devopsy.kinsta.cloud

Tag: Cloud Computing

  • Survey Sees Limited DevSecOps Progress Being Made as Vulnerabilities Mount

    Survey Sees Limited DevSecOps Progress Being Made as Vulnerabilities Mount

    A survey of 2,037 IT and security professionals conducted by the Cloud Security Alliance (CSA) on behalf of Dazz, a provider of a platform for mapping cloud computing environments, finds well over a third of respondents (38%) estimated that 21-40% of their code contains vulnerabilities, while 19% estimated 41-60% of their code contains vulnerabilities. Another 13% estimated they have vulnerabilities in 61-80% of their code.

    As a result, organizations on average have 55.5 security vulnerabilities each day in their remediation queue, with typically at least one being deemed critical, the survey finds. Overall, the average number of vulnerabilities that could be addressed is 1,025 per month, but organizations typically only address 270 within a month.

    In general, there are four phases to a remediation with each phase, on average, requiring between three to six hours so it easy to see how some organizations with limited resources can reach a point where they never catch up. The report noted that more than half of the vulnerabilities that have been remediated reoccur within a month, often because the root cause was never adequately addressed.

    Hillary Baron, senior technical director for research for CSA, said the high number of vulnerabilities that need to be regularly addressed suggested that progress in adopting DevSecOps best practices remains limited. While not every vulnerability is equally critical, it’s clear application development and cybersecurity teams are not yet proactively addressing application security issues, she noted.

    In fact, the survey found that less than a third (30%) of respondents reported there is a good working relationship between the application development teams that typically provision cloud computing environments and the cybersecurity teams that usually are held accountable for maintaining cloud security. Just under half of respondents (49%) said their vulnerability remediation teams comprised four to six members. Most respondents (60%) found it somewhat difficult to identify code owners, with an additional 24% facing moderate difficulty and 5% that found it highly challenging.

    Dazz CTO Tomer Schwartz said the more dynamic application development becomes, the bigger the DevSecOps challenge. Most organizations lacked the visibility required to proactively correlate their DevSecOps practices, he added. For example, more than three-quarters (77%) of respondents said they lacked full transparency into their cloud computing environments, and 6% had no visibility at all.

    In total, the survey finds organizations typically employ a variety of scanning and detection tools to safeguard their cloud environments, with 32% using five to six tools while another 29% report using three to four tools.

    More than three-quarters of respondents (76%) also noted that one in 10 of the alerts these tools generate is a false positive.

    Just under 75% of respondents also noted security teams spend more than 20% of their time performing manual tasks when addressing vulnerabilities, even though 83% reported using at least some automation in their remediation process. A full 61% also noted their organization is using three to six different detection tools, with nearly half (45%) considering increasing their security budgets in 2024, so it’s likely that many will be adding additional tools. In total, 22% dedicated less than 20% of their budget to cloud security, compared to 31% that allocated 21-40% of their budget and 27% that invest 41-60% of their budget to securing cloud environments.

    Unfortunately, less than a quarter (24%) said they feel very prepared for the cybersecurity threats their organization faces. Much of that uncertainty stems from knowing just how many vulnerabilities there really are in production environments and that they are being attacked with greater frequency each day.

  • Survey: Significant Shift in IaC Tool Preferences

    Survey: Significant Shift in IaC Tool Preferences

    A survey of 350 IT professionals conducted by Firefly, a provider of a platform for managing cloud computing environments, suggests usage of infrastructure-as-code (IaC) tools is evolving rapidly in the cloud computing era.

    For example, more than 40% of the respondents reported that, to some degree, they are already using OpenTofu, an open source IaC tool that was launched as a fork of the Terraform IaC in the wake of changes to the software licensing terms it is made available under by HashiCorp. Well over half said they planned to use OpenTofu in the future. That compares to 60% using Terraform today, but only just over 20% said they planned to use Terraform in the future.

    The licensing changes HashiCorp implemented only affect third-party entities within a third-party platform. However, the survey indicates the number of end users affected by that change is more substantial than anticipated. A full 56% of respondents described the changes made to the Terraform license as disruptive.

    The survey also finds there is a lot more diversity in terms of the types of IaC tools being employed, with both the IaC tools from Pulumi and the open source Crossplane framework being advanced under the auspices of the Cloud Native Computing Foundation (CNCF) also gaining traction. The report finds more than 40% of respondents are also using Pulumi, with well more than half planning to use that IaC tool in the future.

    Crossplane, meanwhile, is now being used by 40% of respondents, with 60% planning to adopt it.

