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Tag: public cloud

  • Serverless Computing: Taking DevOps to the Next Level

    Serverless Computing: Taking DevOps to the Next Level

    Serverless computing enables you to outsource information, thus freeing teams to focus on front-end work. Organizations choose serverless when they look for faster and easier ways to release updates and patches. DevOps teams often use serverless when they are looking to automate infrastructure tasks. However, each provider offers different capabilities, and each service does require a level of training pre-adoption.

    What Is Serverless Computing?

    Serverless computing is a method that outsources infrastructure and infrastructure tasks to external providers. Organizations choose serverless computing because it enables development and operations teams to focus on the front-end of products and services.

    There are a few traits that distinguish serverless infrastructures from traditional cloud automation models:

    • Serverless computing services eliminate user responsibility for the management or operation of infrastructure.
    • Serverless computing services enable users to run code on-demand according to requests or event triggers. Infrastructure use scales transparently based on how many requests or events occur.
    • Serverless computing is pay-for-use and can be used to ensure that users pay only for actively used resources.

    The benefits of serverless in enterprise environments include:

    • Better control over production deployments.
    • Faster and easier updates or patches.
    • Increased productivity and easier release rollouts.

    Popular Serverless Computing Services

    All three major cloud providers offer serverless computing services. Below you can learn about these services and how each operates.

    AWS Lambda

    AWS Lambda is a service for serverless computing with other AWS services or via API. It can be connected to applications or run as standalone code. When using Lambda, users pay for active compute time although instances can be reserved to ensure their code runs with menial latency.

    Lambda can be triggered by a variety of AWS services, including Kinesis and DynamoDB. It can be monitored through Amazon Cloud Watch. Common use cases for Lambda include data processing, stream processing, machine learning and application backends.

    Azure Functions

    Azure Functions is Microsoft’s serverless service. You can use it for end-to-end development, including building, testing and deploying code. Functions can be used with a variety of Azure services and integrate with Visual Studio and Visual Studio Code for easy use.

    In addition to Functions, Azure offers Logic Apps, a service for creating visual design workflows and orchestrating Functions activities, and Event Grid, a message routing service to integrate Functions with other Azure services.

    Google Cloud Functions

    Cloud Functions is Google Cloud Platform’s functions as a service (FaaS) (i.e. serverless) offering. It can be used in the cloud or with hybrid deployments and it includes built-in monitoring, logging and debugging features.

    Cloud Functions supports a variety of environments including Cloud Run, Kubernetes and other Knative-based environments. Use cases for Cloud Functions include integration with third-party services, application backends, real-time processing, virtual assistants and machine learning.

    Why Serverless for DevOps

    If you are already using a DevOps approach or are considering adopting one, serverless can be a good option. Many DevOps teams, especially those operating in the cloud, are already working with modular components managed via a pipeline. Moving these modular services to serverless can enable teams to eliminate some of the tasks related to pipeline management and focus on development and deployment.

    This capability is especially valuable for teams that are just getting started or are looking to switch to DevOps practices. Serverless systems can enable teams to get started with development and testing right away on a comfortable scale. Then, as productivity increases, the serverless infrastructure can smoothly scale with minimal to no effort on the part of operations.

    Another benefit of serverless infrastructures is the ability to easily enable DevOps automation. With serverless, you can deploy your pipeline without hosted solutions. You are only responsible for “glue code.” This infrastructure is flexible and you can easily modify it as needed using infrastructure as code (IaC) solutions and automated events.

    Despite these benefits, there is a potential downside to serverless. Your DevOps team does not have the same visibility into or control of the functioning of the infrastructure. While you can integrate monitoring, teams are limited in how much of the infrastructure can be customized or manually affected.

    How Serverless Can Take DevOps to the Next Level

    There are several ways serverless deployments can be leveraged to improve DevOps productivity. Below are a few examples to consider.

    Infrastructure as Code

    Provisioning infrastructure is often a significant portion of deployment processes. Many applications use a variety of serverless services as building blocks through all stages of development and release. Making sure that these services are correctly connected and configured is key to a successful deployment.

    IaC can help users accomplish these tasks smoothly by leveraging declarative languages and tools such as Terraform. With these solutions, users can version your infrastructure along with their code, keeping tasks in sync and deployments consistent.

    Flexible Deployments

    With serverless services, infrastructure is immutable. Any changes result in new instances being spun up and activated. This means both old and new versions can run simultaneously.

    This immutability can be used to perform flexible deployments that are not possible or are much more difficult with traditional infrastructures; for example, canary or blue-green deployments. With serverless infrastructure, users can switch from one version to another with minimal fear of service interruptions and the ability to easily rollback updates.

