeat until the migration portfolio is empty. Share the data. Have subject matter experts review it.

    Found CCoE. This is part of the CAF mentioned above. Before executing the migration, create a team of people responsible for creating a strategy and defining a good standard of living in the cloud: A Cloud Center of Excellence. It should include people with a variety of subject matter expertise including management, operations, platform, people, finance and every other department consuming or providing services in the cloud. These people will prepare a landing zone for the migration, hard policies and softer policies for the landing zone; preparing the company for life in the cloud. Don’t fear revisiting any policy.  Make changes as new factors come to light.

    Well-architected framework reviews (WAFR). Do well-architected framework reviews (WAFRs) during migration waves and after them. That will allow you to avoid foolish mistakes and to get a high-level overview of what you have done from a technical perspective.

    Modernization plan. Prepare a modernization plan along with the migration plan. Migration isn’t the end of the story. To be effective in the cloud, you will have to do well-architected reviews and modernization. The first modernization is likely to be huge; that’s why it’s important to plan and to schedule budgets and resources in advance. Failure to do this will lead to increased operational costs, not decreased costs.

    Summary

    If we want to reduce the risk associated with a migration and to make it less stressful, we do not rush. You may believe that rushing will save you time and other problems will be managed later, but experience tells us that this is wrong. The most likely outcome is that you will end up resolving all the issues encountered in the most stressful situation possible: When you cut over to your new cloud-based production environment. Instead of resolving issues in a well-considered way and in advance, the choices will be made under duress. Proper engineering principles must be applied here. Picking up a bridge and moving it from one river and plunking it down on another never works. The key to migration success is to measure, analyze, design and plan. Migrating a workload to the cloud is hard, but I hope these do’s and don’ts will make it easier.

  • Dead Downtown: It’s YOUR Fault | Pentagon’s FOUR Cloud Vendors | Apple Adds MORE Price Flexibility

    Dead Downtown: It’s YOUR Fault | Pentagon’s FOUR Cloud Vendors | Apple Adds MORE Price Flexibility

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