    Conversely, the report also notes the number of organizations planning to migrate away from CloudFormation from Amazon Web Services (AWS) is rising. While well over 60% use AWS CloudFormation today, only a third plan to use it in the future.

    Cindy Blake, vice president of marketing for Firefly, said as organizations employ additional cloud platforms, IT teams are clearly looking for tools that make it easier to centralize the management of multiple computing platforms. That trend will only accelerate as more DevOps teams adopt platform engineering as a methodology for managing the building and deployment of applications at scale, she added.

    In fact, noted Blake, it’s already fairly common for IT teams to use two or more frameworks. The report finds 57% of respondents work for organizations that are using two or more frameworks. Overall, the report finds that more than 64% of respondents have also codified more than half of their cloud assets.

    The number of organizations employing IaC tools to programmatically manage infrastructure is only going to increase, said Blake. The report, for example, found that three-quarters of respondents either already are or plan to use IaC tools to configure software-as-a-service (SaaS) application environments. In the longer term, advances in artificial intelligence (AI) will make it simpler for organizations to achieve that goal. Open source tools such as AiAC, for example, already make it possible to leverage large language models (LLMs) to generate code. Those types of tools will eventually eliminate the need to master specific programming languages to provision IT infrastructure as code, noted Blake.

    It’s not clear how IaC tools within the context of DevOps workflow will evolve, but the one thing that is certain is that the number of types of tools being adopted has never been more diverse.

  • Self-Hosting is Dead. Hybrid is the Way to Go

    Self-Hosting is Dead. Hybrid is the Way to Go

    If I scroll back through my photo library, it’s astonishing how few photos I have from before 2004. And in 2006 (and probably for a few years after that), I still kept every photo I had on the hard drive of my laptop computer. If I lost that laptop, those photos would be gone forever. At some point, I went through the process to back them up to an external hard drive.

    And then along came the cloud. At some point, I could give my pictures to Apple or Google and not worry about backups. There was always the possibility they could have a critical disaster and lose every wedding photo I had or all the early pictures of my kids (it could still happen). But as a father who takes way too many pictures of my kids, I no longer maintain an external drive of backups because the several terabytes of photos I have are sufficiently stored and backed up in the big cloud provider I pay to handle it. The SaaS solution in a cloud backup was more than sufficient for me.

    Camera Rolls and Data Centers

    Likewise, it wasn’t that long ago that any meaningful internet presence required a company to have a large server room and host their own infrastructure. That meant racks and racks of computers and an enterprise internet connection to make sure customers could access those racks of computers. Most services you relied upon had to be close by physically to deal with latency and ensure the experience worked for your customers.

    Logging and metrics were kept locally, as were backups. I’m sure I’m not the only one who remembers swapping out big tape drives for daily backups and storing them in large plastic bins somewhere we really hoped wouldn’t flood.

    If you were using a significant piece of software, you would need to self-host that software for many reasons—but the biggest reason was that shared infrastructure wasn’t a reality yet. There was no way to share hardware and no meaningful way to share software in a multi-tenant environment.

    IaaS, the Cloud, Automated Backups and SaaS

    Today, the infrastructure-as-a-service (IaaS, or “Cloud”) providers are offering everything from email hosting to Kubernetes-as-a-service (KaaS), from serverless to logging. They even make sure the software that enables your edge computing is obscured from you and managed by them (backups are automatic! And included in the price! And happen without a single person touching a tape drive!). This frees us up significantly to spend time shipping code and bits instead of fiddling with wires, CPUs and drives. It’s like shipping your photos to a SaaS photo storage provider—it takes the headache and the worry away. Yet when companies move to the cloud, many maintain the “old way” of doing things because they haven’t adjusted to the new reality yet.

    There is now no need to self-host your own email service. The cloud provides it, or you can use a third-party service that runs in the same cloud. Data proximity is no longer a concern, and latency won’t suffer. Similarly, there is no need to self-host your backups or even your logging service—because the cloud will provide it, and similarly, a third-party service is no longer a latency concern—that third party is probably hosted by the same cloud in the same region.

    This move to the cloud and shared infrastructure has been a game changer. SaaS is the name of the winning solution. Still, there will always be some companies with compliance or security needs that want to maintain data residency, just like there will always be people with such sensitive data or important family photos that no matter how safe and reliable the cloud is, they’ll insist on self-storage for photos and backups.

    The Hybrid Solution

    That’s why a hybrid cloud is the future of cloud-native solutions for complex enterprise applications and data. You host the data, but the SaaS provider hosts the application. The data stays under your control, but the SaaS firm updates the application regularly. Today, a large enterprise may have five engineers just to handle a self-hosted version of a logging app. At $180,000/year per engineer (a reasonable tech salary today), that’s almost a million dollars per year to maintain a software product that the vendor will gladly maintain for you.

