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Tag: AWS Cloud

  • TidalScale Enables Hot-Swapping of Failed Servers

    TidalScale Enables Hot-Swapping of Failed Servers

    TidalScale has updated its namesake software for automating server management to include the ability to detect and prevent impending failures and enable IT teams to hot-swap another server.

    Version 4.1 of TidalScale also adds server wear leveling and preventative health checks that identify servers that should be replaced based on their remaining estimated life span.

    TidalScale CEO Gary Smerdon said that capability is especially critical given the high rate of DRAM memory failure that results in a high rate of downtime caused by server failures. The latest update to the company’s software-defined server management software reduces the failure rate in on-premises or cloud computing environments by a factor of 100 to ensure 99.999% uptime, he said.

    The company also announced that its software is now available on the Amazon Web Services (AWS) Marketplace.

    TidalScale employs machine learning algorithms to aggregate and virtualize CPU cores, memory and I/O across servers to present operating systems with a single software-defined server. That makes it possible to hot-swap individual servers to ensure availability.

    The single biggest cause of downtime in IT environments is memory failures; they are now 100 times more likely than they were a decade ago, noted Smerdon. In most cases, the root cause of the issues is the demands of modern applications running on legacy infrastructure that was not intended to support the latency requirements of those applications, he added.

    That issue can be especially acute in cloud computing environments where infrastructure is often shared by multiple applications, said Smerdon.

    It’s not clear at what rate cloud service providers are replacing legacy server infrastructure, but the ability to determine when to replace infrastructure gives IT teams an added measure of control over servers regardless of where they are deployed. The biggest issue, of course, is not so much replacing a server as it is determining which one actually failed. It often takes longer to identify a failed server than it does to bring a new one online.

    TidalScale is made available by both cloud service providers and manufacturers of servers used in on-premises IT environments, but it needs to be configured and deployed by an IT team. The overall goal is to not only increase system availability but also reduce the total cost of IT by managing infrastructure more efficiently across the life span of a server, said Smerdon. Some IT teams routinely replace servers at specified intervals, regardless of actual usage, to avoid downtime. TidalScale enables IT teams to determine which servers to replace based on the actual wear within the context of a self-healing server farm, he noted.

    Given all the things that might potentially go wrong in an application environment, not having to worry about server failures should enable DevOps teams to spend more time optimizing application performance.

    In theory, of course, modern applications based on microservices should be able to reroute calls to application programming interfaces (APIs) anytime a server becomes unavailable. However, over time it’s not uncommon for single points of failure to emerge as applications are updated. In the meantime, the majority of applications running today are based on legacy monolithic architectures that are much more susceptible to server failures that, unfortunately, are still far too common.

  • Majority of Organizations Now Adopt Multi-Cloud

    Majority of Organizations Now Adopt Multi-Cloud

    As IT’s digital footprint grows, its cloud footprint is rising both in size and complexity. As a result, most organizations have matured into multi-cloud operators. A multi-cloud approach empowers different divisions with the autonomy to select the right computing environment for their needs. It also enables a lift-and-shift ability to port workloads across cloud service providers (CSPs) when needed. Adopting a multi-cloud model could bring performance benefits, cost savings or better scalability, all while encouraging a more vendor-neutral stance.

    We’re in a multi-cloud world. A recent HashiCorp study found three out of every four organizations are already multi-cloud. This is a staggering increase from just a few years ago when mono-cloud was more accepted, and operators had zombie-like allegiance to AWS. The uptick in multi-cloud signals the maturity of offerings at other CSPs, like Azure and GCP. It also signals differentiation among clouds as each hones in their unique value propositions.

    HashiCorp’s inaugural State of Cloud Strategy Survey offers some very clear results about the state of multi-cloud adoption. Below, I’ll review major takeaways from the report to better understand the state of multi-cloud adoption. To sum it up, large organizations tend to benefit most from multi-cloud adoption, as there are still significant roadblocks to truly reaping a sizable return from a multi-cloud status. Yet, more infrastructure automation may help companies of all sizes respond to multi-cloud complexities.