    Distributed DevOps

    Serverless services can enable DevOps teams to work across a variety of environments and locations with minimal impact on others. These services allow the distribution of workloads at scale and can ensure that infrastructure is always available.

    The catch is that greater distribution and the ephemeral nature of serverless can make infrastructure much more difficult to monitor effectively. To account for this, teams need to ensure centralized monitoring with real-time alerts. Teams should also periodically audit infrastructure availability and performance to ensure that resources are functioning as expected.

    Conclusion

    Serverless computing enables DevOps teams to eliminate time and cost on the back end. Each serverless provider offers different services that can help achieve different capabilities. The main capabilities are provided via the use of functions, which enable the automation of infrastructure. However, in most cases, teams do need to learn how to use functions to properly configure customized IaC workflows. Once teams understand how to use the software, they can create flexible deployments and a distributed DevOps pipeline.

  • How to Overcome Challenges With AWS Lambda Logging

    How to Overcome Challenges With AWS Lambda Logging

    Monitoring AWS Lambda can be a complex and potentially costly endeavor. Here’s what you need to know to stay on track and on budget

    Organizations are already experiencing a shift toward serverless cloud computing. According to the O’Reilly “Serverless Survey 2019,” around 40% of respondents said they had implemented serverless architecture. Forrester “Global Business Technographics” Developer 2019 found that 49% of companies are using it or planning to use it in the next 12 months.

    AWS leads the way in this space. According to Serverless.com, 96% of respondents choose AWS Lambda over Azure Functions and Google Cloud Functions. AWS Lambda helps us to design a lightweight and robust application architecture that can be built and deployed without any hassle. However, nothing comes for free. There are several, potentially costly, complexities when monitoring AWS Lambda. Fortunately, there is an array of solutions.

    Logging

    By default, AWS Lambda’s stdout and stderr messages are sent to CloudWatch Logs, where every function has its log group. A log group is a collection of log streams (sequence of log events) that can be stored as long as you want. Storage of logs costs USD 0.03/GB and data ingestion costs around USD 0.50/GB.

    It is common practice to break up your Lambdas into single responsibility functions. This means, for example, if you need one Lambda to read a certain object and another to write it, you’re setting up two separate functions. However, this also means two log groups.

    This creates a challenge when you want to analyze your application’s output log. There is no direct way to log queries across multiple log groups. In response to this, AWS enabled CloudWatch Log Insights to conduct cross-log querying. While this brought many of the improvements users wanted and needed, analyzing multiple log groups together meant a higher cost for queries. This prohibitive cost model encouraged many to look to external services.

    Tracing

    AWS X-Ray enables you to trace the underlying components of your application and helps you to dig out the fundamental reason behind distributed issues. It has quickly become an essential troubleshooting and optimization tool for engineers.

    For example, cold start latency can be problematic for AWS Lambda functions with slow startup times. Although you can counter this by enabling Provisioned Concurrency, you will need to pay extra.

    If you have budget constraints and still want to resolve the issue, X-Ray might help you eliminate or at least optimize your application by removing the bottleneck. It lets you know, among other things, if your application is consuming more time during initialization or invocation. You can find X-Ray SDK on AWS Lambda for Go, Java, Node.js, Python and .NET.

    Debugging

    Traditional architecture and serverless architectures are as different as day and night. Serverless requires changes across the software engineering spectrum, including debugging.

    A serverless application is a combination of various services or resources within infrastructure, which can include tools such as AWS API Gateway, CloudWatch and SNS. Such distribution of web services helps avoid a single point of failure (SPOF), but this design creates a problem. Debugging or replicating an issue on a local machine is not always feasible, and debugging a production application is always a dangerous proposition.

    Moreover, the abstraction of AWS Lambda makes debugging complicated, as you don’t have direct access to the underlying OS. Hunting down dispersed logs adds to this overhead. As your serverless infrastructure scales, it becomes difficult to identify the root cause.

    To combat this, developers can use AWS native tools such as CloudWatch, X-Ray or Serverless Application Model (also known as SAM). Any of these tools on their own can be difficult to use; together, however, they form a powerful debugging suite.

    Outside of the AWS-native toolset, some tools provide further assistance with debugging. For example, the Serverless framework, which is an open source tool to develop and deploy serverless applications over AWS, lets you see your live application’s function log, for example:

    Monitoring

    Robust monitoring ensures the smooth operation of an application and helps to detect issues quickly. In traditional infrastructure, metrics only appear from a handful of sources, so collecting them together is less of a challenge. In a serverless architecture, this problem is much more complex.

    AWS gives you the freedom of converting CloudWatch Logs to metrics. These metrics can be filtered, measured and, when a threshold is crossed, alerted on. You can define a metric filter by choosing a log group created by your serverless function and target the log stream. This enables you to create a visual reference for your log events. Every custom metric you create will cost $0.30/10000 metrics per month.