    This is a simple shift, but it has only become a reality recently due to advances in technology, the things the cloud has enabled and the increased headache—now seemingly unnecessarily dated—of self-hosting (and then upgrading and patching) software built by a third party.

    With a hybrid cloud offering, you’re always using the latest version of the software because you’re using the software hosted and updated by the SaaS provider. There is no need to self-update, scale up or down or security patch a self-hosted install. The SaaS provider handles the compute and scaling required to make the service run smoothly. And you get the best of both worlds — zero software maintenance while still keeping your data in your own hands.

    To hear more about cloud-native topics, join the Cloud Native Computing Foundation, Techstrong Group and the entire cloud-native community in Paris, France at KubeCon+CloudNativeCon EU 2024 – March 19-22, 2024.

  • Akamai Launches Gecko Edge Computing Services

    Akamai Launches Gecko Edge Computing Services

    Akamai Technologies today launched an initiative that promises to make it simpler to centrally manage and deploy application workloads on edge computing platforms.

    Shawn Michels, vice president for product management for cloud computing Akamai, said a Generalized Edge Compute (Gecko) offering leverages the global points of presence (PoPs) that Akamai uses for its content delivery network (CDN) to now deploy application workload managed via the Linode cloud service the company acquired in 2022.

    At the core of this offering is a set of virtual machines that enable a full stack of application software to be deployed in an edge computing environment to eliminate latency that would otherwise be encountered when transferring data to a cloud computing environment. The ultimate goal is to provide IT organizations with a federated set of services they can employ to process data where it makes the most sense based on performance requirements, said Michels.

    For example, applications infused with artificial intelligence (AI) will need to be able to invoke enough compute resources to run inference engines at the edge, while other less compute-intensive application workloads are best deployed in cloud computing environments, he noted.

    Michels added that rather than locking IT teams into a specific architecture, Akamai is committing to meeting IT organizations where they are, including adding support for containers running on Kubernetes clusters in its PoPs later this year.

    Akamai has more than 4,100 points of presence around the globe. With the acquisition of Linode, Akamai added a set of cloud computing services to compete directly against hyperscalers such as Amazon Web Services (AWS), Microsoft and Google by making cloud services available at a lower cost at a time when more organizations than ever are concerned about the total cost of IT.

    In its first phase of Gecko, Akamai will provide access to virtual machines in 100 locations by the end of the year. Akamai has already deployed Gecko servers in Hong Kong SAR; Kuala Lumpur, Malaysia; Querétaro, Mexico; and Johannesburg, South Africa, as well as in cities without a concentrated hyperscaler presence, including Bogotá, Colombia; Denver, Colorado; Houston, Texas; Hamburg, Germany; and Marseille, France. Deployment of a tenth Gecko region this quarter is planned for Santiago, Chile. Akamai is committing to adding hundreds of cities to its global cloud computing footprint over the next several years.

    In the longer term, Akamai also plans to add automated workload orchestration to make it easier for developers to build applications across hundreds of distributed locations.

    More workloads than ever are being deployed at the network edge as IT teams look to deploy software closer to the point where data is being created and consumed. That will require extending the reach of existing DevOps workflows to edge computing environments that will be based on everything from x86 and Arm processors to graphical processor units (GPUs).

    The challenge, as always, will be finding a way to effectively manage those workloads when the IT teams responsible for them are often physically located thousands of miles away.

  • Scrimmage for Control: On-Premises Vs. SaaS in the Observability Super Bowl of 2024

    Scrimmage for Control: On-Premises Vs. SaaS in the Observability Super Bowl of 2024

    Observability means data. It encompasses a set of practices and tools designed to track the performance and health of software applications, providing insights into the “why” behind system behaviors, not just the “what.” At its core are data pillars we’ve learned how to work with and hopefully get the most out of—metrics (quantitative data on system performance), logs (recorded events within the system) and traces (detailed views of request paths through the system) that offer a comprehensive view of the system’s operation in real-time. SaaS is where the industry has been turning towards for the past decade. It’s easy to operate and upgrade and takes away maintenance and manpower requirements.

    But, using a SaaS solution where data is stored on the vendor’s infrastructure can be compared to playing a football game at your opponent’s home field. Your team does not own the field and must play along with conditions that are outside their comfort zone. While your team can still strategize, execute plays and score points, the control over the playing environment, including the surface, lighting and even some rules, lies with the owner of the stadium (in this case, the SaaS vendor).