    The Multi-Cloud Era

    DevOps truly operates in a multi-cloud era. The report revealed 76% of organizations are already multi-cloud; that leaves only one in four companies leveraging a single cloud. And, that trend won’t stop—within two years, 86% predict they will be multi-cloud operators. The study also confirms that the larger a company is, the more likely it will adopt multi-cloud—94% of large enterprises with 5,000 or more employees are multi-cloud.

    So, what’s driving this cloud fragmentation? Well, 34% of respondents cite digital transformation as a top driver for multi-cloud adoption. In the race to meet new digital innovation demands, multi-cloud has emerged as a strategic force. To enact this rapid change, many organizations are investing in a cloud center of excellence (CCoE) to guide cloud transformation efforts. A CCoE is most common within large companies with a cloud budget of $5 million or more.

    Speaking of budgets, cloud spending is going through the roof. In 2020, only half of companies met their projected cloud spend, and 39% of companies overspent their allotted cloud budgets. As I’ve covered before, cloud-native costs are notoriously difficult to identify and trim. Without the proper guardrails to manage spending, surprise data egress fees or hidden server costs can strain the cloud checkbook. As it stands now, 40% of companies lie in the $100,000 to $2 million per year range, and 6% of enterprises are investing $50 million a year or more into multi-cloud. This spending will likely increase in the coming years as cloud reliance expands.

    Enterprises Benefit Most

    So, which clouds are companies using? If we compare cloud adoption, AWS is a clear market leader; 88% of companies use AWS, 74% use Azure and 61% use GCP. AWS’s hegemony is not expected to fade in the next two years. Yet, while AWS usage will remain the same, competing CSPs will experience modest increases. This is likely due to Azure and GCP making gains in geographical zones outside North America, such as Asia-Pacific and Africa.

    In terms of technology used in cloud environments, open source software (OSS) is a popular choice. Cloud-native open source projects, such as Kubernetes, OpenStack and Terraform, have taken on a life of their own, with vibrant community support. However, not all shops build upon OSS and run it themselves. Somewhat ironically, we’re seeing more managed OSS emerge. One stand-out area is provisioning, where 42% of organizations build with open source and run it themselves.

    On the whole, multi-cloud is working at most enterprises, with 53% of survey respondents saying multi-cloud has helped achieve their business goals. The top benefit of multi-cloud is digital transformation, at 34%. This is followed by avoiding lock-in (30%), reducing cost (28%) and scalability (25%). But multi-cloud does not treat all companies as equals; the likelihood of multi-cloud success increases as the company size increases. Less than half (42%) of small companies say they have multi-cloud success, which jumps to 64% for large enterprises. With fewer resources for support, multi-cloud may be less beneficial for startups and small to medium businesses. In fact, 41% of professionals say a lack of in-house skills inhibits their cloud success.

    Challenges in a Hybrid Multi-Cloud World

    An ongoing talent gap is just one potential challenge to cloud success. Just over half (51%) say cost concerns are a top inhibitor to their cloud program success. Hybrid cloud complexity is another prominent challenge, with 35% of organizations citing it as a major cloud obstacle. Many enterprises are still grappling with the remnants of legacy on-premises estates. But technical debt is not the only reason for hybrid modalities. Surprisingly, large platforms even have constructed their own data centers or used colocation as an intentional strategy.

    Security is a top cloud inhibitor, according to 47% of IT professionals. The leading cloud security concerns include data protection (40%), data theft (33%) and regulatory compliance (31%). The myriad cybersecurity threats evolve each day, and cloud technologies are not immune; for example, web APIs are now a significant threat vector. A separate report found a 300% increase in malicious API traffic in the past six months. Other issues, such as exposed keys, insecure defaults and misconfigurations are known to hamper cloud-native infrastructure.