    Metric filters can be a powerful tool, but it can also be a bit overwhelming to set up everything, and there are certain bottlenecks as well. For instance, you can’t parameterize metric names, which forces you to create a filter for every custom metric you want to track. There is also a hard limit of 100 metric filters per log group, which restricts you as your application evolves.

    Other than this, AWS resources are tightly coupled with each other, which makes AWS-native monitoring tools a fine choice when you need to monitor individual AWS resources or Lambda functions. To get an infrastructure-wide view and to monitor other third-party tools, a centralized logging approach is necessary to take full advantage of the log data.

    Conclusion

    There is no denying that serverless tooling quickly unlocks high availability, scalability and cost optimization. To make the most of this new paradigm, engineers need to build a robust and reliable monitoring system. The ability to manage log data streaming from many components, detect and trace issues on the fly, and deliver accurate insights to keep on improving the application is crucial to remain online and competitive.

    While serverless solutions give access to many of the technical features we need, the dangers of vendor lock-in and the power of third-party providers must be considered if you want to scale your organization and its infrastructure smoothly.

  • Nebulon Unveils Hybrid Cloud Computing Platform

    Nebulon Unveils Hybrid Cloud Computing Platform

    Nebulon has emerged from stealth to launch a hybrid cloud computing platform that enables workloads to be processed in the cloud while data continues to be stored on a local application server.

    Company COO Craig Nunes said the Cloud-Defined Storage platform employs PCIe cards embedded with a Nebulon Services Processing Unit (SPU) based on an ASIC to connect local storage systems to a cloud-based control plane dubbed Nebulon ON that can span Amazon Web Services (AWS) and Google Cloud Platform (GCP) services.

    The PCIe card is installed in an application server residing in a local data center, where it connects to solid-state drives (SSDs) installed on the server. The Nebulon SPU offloads compression, encryption, deduplication, erasure coding, snapshots and data mirroring.

    The Nebulon SPU also transmits storage, server and application metrics to Nebulon ON, where machine learning algorithms are applied to surface recommendations to improve performance.

    Nunes said both Hewlett Packard Enterprise (HPE) and Supermicro have already agreed to resell the Cloud-Defined Storage platform.

    At its core, the Cloud-Defined Storage platform takes hyperconverged infrastructure (HCI) to another level. Instead of combining compute and storage in a local data center, however, compute processing is shifted to the cloud, said Nunes. That approach, he noted, makes it possible to take advantage of inexpensive compute resources in the cloud without losing control over data.

    In addition, Nunes noted, the Cloud-Defined Storage platform ensures application service levels are maintained while reducing costs by eliminating the need to transfer massive amounts of data into and out of the public cloud.

    Organizations that work within highly regulated industries can now take advantage of cloud resources while continuing to meet compliance requirements, he added.

    Finally, the Nebulon Cloud-Defined Storage platform can support both monolithic and microservices-based applications regardless of the type of virtual machine or container employed.

    At a time when many organizations are under increased pressure to reduce the total cost of IT, there’s a lot more interest in ways to leverage cloud computing to reduce costs. However, for many organizations, moving data into the cloud is problematic for a host of performance, security and compliance issues.

    A hybrid cloud computing architecture that doesn’t require data to be stored or moved into and out of a cloud could provide a way for organizations to re-evaluate their overall cloud computing strategies. Organizations beyond those in highly regulated industries could conclude they would prefer to retain control over their data.

    Cloud service providers are, of course, banking on massive amounts of data being stored in the cloud. They have long argued that as the amount of data stored in the cloud exponentially increases, the more sense it makes to deploy applications in the cloud as close as possible to that data. Each new application deployed in the cloud then increases the amount of data gravity that cloud exerts on other application deployment decisions.

    It’s not likely hybrid cloud platforms such as the Nebulon Cloud-Defined Storage system will completely reverse that trend. However, it does signal that data gravity in the cloud may not be as inexorable a force as many cloud service providers have long assumed.

  • IT Modernization Yields Business Benefits Even in Early Stages

    IT Modernization Yields Business Benefits Even in Early Stages

    In recent years, with the emergence of newer technologies ranging from the cloud to machine learning, IT modernization has evolved from a replacement of end-of-life infrastructure to an enabler of innovation and business value. It is a complex process that can take months or even years, but a recent survey shows that the effort begins to deliver measurable results almost as soon as an organization executes the first steps on its roadmap.

    In The State of IT Modernization 2020, an IDG Research Services survey of 200 IT executives commissioned last December by Insight Enterprises’ Cloud + Data Center Transformation team, respondents that had completed 25% or less of their initial modernization objectives reported achieving business improvements in each of the eight categories measured. Sixty-five percent had already achieved better quality of service. Significant progress had also been made in improving customer experience/satisfaction (52%), cost savings (50%), uptime (44%) and the ability to create new revenue-generating products and services (42%). 