    You don’t get the home-field advantage and the comfort of your familiar surroundings, and you also can’t control the audience’s shouts and cheers in the stands across the arena.

    Just as a visiting team must trust the host’s management of the stadium and adapt to its conditions, organizations using SaaS solutions entrust their operational data to third-party vendors. They must trust its data protection policies and privacy agreements to ensure that the organization’s data is handled securely and in compliance with relevant regulations.

    And even more importantly, they have to adhere to its hosting costs.

    Let’s Leverage the Home-Field Advantage

    The alternative is clear: While playing on your own field, you, the coach—hell, the entire team—know this field by heart, and you know best how to keep and enforce your own rules.

    Just as a football team controls the ball and decides on the play, having on-premises data means a company or organization keeps its data within its infrastructure, offering direct control over its storage, management and security. The organization decides how to deploy, use and protect this data and even how to manage the tradeoff of data costs.

    The downsides? Playing on your home field at all times means you’re running slower than the world out there. You’re not quick to update your software to the newest common practices and you’re tasked with maintaining another stack—your observability stack—on top of building your product, which serves your users.

    There’s Another Way. Play the Data on the Scrimmage Line

    In football, the scrimmage line is the imaginary line across the field where the ball is placed at the start of each play. This line serves as the point of engagement between the two opposing teams, with specific rules governing how players can position themselves and how the play begins.

    What if we can keep the data on-premise, in the home field, a little like having the ball on our side of the scrimmage line, within our team’s possession and control? We have the ball, and we decide and strategize how to advance the ball or score from the position behind the scrimmage line, but we can still interact with the outside world (or the opposing team) under a set of rules to which we both adhere.

    This is exactly where observability solutions are heading: A combination of the advantages of SaaS—easy to update and maintain value, with an easy way to distribute the solution inside the organization, alongside the advantages of on-premise—data privacy, data control and full transparent and controllable data costs.

    I call this approach inCloud. It is a modern on-premises approach—data in your cloud environment, protected and controlled by the user, but still governed, managed and served with a guaranteed SLA just like the best SaaS offerings out there.

    Just like the scrimmage line in football that provides a clear boundary and set of rules for how the game is played, inCloud acts in a similar way. Data is kept on-premises, allowing the organization full control over retention, privacy and data integrations. And on the other hand, inCloud defines a set of strict rules under which a control plane is allowed to operate and pass the scrimmage line, or past the organization’s cloud borderline, to manage and access the data like a SaaS solution does best.

    So when we sit down to watch the Super Bowl this Sunday—let’s use that halftime show to think about where we’ll be taking our organization’s observability capabilities in 2024. Will the data be in our hands, crossing that invisible scrimmage line? Or will we lose to our opponent’s home-field advantage?

    May the best team win.

  • CloudBolt Commits to Applying AI to FinOps

    CloudBolt Commits to Applying AI to FinOps

    CloudBolt Software today revealed it plans to infuse artificial intelligence (AI) into the financial operations (FinOps) capabilities it provides via its IT management platform over the coming year.

    Kyle Campos, chief product and technology officer for CloudBolt, said given the inherent complexity of modern IT environments, there is a need to apply machine learning algorithms and other forms of AI to enable IT organizations to apply policies in real-time to reduce costs. That capability is especially critical in cloud computing environments where services are often invoked by developers with little to no oversight, he noted.

    FinOps is a discipline that promotes a shared responsibility for an organization’s cloud computing infrastructure and costs. Rather than having disparate procurement teams working in silos to identify and approve costs, business, financial and IT leaders establish policies and best practices for usage that are programmatically enforced. The FinOps Foundation, an arm of the Linux Foundation, has been defining a set of FinOps best practices, but many organizations still lack the discipline required to implement them. One of the major reasons organizations lack this discipline is that many of them have been allowing application developers to provision cloud resources themselves. It’s not until the bill comes due at the end of the month that finance teams realize there is an issue when there is a sudden spike in costs.

    Rather than deploying a separate platform to manage FinOps, CloudBolt is making a case for integrating a framework for managing FinOps within the same platform IT teams use to manage those IT environments. That approach makes it possible to apply FinOps policies in a way that ensures best practices for controlling costs are implemented without creating yet another silo within an IT organization, said Campos.

    Running application workloads in the cloud is fundamentally different than running them in an on-premises IT environment where costs are largely fixed. Not many developers have much of an appreciation for the additional storage and cybersecurity expenses that are generated every time a new workload is added. As a result, many organizations lack visibility into the total cost of cloud computing until the monthly bill arrives. By then, it’s too late for IT teams to have any impact on the outcome.