    Contrary to popular belief, nearly half (46%) of companies reported that COVID-19 has not quickened their cloud adoption. This reality could indicate that cloud migration has been planned for years, and recent adoption is only part of an ongoing trend. The study found that the pandemic did, however, accelerate things like infrastructure-as-code (IaC), container orchestration, compliance and governance and other operational factors.

    Infrastructure Automation Supports Multi-Cloud

    Multi-cloud feels like an inevitable result of accelerating cloud adoption in a more diversified market. Rising multi-cloud use is also arguably in line with Conway’s Law. As organizations develop more and more digital experiences across new verticals, the platforms and backend processes to support these initiatives will inevitably grow more and more complex.

    To mitigate some of the issues posed by multi-cloud, many organizations are turning toward increased infrastructure automation. In fact, 70% of those surveyed said infrastructure automation tools are extremely important to their organization. Of these tools, provisioning automation (75%) is the most popular kind in use. Automation for other areas, like networking (58%), security (50%) and app development (69%) follow.

    Hashicorp’s State of Cloud Strategy Survey boldly announces, “Welcome to the Multi-Cloud Era,” and its findings back up that sentiment. For further insights, you can view the results freely on this website.

  • Is AWS Cloud Per-Second Billing Boon or Bane for DevOps Engineers?

    Is AWS Cloud Per-Second Billing Boon or Bane for DevOps Engineers?

    Amazon’s introduction of its AWS services in 2006 with a per-hour billing model for compute resources was a game-changer for the IT world. Since then, AWS has taken over the cloud computing market as a leader, while broadening the range of cloud services offered every year. However, the per-hour billing business model was one of the major issues for many customers—in particular, those who had applications using EC2 for only minutes at a time.

    Recently, AWS announced support for per-second billing of its EC2 service, addressing the aforementioned concerns. Of course, this also created controversy among the per-hour supporters. While I won’t get into the pros and cons across the whole enterprise, one group in particular is affected from the new per-second model: DevOps engineers.

    Here are the top five implications for DevOps teams as a result of per-second billing:

    Autoscale without worrying about cost

    Most engineers were vary of autoscaling at will, mostly because of EC2’s hourly charges even though they might need additional compute capacity for just 15 minutes. With per-second billing, DevOps engineers don’t have to worry—it’s as simple as scaling your EC2 instance as you need to, and when you need to.

    No more custom logic for hourly batches

    Many customers use EC2 for jobs and batch processing purposes. Due to the hourly pricing, engineers have written custom logic to benchmark and constantly tune the number of nodes in their batch clusters to ensure they are cost-optimized. Per-second billing frees up headaches for DevOps engineers that are using EC2 for batch processing and job clusters.

    The need to speed up EC2 launches

    With per-second billing, it’s important to take advantage of prebaked Amazon Machine Images (AMI) for launching your EC2 instances, instead of complete configuration setup on every instance launch. This will reduce the costs for you, by saving anywhere from five to 15 minutes. It’s time to create prebaked AMIs for faster instance launches, ultimately saving costs.

    Dilemma of Lambda or EC2

    Be prepared to compare whether to use Lambda or EC2 for new workloads and applications more often than you are used to. Your benchmarking between Lambda and EC2 has become a little more dicey. The serverless lambda just got competition from EC2 again.

    Your big data just got easier

    With EMR also supporting per-second billing, your job has become a lot easier. As a , you no longer need to constantly benchmark your EMR clusters for number of nodes and job processing times to be optimized for per-hour billing.

    DevOps engineers have a lot to benefit from per-hour billing, but also much to consider when it comes to time-to-deployment and choosing a compute service. Now is the the time for DevOps engineers engineers to bring these concerns to their CIOs to make a smooth transition to the new AWS business model.

    About the Author / Vijay Rayapati

    Vijay Rayapati, CEO of cloud management platform company Botmetric, identifies himself as a technology entrepreneur, passionate about creating products, building high-performance teams, and solutions that solve real-world business issues. Vijay is a popular speaker in India and the US, and has co-authored a popular book, “Learning Big Data.” Connect with him on LinkedIn and Twitter.