    Organizations that had completed their initial modernization objectives reported even better outcomes on all eight measures, notably including the ability to extract business value from data (56%) and faster time to market for new products and services (50%). 

    The findings clearly demonstrate that a modernized IT ecosystem is a core building block of business transformation. Whether it’s spinning up a new service or application quickly, doing a deep data dive to identify new market opportunities or using artificial intelligence to improve sales forecasts or warehouse operations, it’s essential to have the horsepower, agility and advanced data analysis capabilities to do the job.

    The survey of CIOs, CTOs, CSOs and IT directors working at organizations with an average of 29,294 employees also revealed a wide range of details about the status of IT modernization efforts. Let’s look at some examples.

    Progress Made

    Fifty-six percent of the enterprises surveyed have either achieved initial IT modernization objectives or have made significant progress toward doing so, while 19% have made moderate progress and 26% are in the beginning stages. Interestingly, even those in the earliest stages are pursuing emerging technologies such as AI, machine and/or deep learning (43%), automation to support scale-out and other cloud strategies (37%), cloud native application development (35%) and public cloud container services (35%). 

    Projects Derailed 

    Despite this progress, the road to IT modernization can be bumpy. Forty-one percent of survey respondents reported having delayed or abandoned some of their 2019 IT modernization initiatives. The top reasons cited were competing priorities (46%) and lack of a clear roadmap or strategy (45%). Other causes included data security concerns (39%), inadequate in-house expertise (38%), poor preparation (29%) and outdated processes or tools (27%). 

    Shifting Cloud Strategy

    Whether they have just embarked on their IT modernization journey or have made significant progress on their roadmap, organizations continue to grapple with optimizing their cloud strategy. The survey showed that:

    • Ninety-two percent of survey respondents increased workloads deployed in the public cloud and 91% in the private cloud in 2019, reflecting the ongoing increase in cloud adoption as well as migration from one platform to another.  
    • Eighty-nine percent switched or planned to switch from an all-private or all-public cloud strategy to a hybrid cloud approach – and 87% adopted a multicloud approach using more than one public cloud provider – as they attempted to find the right path for their cloud needs.
    • Eighty-four percent moved select workloads from a public cloud to an alternative cloud or non-cloud location, suggesting a failure to perform appropriate cost modeling, workload/platform alignment and other due diligence before the initial move.

    Poor Public Cloud Cost Controls

    More than two-thirds of survey respondents reported that public cloud costs exceeded their expectations, with cost overruns for roughly half that group ranging from 51% to 100%. Most of the causes can be traced to inadequate due diligence, governance or cloud optimization efforts, often due to a lack of in-house expertise in these areas. Examples include: unexpected data egress charges, subscribing to more cloud resources than required, failure to take advantage of vendor volume discounts, lack of knowledge to analyze monthly cloud costs and failure to optimize cloud workloads to extract maximum value from cloud platforms.

    Managed Services

    Adoption of managed services is widespread at every stage of the IT modernization journey, with an average of 95% of respondents outsourcing one or more IT operating environment functions to a managed services provider and 84% outsourcing cloud management. 

    Top Challenges Faced

    Governance is the number one modernization challenge in 2020, according to survey respondents, with new strategies and processes required to ensure control over areas ranging from cloud deployments to continuous integration and continuous delivery (CI/CD), automation and orchestration, and infrastructure as code. Optimizing and managing the centers of data that are replacing the traditional data center ranks as number two, with workloads located on-premises and in multiple clouds as well as on the edge.

    At the same time, most IT organizations have long-standing cultural and technological norms that need to change in order to move modernization initiatives forward. Hurdles cited elsewhere in the survey range from IT silos to outdated processes and tools, understaffed or underskilled DevOps teams and lack of enabling technology for containerization and automation.

    These challenges also need to be overcome in order to take full advantage of today’s technology to drive innovation, business transformation and the competitive edge that can help businesses both survive and thrive in today’s economy.

  • Should I Stay or Should I Go? A Cloudy Decision

    Should I Stay or Should I Go? A Cloudy Decision

    If you’ve been operating in the cloud for some time now, chances are your business has changed since you first made that move and particularly during the current climate. Has your cloud usage grown considerably — and your OpEx costs? Is that just the cost of doing business in the cloud?

    It doesn’t have to be. Here’s how you can rationalize your infrastructure and determine if there are cloud expenses you can reclaim and even if it makes sense to move some of your cloud deployments into colocation.