    In the face of ongoing economic uncertainty, more organizations are clearly moving to reduce cloud computing costs more aggressively. In an ideal world, IT teams would be able to instantly see what impact any change to an IT environment will have on costs as part of any scenario planning exercise, said Campos.

    While most organizations would like to reduce their cloud costs, it’s just as important to ensure that the bills being incurred are predictable. Finance teams don’t appreciate surprises, no matter how important an application may be. IT leaders are now being held more accountable than ever to make sure cloud computing costs meet expectations from one month to the next. The challenge now is finding a way to inject controls in IT environments long after applications have already been deployed.

  • 5 Serverless Challenges of DevOps Teams and How to Overcome Them

    5 Serverless Challenges of DevOps Teams and How to Overcome Them

    Serverless is a cloud computing execution model where the cloud provider dynamically manages the allocation of machine resources. The term ‘serverless’ might be somewhat misleading as it doesn’t mean servers are not involved. Instead, it means that developers no longer have to think about servers, even though they’re running on them.

    The idea is to abstract the infrastructure away so that developers can focus solely on the code. Functions, the units of code, are triggered by a variety of events, including HTTP requests, database events, queuing services, monitoring alerts, file uploads, scheduled events (cron jobs), and user sign-ups or in-app activities.

    The Importance of Serverless for DevOps Teams

    Serverless computing brings a paradigm shift in how applications are built, deployed and managed, directly impacting DevOps teams. The core advantage of serverless for these teams is the significant reduction in operational overhead. With serverless, the cloud provider takes responsibility for running the server, ensuring its reliability, and scaling the infrastructure. This frees DevOps teams from the routine tasks of server provisioning, maintenance, and patching, allowing them to focus more on optimizing the application’s code and business logic.

    However, this shift also demands a change in mindset and approach. DevOps teams must adapt to a more granular, event-driven architecture that serverless promotes. They need to design systems thinking about individual functions and how they interact, instead of traditional monolithic applications or even microservices. This requires a deeper understanding of the cloud environment and its services, as serverless functions are often tightly integrated with other cloud services like databases, message queues, and API gateways.

    Moreover, serverless computing introduces new challenges in areas like security, monitoring, and cost management. For instance, the ephemeral nature of serverless functions can make traditional monitoring approaches less effective, and the dynamic scaling can lead to unpredictable costs. DevOps teams need to develop new strategies and adopt specialized tools to address these challenges. Despite these issues, the benefits of serverless – in terms of agility, scalability, and potential cost savings – make it an increasingly essential tool in the DevOps arsenal, particularly for organizations looking to innovate and deploy rapidly in a cloud-centric world.

    5 Serverless Challenges of DevOps Teams and How to Overcome Them

    1. Complexity of Monitoring in Serverless

    A main challenge in the serverless world is the complexity of monitoring. Unlike traditional architectures where you can monitor physical or virtual servers, in serverless, you need to monitor individual functions. This can be tricky as you may have hundreds or even thousands of functions running simultaneously.

    To effectively monitor serverless architectures, you need to go beyond traditional methods. You need tools that can provide insights at the function level, such as AWS CloudWatch or Azure Monitor. These tools allow you to monitor metrics like execution time, error rates, and invocation counts for each of your functions.

    But monitoring is not just about gathering metrics. It’s also about understanding the relationships between your functions and other components of your system. For this, you need distributed tracing tools like AWS X-Ray or OpenTelemetry, which can provide a detailed view of how requests flow through your system.

    2. Managing Lambda Cold Starts

    One of the most common serverless challenges that DevOps teams face is cold starts. A “cold start” refers to the delay that occurs when a function is invoked after being idle for a while. This delay can significantly impact the performance of your applications, especially those that rely on real-time processing.

    The first step to managing Lambda cold starts is understanding what triggers them. Typically, a cold start happens when a new instance of your function is created, which can be due to several reasons, such as an increase in traffic, the deployment of a new version of your function or after a function has been idle for too long.

    To overcome this challenge, there are several strategies you can employ. First, you can use provisioned concurrency, a feature offered by AWS Lambda that allows you to keep a specified number of function instances warm and ready to respond to invocations. Another strategy is to design your applications to be resilient to cold starts by implementing retry logic or using asynchronous invocation when possible.

    3. Security Concerns in Serverless Architectures

    Security is a top concern for any DevOps team. In serverless architectures, you have less control over the underlying infrastructure, making it more difficult to ensure the security of your applications.

    The first step to securing your serverless applications is understanding the shared responsibility model. In a serverless environment, the cloud provider is responsible for securing the infrastructure, while you are responsible for securing your code and configurations. This means you need to pay extra attention to things like input validation, error handling and secure configuration practices.

    Another key aspect of serverless security is managing permissions. Each of your functions should have the least privileges necessary to perform its task. This can be achieved by using identity and access management (IAM) services provided by your cloud provider.

    4. Managing Third-Party Dependencies

    Managing third-party dependencies is another challenge that DevOps teams often face in serverless architectures. These dependencies can introduce vulnerabilities into your applications, affect the performance of your functions, and even increase the cost of your serverless deployments.

    The key to managing third-party dependencies is to minimize their use. Only use dependencies that are necessary for your application and regularly review them to ensure they are still needed. You should also keep your dependencies up-to-date to benefit from the latest security patches and improvements.

    When using third-party dependencies, it’s also important to understand their impact on your functions. You can use tools like AWS X-Ray or Google Cloud Trace to monitor how these dependencies affect the performance of your functions.

    5. Cost Management and Optimization

    While serverless can be cost-effective, it’s easy to rack up high bills if you’re not careful. This is because in serverless, you pay for every invocation of your functions, even if they result in errors.

    To manage costs in serverless, you need to monitor your usage closely. Tools like AWS Cost Explorer or Google Cloud Billing can provide insights into your spending and help you identify areas for optimization.

    You can also optimize costs by designing efficient functions. This means writing code that executes quickly and efficiently, minimizing the use of third-party dependencies, and managing the concurrency of your functions.

    In conclusion, while serverless technologies offer many benefits, they also present unique challenges for DevOps teams. By understanding these challenges and employing the right strategies, you can effectively manage and overcome them, ensuring the successful delivery of your serverless applications.

  • 2024 Infrastructure Tech Predictions

    2024 Infrastructure Tech Predictions

    Ganesh Srinivasan, partner at Venrock, co-authored this article.

    2023 was a rollercoaster like none other; from the death of the modern data stack sprawl to the birth of generative AI, we are only at the beginning of a new era in the ‘art of the possible.’ We guarantee 2024 won’t be a disappointment.

    With a new year approaching, it’s the perfect time for us to examine what we anticipate being the biggest developments in the year ahead. Here is what we think is going to happen in 2024:

    1. OpenAI’s Reign Challenged

    With the emerging learnings in core neural net architectures that led to the transformer and dominance by OpenAI, it is likely that their imminent release of GPT5 will be surpassed in specific performance benchmarks by a new entrant on the backs of more efficient architectures, improved multimodal capabilities, better contextual understanding of the world and enhanced transfer learning. These new models will be built on emerging research in spatial networks, graph structures and combinations of various neural networks that will lead to more efficient, versatile and powerful capabilities.

    2. Apple: The New Leader in Generative AI

    One of the most important players in the generative AI space is only starting to show their cards. 2024 will be the year Apple launches its first set of generative AI capabilities, unlocking the true potential of an AI-on-the-edge, closed architecture with full access to your personal data – showing that Apple is actually the most important company in the generative AI race.

    3. Building for Client-First

    The last decade has reflected a shift away from fat clients to server-side rendering and compute. But the world is changing back to the client. Mobile-first experiences will be required to work in offline mode. Real-time experiences require ultra-low latency transactions. Running LLMs will increasingly be required to run on the device to increase performance and reduce costs.

    4. Death of Data Infrastructure Sprawl

    The rapid growth of the data infrastructure needs of enterprises has led to an increasing sprawl of point solutions, from data catalogs, data governance, reverse extract, transform, load, and airflow alternatives to vector databases and yet another lakehouse. The pendulum will swing back to unified platforms and fewer silos to bring down the total cost of ownership and operating overhead going into 2024.

    5. Approaching the AI Winter

    Generative AI in 2023 could be best characterized as the ‘art of the possible,’ with 2024 being the true test to see if prototypes convert into production use cases. With the peak of the hype cycle likely here, 2024 will experience the stage of disillusionment where enterprises discover where generative AI can create margin-positive impact and where the costs outweigh the benefits.

    6. The Misinformation Threat

    While image and video diffusion models have unlocked a new era for digital creation and artistic expression, there’s no doubt that its dark side has not yet taken its toll. With a presidential election in the wings, diffusion models as a machine for political disinformation will emerge to become the next major disinformation weapon of choice.