    The rush to the public cloud has now slowed as organizations realized that it is not a one-size-fits-all solution. The main issue is the lack of deep visibility into the performance of applications provided by the host. Our own research has recently revealed that 32% of public cloud resources are currently under-utilized, and without proper direction and guidance, this will remain the case. What is needed is real-time data and intelligent recommendations to lower costs and assure performance.

    In order to optimize cloud resources, a third-party AIOps based resource is needed. This will provide an independent and granular view of how applications are using capacity and if it is right-sized. In addition, it will monitor the performance of the applications in real-time and provide metrics and analytics to eliminate bottlenecks. The allocated capacity can also be monitored to ensure an accurate match to workload requirements via real-time performance data.

    Although the major hosts provide cost optimization tools, these are not very accurate. Analysis of billing and how it matches capacity over time — as well as in real-time — is what is needed for the cloud to remain a vital part in IT infrastructure. Armed with this information you can plan capacity purchases and discover wasted spend. By using a single platform for cloud management, you can monitor your infrastructure, plan capacity and eliminate performance risks. Performance bottlenecks can be predicted before they affect clients and SLAs with multi-conditional alerting powered by advanced anomaly detection.

    Cloud solutions are not only publicly provided by the likes of AWS and Azure. Colocation is also a strong option where your applications are managed on your behalf by a system integrator. This is increasingly becoming a stronger option for more business-critical applications. But to determine which is best for you, you need to start with the facts. 

    The cloud promises IT organizations unprecedented value in the form of business agility, faster innovation, superior scalability and, most importantly, cost savings. For many organizations, it is at the core of their IT digital transformation strategy. It is a disruptive force that requires application workload behavior knowledge, careful planning and collaboration from well-informed, trusted advisors.

    As a first step, enterprises frequently target a subset of their less critical on-premises applications for migration to the public cloud. Typically, organizations will take one of two paths to the cloud:

    1. Going Cloud Native. Rewrite your application to use resources offered by a cloud provider.
    2. Lift and Shift. Very minimal or zero code changes to the application. Largely, just replicate the application in the cloud.

    The faster time-to-production choice is to lift and shift the targeted applications to a cloud service provider’s Infrastructure as a Service (IaaS). In the lift and shift option, the advantage is a reduction in the cost incurred in the physical infrastructure such as hardware, floor space, cooling, security, etc., and the management of that infrastructure. Savings will differ depending on your unique computing resource needs, workload refactoring and business models.

    Even in its simplest form, IaaS migrations must be carefully planned requiring answers to some fundamental questions:

    1. Will my application perform as expected in a public cloud? (Application Fitness)
    2. How much will it cost to run my applications in a public cloud? (OpEx)
    3. Which cloud service provider is the best choice for my applications? (Cost and Fit)

    IT managers need answers to these questions before the actual migration is performed. As most internal IT organizations don’t have deep cloud expertise, the question is: Who can you trust to provide you with the answers and help you make better business decisions?

    As technology and the cloud stands to play an ever-increasing role throughout organizations, ensuring that you’re adopting the right type of infrastructure specifically for your business has never been more vital for continued success. Choosing a service that provides the answers to your key questions, before the actual migration takes place and prepares you with vital insights into your applications and workloads targeted for cloud migration, has to be an important part of the decision-making process.

    As organizations continue to battle the COVID-19 storm, understanding the product that will overhaul your IT infrastructure, before you fully buy into it, is going to provide the confidence and assurance you need to make that decision a little less cloudy.

  • OpenStack Delivers Ussuri Update

    OpenStack Delivers Ussuri Update

    The OpenStack community today officially released Ussuri, an update to the cloud management framework that tightens integration between components including the ability to automatically provision bare-metal servers using the Ironic IT automation framework built for that purpose.

    In addition, the community has added IPv6 support to the Kuryr project for integrating OpenStack with container networking and support for the CRI-O image specification for Kubernetes clusters within the Zun container runtime project. As a result, IT teams can now employ Zun-created pods on Kubernetes clusters that can run Kata containers being developed under the auspices of the OpenStack Foundation.

    Jonathan Bryce, executive director of the OSF, said support for OpenStack remains strong with more than 1,000 developers from 188 different organizations making contributions to Ussuri. More than 24,000 code changes have been made to OpenStack in this release. According to 451 Research, the OpenStack ecosystem is on track to be valued at $7.7 billion by 2023.

    Most OpenStack deployments have been on top of virtual machines. However, as interest in bare-metal servers to run platforms such as Kubernetes has increased, so too has interest in employing OpenStack to automate the provisioning on that infrastructure.