    7. AI’s Real-World Breakthrough

    Coming out of the ‘field of dreams’ era for AI, 2024 will represent a breakthrough for commercial use cases in AI, particularly in the physical world. Using AI for physical world modalities will unlock our ability to change and engage with the machines and devices around us, from understanding machine telemetry for problem detection to distilling insights across thousands of real-time sensor feeds.

    8. S3: The Growing Threat to Snowflake

    AWS S3 is about to become the biggest competitor to Snowflake. With a rapidly growing ecosystem of tools emerging as the compute layers on top of S3 leverage their ultra-low costs, high availability, Availability Zone support, and new single-digit millisecond latency service, everyone’s ‘Snowflake cost problem’ is about to have a new set of attractive alternatives.

    9. The Rise of Flink and Operational Analytics

    If business analytics drove the first wave of the data infrastructure evolution, operational analytics will drive the next wave, with Apache Flink at the center of it. Enterprises will begin en masse adopting real-time and streaming capabilities to begin using data to drive operational decision making. This will create new value in areas such as logistics, financial transactions, inventory management and fraud detection.

    10. The Developer AI Stack

    Going into 2024, AI’s most significant impact in the digital world will be unlocking developer productivity. From code generation to debugging to build management, AI will unlock a new level of developer productivity that we haven’t seen since the advent of the cloud.

    If you agree, disagree or would like to share your own 2024 predictions with us, please reach out on X at @ethanjb and @gan3sh.

  • Hybrid Cloud in 2024: Trends and Predictions

    Hybrid Cloud in 2024: Trends and Predictions

    Hybrid cloud environments are becoming increasingly pivotal for DevOps teams, primarily due to their ability to bridge the gap between the rapid deployment of public cloud resources and the security and control of private cloud infrastructure. This blending of environments provides DevOps teams with flexibility and scalability, which is crucial for operating continuous integration and continuous deployment (CI/CD) in large enterprises.

    In a hybrid cloud setup, DevOps teams can swiftly deploy and test new applications in a cost-effective and scalable public cloud environment. Once the applications are ready for production, they can be seamlessly transitioned to a private cloud or on-premises environment, where they benefit from enhanced security and control. This allows DevOps teams to optimize their workflows, reduce time to market, and respond more effectively to business needs.

    The hybrid cloud also enables a more collaborative and agile working environment. DevOps teams can leverage various tools and platforms available in the public cloud while ensuring that sensitive data and critical applications are securely managed in the private cloud. This both enhances operational efficiency and improves compliance with data governance and regulatory requirements. These benefits will make hybrid cloud an indispensable asset for DevOps teams in 2024 and beyond.

    What is a Hybrid Cloud?

    Let’s start with a brief definition. A hybrid cloud is a computing environment that combines a public cloud and a private cloud by allowing data and applications to be shared between them. This combination allows businesses to enjoy the best of both worlds, leveraging the scalability and cost efficiencies of public cloud platforms while enjoying the security and control offered by private cloud infrastructure.

    This hybrid cloud model provides businesses with more deployment options and greater flexibility to scale computing resources. It also helps in reducing capital expenditure and improving security by allowing sensitive data to be stored on a private cloud. A hybrid cloud strategy enables businesses to allocate resources efficiently, keeping less critical applications on the public cloud, while mission-critical applications run on the private cloud.

    Current State of Hybrid Cloud Computing

    The hybrid cloud market is in a state of rapid growth and evolution. As businesses increasingly recognize the benefits of a hybrid approach, the adoption of hybrid cloud strategies is on the rise.

    In a world where digital transformation is the norm, hybrid cloud computing has emerged as a key enabler. It offers the flexibility needed to adapt quickly to changing business conditions, the scalability to handle sudden increases in workload, and the security to protect sensitive data. These benefits have made hybrid cloud a cornerstone of digital transformation strategies.

    However, the journey to hybrid cloud is not without its challenges. Businesses are grappling with issues related to data security, compliance, integration, and management. There are also complexities related to workload portability, interoperability, and the need for skilled resources. Despite these challenges, the adoption of hybrid cloud continues to grow as businesses seek to leverage its benefits to drive innovation and competitive advantage.

    Emerging Trends in Hybrid Cloud for 2024

    Increased Adoption Across Industries

    Many industries, including the banking and finance sector, healthcare, retail, manufacturing, and even the government sector, are seeing increased adoption of hybrid cloud strategies. This trend is driven by the need for greater agility and flexibility, better cost management, and improved security and compliance.

    In the healthcare sector, for example, hybrid cloud is enabling the integration of disparate systems, facilitating the sharing of patient data, and supporting telehealth initiatives. In the banking sector, it is helping to manage risk, improve customer experiences, and drive innovation. In retail, hybrid cloud is supporting omnichannel strategies, personalizing customer experiences, and improving supply chain efficiency.