    At the same time, the relationship between Kubernetes and OpenStack remains complex. Many organizations prefer to deploy Kubernetes on top of virtual machines to ensure isolation. Others view Kubernetes running on bare-metal servers as a way to eliminate the need for virtual machines altogether. It’s too early to say how that debate will play out but for now most instances of Kubernetes are deployed on virtual machines. The issue is whether to deploy Kubernetes on one of several open source virtual machines or employ commercial virtual machines from VMware that have been widely adopted in enterprise IT environments.

    The OSF is also trying to drive the development of Kata containers, which will enable IT teams to employ a container runtime on top of a lightweight virtual machine to achieve isolation between workloads. Bryce said IT teams should expect to see a significant upgrade to the Kata project that will, among other things, make the runtime easier to deploy.

    Investments in OpenStack over the last decade have been substantial, so it’s unlikely many organizations that have adopted it are going to abandon it anytime soon. However, in greenfield environments many organizations are considering rolling out next-generation cloud-native applications based solely on Kubernetes. The OpenStack community has already signaled its intent to foster as much interoperability as possible with Kubernetes, which is developed under the auspices of the Cloud Native Computing Foundation (CNCF).

    In the grand scheme of OpenStack history, it’s not likely Ussuri will be remembered as a major update. However, it does serve as a reminder of how active the OpenStack community remains, especially as telecommunications providers continue to rely on the cloud framework to automate the provisioning of both 4G and 5G networking services.

    In the meantime, enterprise IT teams that have embraced OpenStack as well should expect to be employing it to provision infrastructure to run both monolithic and microservices-based applications for years to come.

  • Multi-Cloud Cost Optimization For The Enterprise

    Multi-Cloud Cost Optimization For The Enterprise

    Multi-cloud is an increasingly popular approach for deploying enterprise computing assets. But, in the same vein, managing cloud costs has become a huge challenge. Whilst public cloud continues to grow in popularity, there are many factors that can increase a cloud bill that needs to be taken into consideration. A smart cloud cost management strategy certainly helps to avoid any unwanted billing surprises. Enterprises progressing through their cloud adoption need one in place to control their spend.

    The benefits of cloud infrastructure—scalability, control, security, etc.—are easily seen, but there are challenges, too. Perhaps the biggest challenge of cloud cost management is the difficulty that organizations have in tracking and forecasting usage— these uncertain budget costs can be a massive cloud management pain point. The ability to scale up and down on demand has allowed resource procurement to transition from sole ownership of the finance or procurement team to stakeholders across IT, DevOps and others. Procurement is now in the hands of a group of cost-conscious stakeholders who are responsible for understanding, managing and optimizing costs.

    How much will the public cloud cost? You should begin your cloud cost management strategy by looking at the public cloud providers’ billing models—just like any other IT service, the public cloud can introduce unexpected charges. How much storage, CPU and memory do your applications require currently? Which cloud instances would meet those requirements?

    Then, it’s a question of estimating how much those applications would cost in the cloud and comparing these figures to how much it currently costs you to run them on-premise. If you plan to use multiple public cloud providers, integration and other factors can lead to unexpected fees—try and plan application deployments to see where you might be liable for extra costs. 

    Initially, it seems that most vendors offer similar packages and prices—when you examine them in detail however, perhaps one vendor has a much lower price for certain types of workloads. Understand your business requirements before committing to a cloud vendor, and avoid vendor lock-in. Moving workloads from one cloud vendor to another can sometimes be difficult. If you don’t do your due diligence here, it can be subsequently too difficult to migrate applications or workloads after they are in production.

    Confronting Cloud Costs

    You must first identify waste by uncovering inefficient use of cloud resources. Cloud cost management is not a one-and-done process, but you can make a start saving money on your cloud infrastructure costs if you address key areas that account for the majority of wasted cloud spend and budget overruns.

    Visibility

    Ensure teams have the direct ability to see what they are spending. It’s easy to get carried away spinning up services, unless you know exactly what you are already spending. Identify what you have, and who owns it. Tag resources with user ownership, cost center information, product name and others to give you a better handle on where the spend originates. This information can be used to track usage through detailed billing reports.

    Budgeting

    Once you have a handle on what your spend is, set budgets per account. Doing this after establishing a baseline ensures that you are setting practical and realistic budgets that are based on the actual usage. Look to whitelist instance types (RDS & EC2) to only allow instances of specific types, classes or sizes.

    Manage Storage Lifecycle

    Ensure that you are rotating logs and snapshots regularly and backup and remove any storage volumes that are no longer in use. Ensure that you are using only one logging configuration and have added additional ones only when absolutely necessary. Also, ensure that sandbox or trial accounts are only utilized for exploration purposes and for the duration committed.

    Use Containers

    Another technological solution that can help to reduce operating expenses is the use of containers. Often used by IT teams taking DevOps approaches, containers package applications together with all their dependencies, making them easier to deploy, manage and/or migrate from one environment to another. Containers can also be more cost-effective on one hand but can cause more complexity, and therefore increase costs, if built in the wrong way.

    Review Regions

    Prevent staff from provisioning unapproved virtual instances from the marketplace that include software license costs, or from using specific OS or DB engines from vendors with whom you do not have enterprise agreements in place or are too costly to run at scale. Review in which regions you have services running. The cost of services per region can vary as much as 60%. You need to ensure you are balancing the need with running services in a given region with the cost of doing so. You can use instance scheduling to start and stop instances on a planned schedule. Shutting down environments on nights and weekends can help save you 70% of runtime costs. Look to determine which environments need 24/7 availability, and schedule the rest.

    Use a Cloud Cost Management Vendor

    Many organizations decide that tackling these cost optimization chores on their own takes too much time and skill. Instead, they leverage services from reputable cloud cost management vendors. Cloud cost management is one of the major pain points organizations confront when migrating to the cloud—cloud costs are difficult to estimate without some kind of assistance, due to the complexity of cloud infrastructure.

  • Self-Service Portal From env0 Reins in Public Cloud Costs

    A platform that provides IT teams with a self-service portal through which they can both control access to and the cost of cloud resource consumption is now available in beta for free from env0.

    Company CEO Ohad Maislish said that while many organizations have implemented self-service portals to control who can access resources on public clouds such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), it’s apparent more workloads will be heading into the cloud in the wake of the COVID-19 pandemic to make organizations more resilient. As a result, there’s now a lot more sensitivity to cloud costs.

    Rather than relying on estimations or manual tagging, Maislish said env0 allows IT teams automatically tag infrastructure in a way that ties cloud resources to a predetermined budget using an engine designed for that purpose. All too often, organizations wind up spending a lot more on public cloud resources than planned simply because there is no way to track spending in real-time, he noted.

    In addition, it is common for organizations to find themselves being billed for “phantom workloads” that are created when developers forget to de-provision virtual machines, for example. The env0 platform provides automatic shutdown and time-to-live (TTL) options to eliminate that issue, said Maislish.

    Env0 is fresh off raising $3.3 million in funding. The env0 platform, expected to be generally available in the fall, also makes available policy controls for managing passwords, keys and tokens along with role-based access controls.

    Prior to the COVID-19 pandemic, there was a tendency for organizations to not pay a lot of attention to cloud costs. Achieving faster rates of building and deploying applications was considered a much higher priority. Most organizations will continue to put a premium on delivering applications faster. However, achieving that goal will be weighted more carefully against the total cost, especially as finance teams start issuing stricter cost mandates. In many organizations, the unfettered access to cloud resources that developers once enjoyed is likely to be more constrained.

    Of course, env0 is not the only platform promising to help organizations rein in cloud costs. However, it has combined access and financial controls in a way many organizations have been unable to achieve. In fact, the biggest challenge when it comes to containing cloud costs may very well turn out to be the will to enforce controls on developers who previously had a wide amount of latitude.

    It’s difficult to assess right now at what rate applications will be moving into the cloud. Many organizations may decide to lift and shift monolithic applications into the cloud as the first step toward making their IT environments more resilient. Others may accelerate the rate at which they are building and deploying new applications as once nascent digital business initiatives are transformed into business continuity strategies. Whatever the motivation, the days when many developers could spin up a virtual machine in a public cloud almost at will are most likely coming to an end.

  • Embracing the Journey to Public Cloud

    Embracing the Journey to Public Cloud

    One of the fascinating competitions in today’s business world is the one between the digital disruptors—companies whose business vision is rooted in technology and driven by the cloud—and the so-called incumbents.

    One sector where this competition is particularly intense is financial services. In this sector, the digital-first companies typically don’t compete with banks and other financial institutions directly. Instead, they target specific functions based on a clear—and often data-driven—understanding of what customers want. This strategy has proven particularly successful with millennials. For example, until recently the norm for giving money to a friend or family member was to write a check. Now, almost two-thirds of 20- and 30-year-olds use payment apps, such as Venmo.

    In healthcare, a different pattern is emerging, one where digital-first giants either buy or innovate their way into the sector. Examples include Amazon’s billion-dollar acquisition of the online pharmacy PillPack and the new Apple Watch, which is capable of taking electrocardiograms.

    Whatever the sector, digital disruptors have one characteristic in common. They leverage the capabilities of the cloud to the maximum extent possible. A shift in power toward digital-first companies is underway, and the cloud plays a major role in helping these companies establish themselves.

    Many incumbents are just now taking their first steps on the journey to the cloud, and still working on the challenges involved in migrating their existing legacy applications to more scalable and agile public cloud environments. While they’re engaged in this process, digital insurgents are already exploiting the full potential of the cloud to deliver solutions that meet emerging customer needs associated with today’s evolving lifestyles.