    Advancements in Cloud Technology

    The hybrid cloud landscape in 2024 will be shaped by advancements in cloud technologies. Technologies like containers and Kubernetes are simplifying the deployment and management of applications, making it easier for businesses to adopt a hybrid cloud strategy. The rise of serverless computing is also contributing to the growth of hybrid cloud by eliminating the need to manage servers and allowing developers to focus on writing code.

    Furthermore, advancements in networking technologies are making it easier to connect and integrate public and private clouds. The emergence of 5G is expected to further accelerate the adoption of hybrid cloud by providing the high-speed connectivity needed to support real-time applications.

    Integration of AI and Machine Learning

    The integration of artificial intelligence (AI) and machine learning (ML) into hybrid cloud environments is a trend that is rapidly gaining momentum. One key aspect of this integration is the ability to use AI for better resource management within the hybrid cloud. AI algorithms can analyze patterns in data usage and application performance, allowing for more efficient allocation of resources across public and private cloud environments.

    Furthermore, AI and ML are also facilitating better data management and analytics. Cloud-based services are making AI/ML more accessible to businesses of all sizes. By integrating these technologies, businesses can unlock insights from vast amounts of data stored across different cloud environments.

    Predictions for Hybrid Cloud in 2024

    Growth in Edge Computing Integration

    By 2024, the integration of edge computing with hybrid cloud architectures is expected to grow significantly. Edge computing brings data processing closer to the location where it is needed, optimizing response times and saving bandwidth. 

    In a hybrid cloud context, this means that organizations can process critical data at the edge, in real-time, while still leveraging the cloud for less time-sensitive tasks. This integration is particularly beneficial for industries like manufacturing and autonomous vehicles, where real-time data processing is crucial. The combination of edge and hybrid cloud computing enables businesses to harness the power of cloud computing while maintaining the speed and efficiency of edge processing.

    Improved Security and Compliance Measures

    In 2024, we anticipate significant advancements in the security and compliance aspects of hybrid cloud environments. As these environments become more complex, the need for robust security measures that span both public and private clouds is crucial. Enhanced encryption techniques, more sophisticated identity and access management systems, and advanced threat detection tools will become standard. 

    Additionally, we expect to see the development of more streamlined compliance benchmarks and frameworks designed specifically for hybrid cloud architectures, simplifying the process of adhering to various regulatory standards and ensuring data privacy and protection across multiple platforms.

    Innovations in Cloud Management Platforms

    The year 2024 is likely to witness substantial innovations in cloud management platforms, driven by the need to manage complex hybrid cloud environments more efficiently. These platforms will offer enhanced capabilities in terms of automation, orchestration, and unified management across multiple cloud services. 

    The use of AI and machine learning for predictive analysis, resource optimization, and proactive problem resolution will become more prevalent. These platforms will also provide better tools for cost management and analytics, giving businesses a more granular understanding of their cloud usage and enabling more cost-effective decision-making.

    Customizable and Flexible Cloud Solutions

    As hybrid cloud environments continue to evolve, 2024 will likely see a rise in more customizable and flexible cloud solutions tailored to specific business needs. Providers will offer a range of options that allow businesses to mix and match services from both public and private clouds, creating highly personalized cloud environments. 

    This customization will extend to aspects like security, performance, and compliance, allowing businesses to fine-tune their cloud infrastructure to their specific requirements. Such flexibility will be particularly beneficial for businesses in niche markets or those with unique operational needs, enabling them to leverage the power of cloud computing without compromising on their specific requirements.

    Conclusion

    By 2024, hybrid cloud computing will have significantly evolved, becoming a critical component in the digital transformation strategies of various industries. This technology offers a blend of public and private cloud benefits, crucial for DevOps teams in terms of flexibility, scalability, and security. The integration of advanced technologies like AI, machine learning, and edge computing will enhance resource management, data analytics, and real-time data processing. Additionally, the hybrid cloud’s role in ensuring agility, better cost management, and compliance is expected to drive its wider adoption across sectors like healthcare, banking, retail, and government.

    The landscape will also see advancements in security and compliance, with sophisticated measures spanning both cloud types and cloud management platforms will evolve to include AI and machine learning for more efficient operations. Customizable and flexible cloud solutions will become prevalent, allowing businesses to tailor their cloud environments according to specific needs. Overall, hybrid cloud in 2024 will be a strategic enabler, equipping businesses with the necessary tools and capabilities to thrive in an increasingly digital world.