    In highly regulated industries, such as financial services and healthcare, major brands will not necessarily see an immediate decline in their customer base, nor profits. Nonetheless, digital-first companies are capturing millions of customers annually, and this growth poses a considerable challenge over time. Embracing the journey to public cloud is crucial for legacy enterprises.

    The most successful cloud-based disruptors use experimental sandboxes as a critical component of development. The public cloud can drive progress toward almost any business goal involving IT—operational transformation, new market penetration, new product launches, automation.

    Digital transformation to the public cloud is also the only way companies can leverage storage scalability and the essential innovations of the open-source community. There are still lingering concerns among executives in highly regulated, data-sensitive industries concerning privacy and regulatory compliance, and these can lead to hesitation. The face is, public clouds have been in place for over two decades now, and their security is often superior to older on-premise security. Incumbents can, therefore, tap into the public cloud to ensure safety for mission critical workloads.

    To accelerate the transition to the public cloud, consider the following best practices.

    Learning to Fail Fast and Learn from Experience More Quickly

    The Silicon Valley maxim to fail fast may run counter to incumbent corporate culture, but it is the best path to success in the new digital reality. The key is being able to learn from failures quickly and adjust accordingly.

    Partnering for Progress

    A digital native approach to business is often lacking in the corporate culture of incumbents. Cloud partners that have a digital disruption in their DNA can play an important role in driving cultural renewal at every level of the organization. A reliable cloud service partnership can accelerate concepts, pilots, staffing and other mechanisms designed to deliver value quickly and securely.

    Re-Examining Compliance Processes

    Operations should be streamlined to transform enterprise IT to be well-suited for the cloud. Companies can apply artificial intelligence to supplement human intervention, and encourage cloud adoption among employees. First, building a solid foundation, then working your way up, enables businesses to make important changes that transform the enterprise into an environment that is compliant by design.

    Successfully competing with digital natives means using the cloud to find new opportunities to streamline and better comprehend customer needs and behaviors. It also means being unafraid to change time-honored business practices. At the same time, in highly regulated and data-sensitive industries, compliance and security must be prioritized. Cloud transformation has quickly become vital for companies in all sectors and represents an essential foundation for future business success.

  • Mission Makes AWS Expertise Available for Free

    Mission Makes AWS Expertise Available for Free

    Mission, a provider of managed services for the Amazon Web Services (AWS) cloud, this week announced it will make its cloud optimization expertise available free of charge for any IT organization that acquires AWS licenses through it.

    Alex Beal, director of product for Mission, said as cloud sprawl continues to be an issue, many internal IT teams simply don’t have the expertise required to rein in those costs. However, rather than charge extra for the expertise Mission will now make its tools and consultants available for free under the auspices of the Mission Cloud Foundation service to any organization that employs Mission to acquire AWS licenses, he said, noting every Cloud Foundation customer will get access to a designated Mission Cloud Analyst who will provide regular account reviews and guidance on implementing best practices.

    Mission can provide the free service because it acquires licenses from AWS at a lower cost. Effectively, AWS is paying for the services being provided by Mission, said Beal.

    As more workloads move into the public cloud, IT teams are struggling to navigate a complex mix of service levels from AWS that range from spot pricing options to reserved instances that can be licensed for specific periods of time at a deep discount. However, determining which workloads lend themselves best to various AWS pricing options can be challenging to determine, especially for developers who spin up virtual machines without consulting with internal IT teams. Collectively, organizations are wasting millions of dollars each year because of suboptimal usage of public cloud resources. Beal estimated that the average IT organization is wasting about $5,000 a year on cloud infrastructure resources that could be better allocated to other IT initiatives.

    Beal said Mission will work with those internal IT teams to identify unused resources and rightsizing candidates, set up budget alerts and recommend better options for specific types of workloads using a combination of monitoring tools from third parties such as CloudHealth and one developed by Mission. Those monitoring tools are also employed to enforce budget constraints and run security checks.

    Mission Cloud Foundation also includes tools to reallocate charges, reference purchase order numbers and set up automated custom reports.

    Most IT organizations could develop much of this expertise on their own. However, Beal said most IT teams also have better things to do with their time that add more value to their organization. Instead of acquiring licenses direct from AWS, Mission is making a case for an alternative approach that provides a level of service and support that AWS generally only provides to Global 2000 customers.

    Other managed services providers (MSPs) may or may not also provide tools and expertise free of charge. Savvy IT teams, however, may soon force the issue. After all, while public cloud represents the most widely employed form of IT infrastructure as code, from a cost perspective it’s also clear public clouds can also quite easily become too much of a good thing.

    — Mike Vizard